refactor: replace Chinese comments with English in frontend components

- Replace all Chinese inline comments with English equivalents across 24 frontend component files
- Update JSDoc comments to use English for better code documentation
- Improve code readability and maintainability for international development team
- Standardize comment style across directories, endpoints, ip-addresses, subdomains, and websites components
- Ensure consistency with previous frontend refactoring efforts

.github/workflows/docker-build.yml

@@ -106,16 +106,17 @@ jobs:
             ${{ steps.version.outputs.IS_RELEASE == 'true' && format('{0}/{1}:latest', env.IMAGE_PREFIX, matrix.image) || '' }}
           build-args: |
             IMAGE_TAG=${{ steps.version.outputs.VERSION }}
-          cache-from: type=gha
-          cache-to: type=gha,mode=max
+          cache-from: type=gha,scope=${{ matrix.image }}
+          cache-to: type=gha,mode=max,scope=${{ matrix.image }}
           provenance: false
           sbom: false
 
   # 所有镜像构建成功后，更新 VERSION 文件
+  # 只有正式版本（不含 -dev, -alpha, -beta, -rc 等后缀）才更新
   update-version:
     runs-on: ubuntu-latest
     needs: build
-    if: startsWith(github.ref, 'refs/tags/v')
+    if: startsWith(github.ref, 'refs/tags/v') && !contains(github.ref, '-')
     steps:
       - name: Checkout
         uses: actions/checkout@v4

.gitignore

@@ -96,6 +96,7 @@ backend/vendor/
 .idea/
 .cursor/
 .claude/
+.kiro/
 .playwright-mcp/
 *.swp
 *.swo
@@ -131,3 +132,5 @@ temp/
 
 HGETALL
 KEYS
+vuln_scan/input_endpoints.txt
+open-in-v0

README.md

@@ -25,23 +25,16 @@
 
 ---
 
+
 <p align="center">
-  <b>🌗 明暗模式切换</b>
+  <b>🎨 现代化 UI </b>
 </p>
 
 <p align="center">
-  <img src="docs/screenshots/light.png" alt="Light Mode" width="49%">
-  <img src="docs/screenshots/dark.png" alt="Dark Mode" width="49%">
-</p>
-
-<p align="center">
-  <b>🎨 多种 UI 主题</b>
-</p>
-
-<p align="center">
-  <img src="docs/screenshots/bubblegum.png" alt="Bubblegum" width="32%">
-  <img src="docs/screenshots/cosmic-night.png" alt="Cosmic Night" width="32%">
-  <img src="docs/screenshots/quantum-rose.png" alt="Quantum Rose" width="32%">
+  <img src="docs/screenshots/light.png" alt="Light Mode" width="24%">
+  <img src="docs/screenshots/bubblegum.png" alt="Bubblegum" width="24%">
+  <img src="docs/screenshots/cosmic-night.png" alt="Cosmic Night" width="24%">
+  <img src="docs/screenshots/quantum-rose.png" alt="Quantum Rose" width="24%">
 </p>
 
 ## 📚 文档
@@ -165,17 +158,9 @@ flowchart TB
 ### 📊 可视化界面
 - **数据统计** - 资产/漏洞统计仪表盘
 - **实时通知** - WebSocket 消息推送
-- **暗色主题** - 支持明暗主题切换
 
 ---
 
-## 🛠️ 技术栈
-
-- **前端**: Next.js + React + TailwindCSS
-- **后端**: Django + Django REST Framework
-- **数据库**: PostgreSQL + Redis
-- **部署**: Docker + Nginx
-
 ## 📦 快速开始
 
 ### 环境要求
@@ -192,11 +177,19 @@ cd xingrin
 
 # 安装并启动（生产模式）
 sudo ./install.sh
+
+# 🇨🇳 中国大陆用户推荐使用镜像加速
+sudo ./install.sh --mirror
 ```
 
+> **💡 --mirror 参数说明**
+> - 自动配置 Docker 镜像加速（国内镜像源）
+> - 加速 Git 仓库克隆（Nuclei 模板等）
+> - 大幅提升安装速度，避免网络超时
+
 ### 访问服务
 
-- **Web 界面**: `https://localhost` 
+- **Web 界面**: `https://ip:8083` 
 
 ### 常用命令
 
@@ -212,9 +205,6 @@ sudo ./restart.sh
 
 # 卸载
 sudo ./uninstall.sh
-
-# 更新
-sudo ./update.sh
 ```
 
 ## 🤝 反馈与贡献

VERSION

@@ -1 +1 @@
-v1.0.30
+v1.1.14

backend/apps/asset/dtos/asset/directory_dto.py

@@ -7,7 +7,6 @@ from typing import Optional
 @dataclass
 class DirectoryDTO:
     """目录数据传输对象"""
-    website_id: int
     target_id: int
     url: str
     status: Optional[int] = None

backend/apps/asset/dtos/asset/website_dto.py

@@ -9,7 +9,7 @@ class WebSiteDTO:
     """网站数据传输对象"""
     target_id: int
     url: str
-    host: str
+    host: str = ''
     title: str = ''
     status_code: Optional[int] = None
     content_length: Optional[int] = None

backend/apps/asset/dtos/snapshot/directory_snapshot_dto.py

@@ -12,11 +12,10 @@ class DirectorySnapshotDTO:
     
     用于保存扫描过程中发现的目录信息到快照表
     
-    注意：website_id 和 target_id 只用于传递数据和转换为资产 DTO，不会保存到快照表中。
+    注意：target_id 只用于传递数据和转换为资产 DTO，不会保存到快照表中。
     快照只属于 scan。
     """
     scan_id: int
-    website_id: int  # 仅用于传递数据，不保存到数据库
     target_id: int  # 仅用于传递数据，不保存到数据库
     url: str
     status: Optional[int] = None
@@ -36,7 +35,6 @@ class DirectorySnapshotDTO:
             DirectoryDTO: 资产表 DTO
         """
         return DirectoryDTO(
-            website_id=self.website_id,
             target_id=self.target_id,
             url=self.url,
             status=self.status,

backend/apps/asset/models/asset_models.py

@@ -4,13 +4,6 @@ from django.contrib.postgres.fields import ArrayField
 from django.core.validators import MinValueValidator, MaxValueValidator
 
 
-class SoftDeleteManager(models.Manager):
-    """软删除管理器：默认只返回未删除的记录"""
-    
-    def get_queryset(self):
-        return super().get_queryset().filter(deleted_at__isnull=True)
-
-
 class Subdomain(models.Model):
     """
     子域名模型（纯资产表）
@@ -29,33 +22,24 @@ class Subdomain(models.Model):
         help_text='所属的扫描目标（主关联字段，表示所属关系，不能为空）'
     )
     name = models.CharField(max_length=1000, help_text='子域名名称')
-    discovered_at = models.DateTimeField(auto_now_add=True, help_text='首次发现时间')
-    
-    # ==================== 软删除字段 ====================
-    deleted_at = models.DateTimeField(null=True, blank=True, db_index=True, help_text='删除时间（NULL表示未删除）')
-    
-    # ==================== 管理器 ====================
-    objects = SoftDeleteManager()  # 默认管理器：只返回未删除的记录
-    all_objects = models.Manager()  # 全量管理器：包括已删除的记录（用于硬删除）
+    created_at = models.DateTimeField(auto_now_add=True, help_text='创建时间')
 
     class Meta:
         db_table = 'subdomain'
         verbose_name = '子域名'
         verbose_name_plural = '子域名'
-        ordering = ['-discovered_at']
+        ordering = ['-created_at']
         indexes = [
-            models.Index(fields=['-discovered_at']),
+            models.Index(fields=['-created_at']),
             models.Index(fields=['name', 'target']),  # 复合索引，优化 get_by_names_and_target_id 批量查询
             models.Index(fields=['target']),     # 优化从target_id快速查找下面的子域名
             models.Index(fields=['name']),            # 优化从name快速查找子域名，搜索场景
-            models.Index(fields=['deleted_at', '-discovered_at']),  # 软删除 + 时间索引
         ]
         constraints = [
-            # 部分唯一约束：只对未删除记录生效
+            # 普通唯一约束：name + target 组合唯一
             models.UniqueConstraint(
                 fields=['name', 'target'],
-                condition=models.Q(deleted_at__isnull=True),
-                name='unique_name_target_active'
+                name='unique_subdomain_name_target'
             )
         ]
 
@@ -87,7 +71,7 @@ class Endpoint(models.Model):
         default='',
         help_text='重定向地址（HTTP 3xx 响应头 Location）'
     )
-    discovered_at = models.DateTimeField(auto_now_add=True, help_text='发现时间')
+    created_at = models.DateTimeField(auto_now_add=True, help_text='创建时间')
     title = models.CharField(
         max_length=1000,
         blank=True,
@@ -139,33 +123,25 @@ class Endpoint(models.Model):
         default=list,
         help_text='匹配的GF模式列表，用于识别敏感端点（如api, debug, config等）'
     )
-    
-    # ==================== 软删除字段 ====================
-    deleted_at = models.DateTimeField(null=True, blank=True, db_index=True, help_text='删除时间（NULL表示未删除）')
-    
-    # ==================== 管理器 ====================
-    objects = SoftDeleteManager()  # 默认管理器：只返回未删除的记录
-    all_objects = models.Manager()  # 全量管理器：包括已删除的记录（用于硬删除）
 
     class Meta:
         db_table = 'endpoint'
         verbose_name = '端点'
         verbose_name_plural = '端点'
-        ordering = ['-discovered_at']
+        ordering = ['-created_at']
         indexes = [
-            models.Index(fields=['-discovered_at']),
+            models.Index(fields=['-created_at']),
             models.Index(fields=['target']),       # 优化从target_id快速查找下面的端点（主关联字段）
             models.Index(fields=['url']),          # URL索引，优化查询性能
             models.Index(fields=['host']),         # host索引，优化根据主机名查询
             models.Index(fields=['status_code']),  # 状态码索引，优化筛选
-            models.Index(fields=['deleted_at', '-discovered_at']),  # 软删除 + 时间索引
+            models.Index(fields=['title']),        # title索引，优化智能过滤搜索
         ]
         constraints = [
-            # 部分唯一约束：只对未删除记录生效
+            # 普通唯一约束：url + target 组合唯一
             models.UniqueConstraint(
                 fields=['url', 'target'],
-                condition=models.Q(deleted_at__isnull=True),
-                name='unique_endpoint_url_target_active'
+                name='unique_endpoint_url_target'
             )
         ]
 
@@ -197,7 +173,7 @@ class WebSite(models.Model):
         default='',
         help_text='重定向地址（HTTP 3xx 响应头 Location）'
     )
-    discovered_at = models.DateTimeField(auto_now_add=True, help_text='发现时间')
+    created_at = models.DateTimeField(auto_now_add=True, help_text='创建时间')
     title = models.CharField(
         max_length=1000,
         blank=True,
@@ -243,32 +219,25 @@ class WebSite(models.Model):
         blank=True,
         help_text='是否支持虚拟主机'
     )
-    
-    # ==================== 软删除字段 ====================
-    deleted_at = models.DateTimeField(null=True, blank=True, db_index=True, help_text='删除时间（NULL表示未删除）')
-    
-    # ==================== 管理器 ====================
-    objects = SoftDeleteManager()  # 默认管理器：只返回未删除的记录
-    all_objects = models.Manager()  # 全量管理器：包括已删除的记录（用于硬删除）
 
     class Meta:
         db_table = 'website'
         verbose_name = '站点'
         verbose_name_plural = '站点'
-        ordering = ['-discovered_at']
+        ordering = ['-created_at']
         indexes = [
-            models.Index(fields=['-discovered_at']),
+            models.Index(fields=['-created_at']),
             models.Index(fields=['url']),  # URL索引，优化查询性能
             models.Index(fields=['host']),  # host索引，优化根据主机名查询
             models.Index(fields=['target']),     # 优化从target_id快速查找下面的站点
-            models.Index(fields=['deleted_at', '-discovered_at']),  # 软删除 + 时间索引
+            models.Index(fields=['title']),      # title索引，优化智能过滤搜索
+            models.Index(fields=['status_code']),  # 状态码索引，优化智能过滤搜索
         ]
         constraints = [
-            # 部分唯一约束：只对未删除记录生效
+            # 普通唯一约束：url + target 组合唯一
             models.UniqueConstraint(
                 fields=['url', 'target'],
-                condition=models.Q(deleted_at__isnull=True),
-                name='unique_website_url_target_active'
+                name='unique_website_url_target'
             )
         ]
 
@@ -282,19 +251,11 @@ class Directory(models.Model):
     """
 
     id = models.AutoField(primary_key=True)
-    website = models.ForeignKey(
-        'Website',
-        on_delete=models.CASCADE,
-        related_name='directories',
-        help_text='所属的站点（主关联字段，表示所属关系，不能为空）'
-    )
     target = models.ForeignKey(
-        'targets.Target',  # 使用字符串引用
+        'targets.Target',
         on_delete=models.CASCADE,
         related_name='directories',
-        null=True,
-        blank=True,
-        help_text='所属的扫描目标（冗余字段，用于快速查询）'
+        help_text='所属的扫描目标'
     )
     
     url = models.CharField(
@@ -335,34 +296,24 @@ class Directory(models.Model):
         help_text='请求耗时（单位：纳秒）'
     )
     
-    discovered_at = models.DateTimeField(auto_now_add=True, help_text='发现时间')
-    
-    # ==================== 软删除字段 ====================
-    deleted_at = models.DateTimeField(null=True, blank=True, db_index=True, help_text='删除时间（NULL表示未删除）')
-    
-    # ==================== 管理器 ====================
-    objects = SoftDeleteManager()  # 默认管理器：只返回未删除的记录
-    all_objects = models.Manager()  # 全量管理器：包括已删除的记录（用于硬删除）
+    created_at = models.DateTimeField(auto_now_add=True, help_text='创建时间')
 
     class Meta:
         db_table = 'directory'
         verbose_name = '目录'
         verbose_name_plural = '目录'
-        ordering = ['-discovered_at']
+        ordering = ['-created_at']
         indexes = [
-            models.Index(fields=['-discovered_at']),
+            models.Index(fields=['-created_at']),
             models.Index(fields=['target']),     # 优化从target_id快速查找下面的目录
             models.Index(fields=['url']),        # URL索引，优化搜索和唯一约束
-            models.Index(fields=['website']),    # 站点索引，优化按站点查询
             models.Index(fields=['status']),     # 状态码索引，优化筛选
-            models.Index(fields=['deleted_at', '-discovered_at']),  # 软删除 + 时间索引
         ]
         constraints = [
-            # 部分唯一约束：只对未删除记录生效
+            # 普通唯一约束：target + url 组合唯一
             models.UniqueConstraint(
-                fields=['website', 'url'],
-                condition=models.Q(deleted_at__isnull=True),
-                name='unique_directory_url_website_active'
+                fields=['target', 'url'],
+                name='unique_directory_url_target'
             ),
         ]
 
@@ -410,43 +361,29 @@ class HostPortMapping(models.Model):
     )
     
     # ==================== 时间字段 ====================
-    discovered_at = models.DateTimeField(
+    created_at = models.DateTimeField(
         auto_now_add=True,
-        help_text='发现时间'
+        help_text='创建时间'
     )
-    
-    # ==================== 软删除字段 ====================
-    deleted_at = models.DateTimeField(
-        null=True,
-        blank=True,
-        db_index=True,
-        help_text='删除时间（NULL表示未删除）'
-    )
-    
-    # ==================== 管理器 ====================
-    objects = SoftDeleteManager()  # 默认管理器：只返回未删除的记录
-    all_objects = models.Manager()  # 全量管理器：包括已删除的记录（用于硬删除）
 
     class Meta:
         db_table = 'host_port_mapping'
         verbose_name = '主机端口映射'
         verbose_name_plural = '主机端口映射'
-        ordering = ['-discovered_at']
+        ordering = ['-created_at']
         indexes = [
             models.Index(fields=['target']),           # 优化按目标查询
             models.Index(fields=['host']),             # 优化按主机名查询
             models.Index(fields=['ip']),               # 优化按IP查询
             models.Index(fields=['port']),             # 优化按端口查询
             models.Index(fields=['host', 'ip']),       # 优化组合查询
-            models.Index(fields=['-discovered_at']),   # 优化时间排序
-            models.Index(fields=['deleted_at', '-discovered_at']),  # 软删除 + 时间索引
+            models.Index(fields=['-created_at']),   # 优化时间排序
         ]
         constraints = [
-            # 复合唯一约束：target + host + ip + port 组合唯一（只对未删除记录生效）
+            # 复合唯一约束：target + host + ip + port 组合唯一
             models.UniqueConstraint(
                 fields=['target', 'host', 'ip', 'port'],
-                condition=models.Q(deleted_at__isnull=True),
-                name='unique_target_host_ip_port_active'
+                name='unique_target_host_ip_port'
             ),
         ]
 
@@ -474,7 +411,7 @@ class Vulnerability(models.Model):
     )
     
     # ==================== 核心字段 ====================
-    url = models.TextField(help_text='漏洞所在的URL')
+    url = models.CharField(max_length=2000, help_text='漏洞所在的URL')
     vuln_type = models.CharField(max_length=100, help_text='漏洞类型（如 xss, sqli）')
     severity = models.CharField(
         max_length=20,
@@ -488,27 +425,20 @@ class Vulnerability(models.Model):
     raw_output = models.JSONField(blank=True, default=dict, help_text='工具原始输出')
     
     # ==================== 时间字段 ====================
-    discovered_at = models.DateTimeField(auto_now_add=True, help_text='首次发现时间')
-    
-    # ==================== 软删除字段 ====================
-    deleted_at = models.DateTimeField(null=True, blank=True, db_index=True, help_text='删除时间（NULL表示未删除）')
-    
-    # ==================== 管理器 ====================
-    objects = SoftDeleteManager()
-    all_objects = models.Manager()
+    created_at = models.DateTimeField(auto_now_add=True, help_text='创建时间')
 
     class Meta:
         db_table = 'vulnerability'
         verbose_name = '漏洞'
         verbose_name_plural = '漏洞'
-        ordering = ['-discovered_at']
+        ordering = ['-created_at']
         indexes = [
             models.Index(fields=['target']),
             models.Index(fields=['vuln_type']),
             models.Index(fields=['severity']),
             models.Index(fields=['source']),
-            models.Index(fields=['-discovered_at']),
-            models.Index(fields=['deleted_at', '-discovered_at']),
+            models.Index(fields=['url']),          # url索引，优化智能过滤搜索
+            models.Index(fields=['-created_at']),
         ]
 
     def __str__(self):

backend/apps/asset/models/snapshot_models.py

@@ -15,17 +15,17 @@ class SubdomainSnapshot(models.Model):
     )
     
     name = models.CharField(max_length=1000, help_text='子域名名称')
-    discovered_at = models.DateTimeField(auto_now_add=True, help_text='发现时间')
+    created_at = models.DateTimeField(auto_now_add=True, help_text='创建时间')
     
     class Meta:
         db_table = 'subdomain_snapshot'
         verbose_name = '子域名快照'
         verbose_name_plural = '子域名快照'
-        ordering = ['-discovered_at']
+        ordering = ['-created_at']
         indexes = [
             models.Index(fields=['scan']),
             models.Index(fields=['name']),
-            models.Index(fields=['-discovered_at']),
+            models.Index(fields=['-created_at']),
         ]
         constraints = [
             # 唯一约束：同一次扫描中，同一个子域名只能记录一次
@@ -70,18 +70,19 @@ class WebsiteSnapshot(models.Model):
     )
     body_preview = models.TextField(blank=True, default='', help_text='响应体预览')
     vhost = models.BooleanField(null=True, blank=True, help_text='虚拟主机标志')
-    discovered_at = models.DateTimeField(auto_now_add=True, help_text='发现时间')
+    created_at = models.DateTimeField(auto_now_add=True, help_text='创建时间')
 
     class Meta:
         db_table = 'website_snapshot'
         verbose_name = '网站快照'
         verbose_name_plural = '网站快照'
-        ordering = ['-discovered_at']
+        ordering = ['-created_at']
         indexes = [
             models.Index(fields=['scan']),
             models.Index(fields=['url']),
             models.Index(fields=['host']),  # host索引，优化根据主机名查询
-            models.Index(fields=['-discovered_at']),
+            models.Index(fields=['title']),  # title索引，优化标题搜索
+            models.Index(fields=['-created_at']),
         ]
         constraints = [
             # 唯一约束：同一次扫描中，同一个URL只能记录一次
@@ -118,18 +119,19 @@ class DirectorySnapshot(models.Model):
     lines = models.IntegerField(null=True, blank=True, help_text='响应体行数（按换行符分割）')
     content_type = models.CharField(max_length=200, blank=True, default='', help_text='响应头 Content-Type 值')
     duration = models.BigIntegerField(null=True, blank=True, help_text='请求耗时（单位：纳秒）')
-    discovered_at = models.DateTimeField(auto_now_add=True, help_text='发现时间')
+    created_at = models.DateTimeField(auto_now_add=True, help_text='创建时间')
 
     class Meta:
         db_table = 'directory_snapshot'
         verbose_name = '目录快照'
         verbose_name_plural = '目录快照'
-        ordering = ['-discovered_at']
+        ordering = ['-created_at']
         indexes = [
             models.Index(fields=['scan']),
             models.Index(fields=['url']),
             models.Index(fields=['status']),  # 状态码索引，优化筛选
-            models.Index(fields=['-discovered_at']),
+            models.Index(fields=['content_type']),  # content_type索引，优化内容类型搜索
+            models.Index(fields=['-created_at']),
         ]
         constraints = [
             # 唯一约束：同一次扫描中，同一个目录URL只能记录一次
@@ -183,16 +185,16 @@ class HostPortMappingSnapshot(models.Model):
     )
     
     # ==================== 时间字段 ====================
-    discovered_at = models.DateTimeField(
+    created_at = models.DateTimeField(
         auto_now_add=True,
-        help_text='发现时间'
+        help_text='创建时间'
     )
 
     class Meta:
         db_table = 'host_port_mapping_snapshot'
         verbose_name = '主机端口映射快照'
         verbose_name_plural = '主机端口映射快照'
-        ordering = ['-discovered_at']
+        ordering = ['-created_at']
         indexes = [
             models.Index(fields=['scan']),             # 优化按扫描查询
             models.Index(fields=['host']),             # 优化按主机名查询
@@ -200,7 +202,7 @@ class HostPortMappingSnapshot(models.Model):
             models.Index(fields=['port']),             # 优化按端口查询
             models.Index(fields=['host', 'ip']),       # 优化组合查询
             models.Index(fields=['scan', 'host']),     # 优化扫描+主机查询
-            models.Index(fields=['-discovered_at']),   # 优化时间排序
+            models.Index(fields=['-created_at']),   # 优化时间排序
         ]
         constraints = [
             # 复合唯一约束：同一次扫描中，scan + host + ip + port 组合唯一
@@ -257,19 +259,21 @@ class EndpointSnapshot(models.Model):
         default=list,
         help_text='匹配的GF模式列表'
     )
-    discovered_at = models.DateTimeField(auto_now_add=True, help_text='发现时间')
+    created_at = models.DateTimeField(auto_now_add=True, help_text='创建时间')
 
     class Meta:
         db_table = 'endpoint_snapshot'
         verbose_name = '端点快照'
         verbose_name_plural = '端点快照'
-        ordering = ['-discovered_at']
+        ordering = ['-created_at']
         indexes = [
             models.Index(fields=['scan']),
             models.Index(fields=['url']),
             models.Index(fields=['host']),  # host索引，优化根据主机名查询
+            models.Index(fields=['title']),  # title索引，优化标题搜索
             models.Index(fields=['status_code']),  # 状态码索引，优化筛选
-            models.Index(fields=['-discovered_at']),
+            models.Index(fields=['webserver']),  # webserver索引，优化服务器搜索
+            models.Index(fields=['-created_at']),
         ]
         constraints = [
             # 唯一约束：同一次扫描中，同一个URL只能记录一次
@@ -302,7 +306,7 @@ class VulnerabilitySnapshot(models.Model):
     )
     
     # ==================== 核心字段 ====================
-    url = models.TextField(help_text='漏洞所在的URL')
+    url = models.CharField(max_length=2000, help_text='漏洞所在的URL')
     vuln_type = models.CharField(max_length=100, help_text='漏洞类型（如 xss, sqli）')
     severity = models.CharField(
         max_length=20,
@@ -316,19 +320,20 @@ class VulnerabilitySnapshot(models.Model):
     raw_output = models.JSONField(blank=True, default=dict, help_text='工具原始输出')
     
     # ==================== 时间字段 ====================
-    discovered_at = models.DateTimeField(auto_now_add=True, help_text='发现时间')
+    created_at = models.DateTimeField(auto_now_add=True, help_text='创建时间')
 
     class Meta:
         db_table = 'vulnerability_snapshot'
         verbose_name = '漏洞快照'
         verbose_name_plural = '漏洞快照'
-        ordering = ['-discovered_at']
+        ordering = ['-created_at']
         indexes = [
             models.Index(fields=['scan']),
+            models.Index(fields=['url']),  # url索引，优化URL搜索
             models.Index(fields=['vuln_type']),
             models.Index(fields=['severity']),
             models.Index(fields=['source']),
-            models.Index(fields=['-discovered_at']),
+            models.Index(fields=['-created_at']),
         ]
 
     def __str__(self):

backend/apps/asset/repositories/asset/directory_repository.py

@@ -3,162 +3,141 @@ Django ORM 实现的 Directory Repository
 """
 
 import logging
-from typing import List, Tuple, Dict, Iterator
-from django.db import transaction, IntegrityError, OperationalError, DatabaseError
-from django.utils import timezone
+from typing import List, Iterator
+from django.db import transaction
 
 from apps.asset.models.asset_models import Directory
 from apps.asset.dtos import DirectoryDTO
 from apps.common.decorators import auto_ensure_db_connection
+from apps.common.utils import deduplicate_for_bulk
 
 logger = logging.getLogger(__name__)
 
 
-
 @auto_ensure_db_connection
 class DjangoDirectoryRepository:
     """Django ORM 实现的 Directory Repository"""
 
-    def bulk_create_ignore_conflicts(self, items: List[DirectoryDTO]) -> int:
+    def bulk_upsert(self, items: List[DirectoryDTO]) -> int:
         """
-        批量创建 Directory，忽略冲突
+        批量创建或更新 Directory（upsert）
+        
+        存在则更新所有字段，不存在则创建。
+        使用 Django 原生 update_conflicts。
+        
+        注意：自动按模型唯一约束去重，保留最后一条记录。
         
         Args:
             items: Directory DTO 列表
             
         Returns:
-            int: 实际创建的记录数
-            
-        Raises:
-            IntegrityError: 数据完整性错误
-            OperationalError: 数据库操作错误
-            DatabaseError: 数据库错误
+            int: 处理的记录数
         """
         if not items:
             return 0
-
+        
         try:
-            # 转换为 Django 模型对象
-            directory_objects = [
+            # 自动按模型唯一约束去重
+            unique_items = deduplicate_for_bulk(items, Directory)
+            
+            # 直接从 DTO 字段构建 Model
+            directories = [
                 Directory(
-                    website_id=item.website_id,
                     target_id=item.target_id,
                     url=item.url,
                     status=item.status,
                     content_length=item.content_length,
                     words=item.words,
                     lines=item.lines,
-                    content_type=item.content_type,
+                    content_type=item.content_type or '',
                     duration=item.duration
                 )
-                for item in items
+                for item in unique_items
             ]
-
+            
             with transaction.atomic():
-                # 批量插入或忽略冲突
-                # 如果 website + url 已存在，忽略冲突
                 Directory.objects.bulk_create(
-                    directory_objects,
-                    ignore_conflicts=True
+                    directories,
+                    update_conflicts=True,
+                    unique_fields=['target', 'url'],
+                    update_fields=[
+                        'status', 'content_length', 'words',
+                        'lines', 'content_type', 'duration'
+                    ],
+                    batch_size=1000
                 )
-
-            logger.debug(f"成功处理 {len(items)} 条 Directory 记录")
-            return len(items)
-
-        except IntegrityError as e:
-            logger.error(
-                f"批量插入 Directory 失败 - 数据完整性错误: {e}, "
-                f"记录数: {len(items)}"
-            )
-            raise
-
-        except OperationalError as e:
-            logger.error(
-                f"批量插入 Directory 失败 - 数据库操作错误: {e}, "
-                f"记录数: {len(items)}"
-            )
-            raise
-
-        except DatabaseError as e:
-            logger.error(
-                f"批量插入 Directory 失败 - 数据库错误: {e}, "
-                f"记录数: {len(items)}"
-            )
-            raise
-
+            
+            logger.debug(f"批量 upsert Directory 成功: {len(unique_items)} 条")
+            return len(unique_items)
+                
         except Exception as e:
-            logger.error(
-                f"批量插入 Directory 失败 - 未知错误: {e}, "
-                f"记录数: {len(items)}, "
-                f"错误类型: {type(e).__name__}",
-                exc_info=True
-            )
+            logger.error(f"批量 upsert Directory 失败: {e}")
             raise
 
-    def get_by_website(self, website_id: int) -> List[DirectoryDTO]:
+    def bulk_create_ignore_conflicts(self, items: List[DirectoryDTO]) -> int:
         """
-        获取指定站点的所有目录
+        批量创建 Directory（存在即跳过）
+        
+        与 bulk_upsert 不同，此方法不会更新已存在的记录。
+        适用于批量添加场景，只提供 URL，没有其他字段数据。
+        
+        注意：自动按模型唯一约束去重，保留最后一条记录。
         
         Args:
-            website_id: 站点 ID
+            items: Directory DTO 列表
             
         Returns:
-            List[DirectoryDTO]: 目录列表
+            int: 处理的记录数
         """
+        if not items:
+            return 0
+        
         try:
-            directories = Directory.objects.filter(website_id=website_id)
-            return [
-                DirectoryDTO(
-                    website_id=d.website_id,
-                    target_id=d.target_id,
-                    url=d.url,
-                    status=d.status,
-                    content_length=d.content_length,
-                    words=d.words,
-                    lines=d.lines,
-                    content_type=d.content_type,
-                    duration=d.duration
+            # 自动按模型唯一约束去重
+            unique_items = deduplicate_for_bulk(items, Directory)
+            
+            directories = [
+                Directory(
+                    target_id=item.target_id,
+                    url=item.url,
+                    status=item.status,
+                    content_length=item.content_length,
+                    words=item.words,
+                    lines=item.lines,
+                    content_type=item.content_type or '',
+                    duration=item.duration
                 )
-                for d in directories
+                for item in unique_items
             ]
-
-        except Exception as e:
-            logger.error(f"获取目录列表失败 - Website ID: {website_id}, 错误: {e}")
-            raise
-
-    def count_by_website(self, website_id: int) -> int:
-        """
-        统计指定站点的目录总数
-        
-        Args:
-            website_id: 站点 ID
             
-        Returns:
-            int: 目录总数
-        """
-        try:
-            count = Directory.objects.filter(website_id=website_id).count()
-            logger.debug(f"Website {website_id} 的目录总数: {count}")
-            return count
-
+            with transaction.atomic():
+                Directory.objects.bulk_create(
+                    directories,
+                    ignore_conflicts=True,
+                    batch_size=1000
+                )
+            
+            logger.debug(f"批量创建 Directory 成功（ignore_conflicts）: {len(unique_items)} 条")
+            return len(unique_items)
+                
         except Exception as e:
-            logger.error(f"统计目录数量失败 - Website ID: {website_id}, 错误: {e}")
+            logger.error(f"批量创建 Directory 失败: {e}")
             raise
-    
+
+    def count_by_target(self, target_id: int) -> int:
+        """统计目标下的目录总数"""
+        return Directory.objects.filter(target_id=target_id).count()
+
     def get_all(self):
-        """
-        获取所有目录
-        
-        Returns:
-            QuerySet: 目录查询集
-        """
-        return Directory.objects.all()
-    
+        """获取所有目录"""
+        return Directory.objects.all().order_by('-created_at')
+
     def get_by_target(self, target_id: int):
-        return Directory.objects.filter(target_id=target_id).select_related('website').order_by('-discovered_at')
+        """获取目标下的所有目录"""
+        return Directory.objects.filter(target_id=target_id).order_by('-created_at')
 
     def get_urls_for_export(self, target_id: int, batch_size: int = 1000) -> Iterator[str]:
-        """流式导出目标下的所有目录 URL（只查 url 字段，避免加载多余数据）。"""
+        """流式导出目标下的所有目录 URL"""
         try:
             queryset = (
                 Directory.objects
@@ -172,78 +151,31 @@ class DjangoDirectoryRepository:
         except Exception as e:
             logger.error("流式导出目录 URL 失败 - Target ID: %s, 错误: %s", target_id, e)
             raise
-    
-    def soft_delete_by_ids(self, directory_ids: List[int]) -> int:
+
+    def iter_raw_data_for_export(
+        self, 
+        target_id: int,
+        batch_size: int = 1000
+    ) -> Iterator[dict]:
         """
-        根据 ID 列表批量软删除Directory
+        流式获取原始数据用于 CSV 导出
         
         Args:
-            directory_ids: Directory ID 列表
+            target_id: 目标 ID
+            batch_size: 每批数据量
         
-        Returns:
-            软删除的记录数
+        Yields:
+            包含所有目录字段的字典
         """
-        try:
-            updated_count = (
-                Directory.objects
-                .filter(id__in=directory_ids)
-                .update(deleted_at=timezone.now())
+        qs = (
+            Directory.objects
+            .filter(target_id=target_id)
+            .values(
+                'url', 'status', 'content_length', 'words',
+                'lines', 'content_type', 'duration', 'created_at'
             )
-            logger.debug(
-                "批量软删除Directory成功 - Count: %s, 更新记录: %s",
-                len(directory_ids),
-                updated_count
-            )
-            return updated_count
-        except Exception as e:
-            logger.error(
-                "批量软删除Directory失败 - IDs: %s, 错误: %s",
-                directory_ids,
-                e
-            )
-            raise
-    
-    def hard_delete_by_ids(self, directory_ids: List[int]) -> Tuple[int, Dict[str, int]]:
-        """
-        根据 ID 列表硬删除Directory（使用数据库级 CASCADE）
+            .order_by('url')
+        )
         
-        Args:
-            directory_ids: Directory ID 列表
-        
-        Returns:
-            (删除的记录数, 删除详情字典)
-        """
-        try:
-            batch_size = 1000
-            total_deleted = 0
-            
-            logger.debug(f"开始批量删除 {len(directory_ids)} 个Directory（数据库 CASCADE）...")
-            
-            for i in range(0, len(directory_ids), batch_size):
-                batch_ids = directory_ids[i:i + batch_size]
-                count, _ = Directory.all_objects.filter(id__in=batch_ids).delete()
-                total_deleted += count
-                logger.debug(f"批次删除完成: {len(batch_ids)} 个Directory，删除 {count} 条记录")
-            
-            deleted_details = {
-                'directories': len(directory_ids),
-                'total': total_deleted,
-                'note': 'Database CASCADE - detailed stats unavailable'
-            }
-            
-            logger.debug(
-                "批量硬删除成功（CASCADE）- Directory数: %s, 总删除记录: %s",
-                len(directory_ids),
-                total_deleted
-            )
-            
-            return total_deleted, deleted_details
-        
-        except Exception as e:
-            logger.error(
-                "批量硬删除失败（CASCADE）- Directory数: %s, 错误: %s",
-                len(directory_ids),
-                str(e),
-                exc_info=True
-            )
-            raise
+        for row in qs.iterator(chunk_size=batch_size):
+            yield row

backend/apps/asset/repositories/asset/endpoint_repository.py

@@ -1,11 +1,12 @@
 """Endpoint Repository - Django ORM 实现"""
 
 import logging
-from typing import List, Optional, Tuple, Dict, Any
+from typing import List, Iterator
 
 from apps.asset.models import Endpoint
 from apps.asset.dtos.asset import EndpointDTO
 from apps.common.decorators import auto_ensure_db_connection
+from apps.common.utils import deduplicate_for_bulk
 from django.db import transaction
 
 logger = logging.getLogger(__name__)
@@ -15,25 +16,31 @@ logger = logging.getLogger(__name__)
 class DjangoEndpointRepository:
     """端点 Repository - 负责端点表的数据访问"""
     
-    def bulk_create_ignore_conflicts(self, items: List[EndpointDTO]) -> int:
+    def bulk_upsert(self, items: List[EndpointDTO]) -> int:
         """
-        批量创建端点（忽略冲突）
+        批量创建或更新端点（upsert）
+        
+        存在则更新所有字段，不存在则创建。
+        使用 Django 原生 update_conflicts。
+        
+        注意：自动按模型唯一约束去重，保留最后一条记录。
         
         Args:
             items: 端点 DTO 列表
             
         Returns:
-            int: 创建的记录数
+            int: 处理的记录数
         """
         if not items:
             return 0
         
         try:
-            endpoints = []
-            for item in items:
-                # Endpoint 模型当前只关联 target，不再依赖 website 外键
-                # 这里按照 EndpointDTO 的字段映射构造 Endpoint 实例
-                endpoints.append(Endpoint(
+            # 自动按模型唯一约束去重
+            unique_items = deduplicate_for_bulk(items, Endpoint)
+            
+            # 直接从 DTO 字段构建 Model
+            endpoints = [
+                Endpoint(
                     target_id=item.target_id,
                     url=item.url,
                     host=item.host or '',
@@ -47,62 +54,35 @@ class DjangoEndpointRepository:
                     vhost=item.vhost,
                     location=item.location or '',
                     matched_gf_patterns=item.matched_gf_patterns if item.matched_gf_patterns else []
-                ))
+                )
+                for item in unique_items
+            ]
             
             with transaction.atomic():
-                created = Endpoint.objects.bulk_create(
+                Endpoint.objects.bulk_create(
                     endpoints,
-                    ignore_conflicts=True,
+                    update_conflicts=True,
+                    unique_fields=['url', 'target'],
+                    update_fields=[
+                        'host', 'title', 'status_code', 'content_length',
+                        'webserver', 'body_preview', 'content_type', 'tech',
+                        'vhost', 'location', 'matched_gf_patterns'
+                    ],
                     batch_size=1000
                 )
-                return len(created)
+            
+            logger.debug(f"批量 upsert 端点成功: {len(unique_items)} 条")
+            return len(unique_items)
                 
         except Exception as e:
-            logger.error(f"批量创建端点失败: {e}")
+            logger.error(f"批量 upsert 端点失败: {e}")
             raise
     
-    def get_by_website(self, website_id: int) -> List[EndpointDTO]:
-        """
-        获取网站下的所有端点
-        
-        Args:
-            website_id: 网站 ID
-            
-        Returns:
-            List[EndpointDTO]: 端点列表
-        """
-        endpoints = Endpoint.objects.filter(
-            website_id=website_id
-        ).order_by('-discovered_at')
-        
-        result = []
-        for endpoint in endpoints:
-            result.append(EndpointDTO(
-                website_id=endpoint.website_id,
-                target_id=endpoint.target_id,
-                url=endpoint.url,
-                title=endpoint.title,
-                status_code=endpoint.status_code,
-                content_length=endpoint.content_length,
-                webserver=endpoint.webserver,
-                body_preview=endpoint.body_preview,
-                content_type=endpoint.content_type,
-                tech=endpoint.tech,
-                vhost=endpoint.vhost,
-                location=endpoint.location,
-                matched_gf_patterns=endpoint.matched_gf_patterns
-            ))
-        
-        return result
-    
-    def get_queryset_by_target(self, target_id: int):
-        return Endpoint.objects.filter(target_id=target_id).order_by('-discovered_at')
-
     def get_all(self):
         """获取所有端点（全局查询）"""
-        return Endpoint.objects.all().order_by('-discovered_at')
+        return Endpoint.objects.all().order_by('-created_at')
     
-    def get_by_target(self, target_id: int) -> List[EndpointDTO]:
+    def get_by_target(self, target_id: int):
         """
         获取目标下的所有端点
         
@@ -110,43 +90,9 @@ class DjangoEndpointRepository:
             target_id: 目标 ID
             
         Returns:
-            List[EndpointDTO]: 端点列表
+            QuerySet: 端点查询集
         """
-        endpoints = Endpoint.objects.filter(
-            target_id=target_id
-        ).order_by('-discovered_at')
-        
-        result = []
-        for endpoint in endpoints:
-            result.append(EndpointDTO(
-                website_id=endpoint.website_id,
-                target_id=endpoint.target_id,
-                url=endpoint.url,
-                title=endpoint.title,
-                status_code=endpoint.status_code,
-                content_length=endpoint.content_length,
-                webserver=endpoint.webserver,
-                body_preview=endpoint.body_preview,
-                content_type=endpoint.content_type,
-                tech=endpoint.tech,
-                vhost=endpoint.vhost,
-                location=endpoint.location,
-                matched_gf_patterns=endpoint.matched_gf_patterns
-            ))
-        
-        return result
-    
-    def count_by_website(self, website_id: int) -> int:
-        """
-        统计网站下的端点数量
-        
-        Args:
-            website_id: 网站 ID
-            
-        Returns:
-            int: 端点数量
-        """
-        return Endpoint.objects.filter(website_id=website_id).count()
+        return Endpoint.objects.filter(target_id=target_id).order_by('-created_at')
     
     def count_by_target(self, target_id: int) -> int:
         """
@@ -159,34 +105,88 @@ class DjangoEndpointRepository:
             int: 端点数量
         """
         return Endpoint.objects.filter(target_id=target_id).count()
-    
-    def soft_delete_by_ids(self, ids: List[int]) -> int:
+
+    def bulk_create_ignore_conflicts(self, items: List[EndpointDTO]) -> int:
         """
-        软删除端点（批量）
+        批量创建端点（存在即跳过）
+        
+        与 bulk_upsert 不同，此方法不会更新已存在的记录。
+        适用于快速扫描场景，只提供 URL，没有其他字段数据。
+        
+        注意：自动按模型唯一约束去重，保留最后一条记录。
         
         Args:
-            ids: 端点 ID 列表
+            items: 端点 DTO 列表
             
         Returns:
-            int: 更新的记录数
+            int: 处理的记录数
         """
-        from django.utils import timezone
-        return Endpoint.objects.filter(
-            id__in=ids
-        ).update(deleted_at=timezone.now())
-    
-    def hard_delete_by_ids(self, ids: List[int]) -> Tuple[int, Dict[str, int]]:
+        if not items:
+            return 0
+        
+        try:
+            # 自动按模型唯一约束去重
+            unique_items = deduplicate_for_bulk(items, Endpoint)
+            
+            # 直接从 DTO 字段构建 Model
+            endpoints = [
+                Endpoint(
+                    target_id=item.target_id,
+                    url=item.url,
+                    host=item.host or '',
+                    title=item.title or '',
+                    status_code=item.status_code,
+                    content_length=item.content_length,
+                    webserver=item.webserver or '',
+                    body_preview=item.body_preview or '',
+                    content_type=item.content_type or '',
+                    tech=item.tech if item.tech else [],
+                    vhost=item.vhost,
+                    location=item.location or '',
+                    matched_gf_patterns=item.matched_gf_patterns if item.matched_gf_patterns else []
+                )
+                for item in unique_items
+            ]
+            
+            with transaction.atomic():
+                Endpoint.objects.bulk_create(
+                    endpoints,
+                    ignore_conflicts=True,
+                    batch_size=1000
+                )
+            
+            logger.debug(f"批量创建端点成功（ignore_conflicts）: {len(unique_items)} 条")
+            return len(unique_items)
+                
+        except Exception as e:
+            logger.error(f"批量创建端点失败: {e}")
+            raise
+
+    def iter_raw_data_for_export(
+        self, 
+        target_id: int,
+        batch_size: int = 1000
+    ) -> Iterator[dict]:
         """
-        硬删除端点（批量）
+        流式获取原始数据用于 CSV 导出
         
         Args:
-            ids: 端点 ID 列表
-            
-        Returns:
-            Tuple[int, Dict[str, int]]: (删除总数, 详细信息)
-        """
-        deleted_count, details = Endpoint.all_objects.filter(
-            id__in=ids
-        ).delete()
+            target_id: 目标 ID
+            batch_size: 每批数据量
         
-        return deleted_count, details
+        Yields:
+            包含所有端点字段的字典
+        """
+        qs = (
+            Endpoint.objects
+            .filter(target_id=target_id)
+            .values(
+                'url', 'host', 'location', 'title', 'status_code',
+                'content_length', 'content_type', 'webserver', 'tech',
+                'body_preview', 'vhost', 'matched_gf_patterns', 'created_at'
+            )
+            .order_by('url')
+        )
+        
+        for row in qs.iterator(chunk_size=batch_size):
+            yield row

backend/apps/asset/repositories/asset/host_port_mapping_repository.py

@@ -1,32 +1,36 @@
 """HostPortMapping Repository - Django ORM 实现"""
 
 import logging
-from typing import List, Iterator
+from typing import List, Iterator, Dict, Optional
+
+from django.db.models import QuerySet, Min
 
 from apps.asset.models.asset_models import HostPortMapping
 from apps.asset.dtos.asset import HostPortMappingDTO
 from apps.common.decorators import auto_ensure_db_connection
+from apps.common.utils import deduplicate_for_bulk
 
 logger = logging.getLogger(__name__)
 
 
 @auto_ensure_db_connection
 class DjangoHostPortMappingRepository:
-    """HostPortMapping Repository - Django ORM 实现"""
+    """HostPortMapping Repository - Django ORM 实现
+    
+    职责：纯数据访问，不包含业务逻辑
+    """
 
     def bulk_create_ignore_conflicts(self, items: List[HostPortMappingDTO]) -> int:
         """
         批量创建主机端口关联（忽略冲突）
         
+        注意：自动按模型唯一约束去重，保留最后一条记录。
+        
         Args:
             items: 主机端口关联 DTO 列表
         
         Returns:
-            int: 实际创建的记录数（注意：ignore_conflicts 时可能为 0）
-        
-        Note:
-            - 基于唯一约束 (target + host + ip + port) 自动去重
-            - 忽略已存在的记录，不更新
+            int: 实际创建的记录数
         """
         try:
             logger.debug("准备批量创建主机端口关联 - 数量: %d", len(items))
@@ -34,18 +38,20 @@ class DjangoHostPortMappingRepository:
             if not items:
                 logger.debug("主机端口关联为空，跳过创建")
                 return 0
+            
+            # 自动按模型唯一约束去重
+            unique_items = deduplicate_for_bulk(items, HostPortMapping)
                 
-            # 构建记录对象
-            records = []
-            for item in items:
-                records.append(HostPortMapping(
+            records = [
+                HostPortMapping(
                     target_id=item.target_id,
                     host=item.host,
                     ip=item.ip,
                     port=item.port
-                ))
+                )
+                for item in unique_items
+            ]
             
-            # 批量创建（忽略冲突，基于唯一约束去重）
             created = HostPortMapping.objects.bulk_create(
                 records, 
                 ignore_conflicts=True
@@ -89,79 +95,47 @@ class DjangoHostPortMappingRepository:
         for ip in queryset:
             yield ip
 
-    def get_ip_aggregation_by_target(self, target_id: int, search: str = None):
-        from django.db.models import Min
+    def get_queryset_by_target(self, target_id: int) -> QuerySet:
+        """获取目标下的 QuerySet"""
+        return HostPortMapping.objects.filter(target_id=target_id)
 
-        qs = HostPortMapping.objects.filter(target_id=target_id)
-        if search:
-            qs = qs.filter(ip__icontains=search)
+    def get_all_queryset(self) -> QuerySet:
+        """获取所有记录的 QuerySet"""
+        return HostPortMapping.objects.all()
 
-        ip_aggregated = (
-            qs
-            .values('ip')
-            .annotate(
-                discovered_at=Min('discovered_at')
-            )
-            .order_by('-discovered_at')
+    def get_queryset_by_ip(self, ip: str, target_id: Optional[int] = None) -> QuerySet:
+        """获取指定 IP 的 QuerySet"""
+        qs = HostPortMapping.objects.filter(ip=ip)
+        if target_id:
+            qs = qs.filter(target_id=target_id)
+        return qs
+
+    def iter_raw_data_for_export(
+        self, 
+        target_id: int,
+        batch_size: int = 1000
+    ) -> Iterator[dict]:
+        """
+        流式获取原始数据用于 CSV 导出
+        
+        Args:
+            target_id: 目标 ID
+            batch_size: 每批数据量
+        
+        Yields:
+            {
+                'ip': '192.168.1.1',
+                'host': 'example.com',
+                'port': 80,
+                'created_at': datetime
+            }
+        """
+        qs = (
+            HostPortMapping.objects
+            .filter(target_id=target_id)
+            .values('ip', 'host', 'port', 'created_at')
+            .order_by('ip', 'host', 'port')
         )
-
-        results = []
-        for item in ip_aggregated:
-            ip = item['ip']
-            mappings = (
-                HostPortMapping.objects
-                .filter(target_id=target_id, ip=ip)
-                .values('host', 'port')
-                .distinct()
-            )
-
-            hosts = sorted({m['host'] for m in mappings})
-            ports = sorted({m['port'] for m in mappings})
-
-            results.append({
-                'ip': ip,
-                'hosts': hosts,
-                'ports': ports,
-                'discovered_at': item['discovered_at'],
-            })
-
-        return results
-
-    def get_all_ip_aggregation(self, search: str = None):
-        """获取所有 IP 聚合数据（全局查询）"""
-        from django.db.models import Min
-
-        qs = HostPortMapping.objects.all()
-        if search:
-            qs = qs.filter(ip__icontains=search)
-
-        ip_aggregated = (
-            qs
-            .values('ip')
-            .annotate(
-                discovered_at=Min('discovered_at')
-            )
-            .order_by('-discovered_at')
-        )
-
-        results = []
-        for item in ip_aggregated:
-            ip = item['ip']
-            mappings = (
-                HostPortMapping.objects
-                .filter(ip=ip)
-                .values('host', 'port')
-                .distinct()
-            )
-
-            hosts = sorted({m['host'] for m in mappings})
-            ports = sorted({m['port'] for m in mappings})
-
-            results.append({
-                'ip': ip,
-                'hosts': hosts,
-                'ports': ports,
-                'discovered_at': item['discovered_at'],
-            })
-
-        return results
+        
+        for row in qs.iterator(chunk_size=batch_size):
+            yield row

backend/apps/asset/repositories/asset/subdomain_repository.py

@@ -1,117 +1,72 @@
+"""Subdomain Repository - Django ORM 实现"""
+
 import logging
 from typing import List, Iterator
 
-from django.db import transaction, IntegrityError, OperationalError, DatabaseError
-from django.utils import timezone
-from typing import Tuple, Dict
+from django.db import transaction
 
 from apps.asset.models.asset_models import Subdomain
 from apps.asset.dtos import SubdomainDTO
 from apps.common.decorators import auto_ensure_db_connection
+from apps.common.utils import deduplicate_for_bulk
 
 logger = logging.getLogger(__name__)
 
 
 @auto_ensure_db_connection
 class DjangoSubdomainRepository:
-    """基于 Django ORM 的子域名仓储实现。"""
+    """基于 Django ORM 的子域名仓储实现"""
 
     def bulk_create_ignore_conflicts(self, items: List[SubdomainDTO]) -> None:
         """
         批量创建子域名，忽略冲突
         
+        注意：自动按模型唯一约束去重，保留最后一条记录。
+        
         Args:
             items: 子域名 DTO 列表
-            
-        Raises:
-            IntegrityError: 数据完整性错误（如唯一约束冲突）
-            OperationalError: 数据库操作错误（如连接失败）
-            DatabaseError: 其他数据库错误
         """
         if not items:
             return
 
         try:
+            # 自动按模型唯一约束去重
+            unique_items = deduplicate_for_bulk(items, Subdomain)
+            
             subdomain_objects = [
                 Subdomain(
                     name=item.name,
                     target_id=item.target_id,
                 )
-                for item in items
+                for item in unique_items
             ]
 
             with transaction.atomic():
-                # 使用 ignore_conflicts 策略：
-                # - 新子域名：INSERT 完整记录
-                # - 已存在子域名：忽略（不更新，因为没有探测字段数据）
-                # 注意：ignore_conflicts 无法返回实际创建的数量
-                Subdomain.objects.bulk_create(  # type: ignore[attr-defined]
+                Subdomain.objects.bulk_create(
                     subdomain_objects,
-                    ignore_conflicts=True,  # 忽略重复记录
+                    ignore_conflicts=True,
                 )
 
-            logger.debug(f"成功处理 {len(items)} 条子域名记录")
-
-        except IntegrityError as e:
-            logger.error(
-                f"批量插入子域名失败 - 数据完整性错误: {e}, "
-                f"记录数: {len(items)}, "
-                f"示例域名: {items[0].name if items else 'N/A'}"
-            )
-            raise
-
-        except OperationalError as e:
-            logger.error(
-                f"批量插入子域名失败 - 数据库操作错误: {e}, "
-                f"记录数: {len(items)}"
-            )
-            raise
-
-        except DatabaseError as e:
-            logger.error(
-                f"批量插入子域名失败 - 数据库错误: {e}, "
-                f"记录数: {len(items)}"
-            )
-            raise
+            logger.debug(f"成功处理 {len(unique_items)} 条子域名记录")
 
         except Exception as e:
-            logger.error(
-                f"批量插入子域名失败 - 未知错误: {e}, "
-                f"记录数: {len(items)}, "
-                f"错误类型: {type(e).__name__}",
-                exc_info=True
-            )
+            logger.error(f"批量插入子域名失败: {e}")
             raise
     
-    def get_or_create(self, name: str, target_id: int) -> Tuple[Subdomain, bool]:
-        """
-        获取或创建子域名
-        
-        Args:
-            name: 子域名名称
-            target_id: 目标 ID
-        
-        Returns:
-            (Subdomain对象, 是否新创建)
-        """
-        return Subdomain.objects.get_or_create(
-            name=name,
-            target_id=target_id,
-        )
+    def get_all(self):
+        """获取所有子域名"""
+        return Subdomain.objects.all().order_by('-created_at')
+
+    def get_by_target(self, target_id: int):
+        """获取目标下的所有子域名"""
+        return Subdomain.objects.filter(target_id=target_id).order_by('-created_at')
+    
+    def count_by_target(self, target_id: int) -> int:
+        """统计目标下的域名数量"""
+        return Subdomain.objects.filter(target_id=target_id).count()
     
     def get_domains_for_export(self, target_id: int, batch_size: int = 1000) -> Iterator[str]:
-        """
-        流式导出域名（用于生成扫描工具输入文件）
-        
-        使用 iterator() 进行流式查询，避免一次性加载所有数据到内存
-        
-        Args:
-            target_id: 目标 ID
-            batch_size: 每次从数据库读取的行数
-            
-        Yields:
-            str: 域名
-        """
+        """流式导出域名"""
         queryset = Subdomain.objects.filter(
             target_id=target_id
         ).only('name').iterator(chunk_size=batch_size)
@@ -119,138 +74,36 @@ class DjangoSubdomainRepository:
         for subdomain in queryset:
             yield subdomain.name
     
-    def get_by_target(self, target_id: int):
-        return Subdomain.objects.filter(target_id=target_id).order_by('-discovered_at')
-    
-    def count_by_target(self, target_id: int) -> int:
-        """
-        统计目标下的域名数量
-        
-        Args:
-            target_id: 目标 ID
-            
-        Returns:
-            int: 域名数量
-        """
-        return Subdomain.objects.filter(target_id=target_id).count()
-    
     def get_by_names_and_target_id(self, names: set, target_id: int) -> dict:
-        """
-        根据域名列表和目标ID批量查询 Subdomain
-        
-        Args:
-            names: 域名集合
-            target_id: 目标 ID
-            
-        Returns:
-            dict: {domain_name: Subdomain对象}
-        """
+        """根据域名列表和目标ID批量查询 Subdomain"""
         subdomains = Subdomain.objects.filter(
             name__in=names,
             target_id=target_id
         ).only('id', 'name')
         
         return {sd.name: sd for sd in subdomains}
-    
-    def get_all(self):
+
+    def iter_raw_data_for_export(
+        self, 
+        target_id: int,
+        batch_size: int = 1000
+    ) -> Iterator[dict]:
         """
-        获取所有子域名
-        
-        Returns:
-            QuerySet: 子域名查询集
-        """
-        return Subdomain.objects.all()
-    
-    def soft_delete_by_ids(self, subdomain_ids: List[int]) -> int:
-        """
-        根据 ID 列表批量软删除子域名
+        流式获取原始数据用于 CSV 导出
         
         Args:
-            subdomain_ids: 子域名 ID 列表
+            target_id: 目标 ID
+            batch_size: 每批数据量
         
-        Returns:
-            软删除的记录数
-        
-        Note:
-            - 使用软删除：只标记为已删除，不真正删除数据库记录
-            - 保留所有关联数据，可恢复
+        Yields:
+            {'name': 'sub.example.com', 'created_at': datetime}
         """
-        try:
-            updated_count = (
-                Subdomain.objects
-                .filter(id__in=subdomain_ids)
-                .update(deleted_at=timezone.now())
-            )
-            logger.debug(
-                "批量软删除子域名成功 - Count: %s, 更新记录: %s",
-                len(subdomain_ids),
-                updated_count
-            )
-            return updated_count
-        except Exception as e:
-            logger.error(
-                "批量软删除子域名失败 - IDs: %s, 错误: %s",
-                subdomain_ids,
-                e
-            )
-            raise
-    
-    def hard_delete_by_ids(self, subdomain_ids: List[int]) -> Tuple[int, Dict[str, int]]:
-        """
-        根据 ID 列表硬删除子域名（使用数据库级 CASCADE）
+        qs = (
+            Subdomain.objects
+            .filter(target_id=target_id)
+            .values('name', 'created_at')
+            .order_by('name')
+        )
         
-        Args:
-            subdomain_ids: 子域名 ID 列表
-        
-        Returns:
-            (删除的记录数, 删除详情字典)
-        
-        Strategy:
-            使用数据库级 CASCADE 删除，性能最优
-        
-        Note:
-            - 硬删除：从数据库中永久删除
-            - 数据库自动处理所有外键级联删除
-            - 不触发 Django 信号（pre_delete/post_delete）
-        """
-        try:
-            batch_size = 1000  # 每批处理1000个子域名
-            total_deleted = 0
-            
-            logger.debug(f"开始批量删除 {len(subdomain_ids)} 个子域名（数据库 CASCADE）...")
-            
-            # 分批处理子域名ID，避免单次删除过多
-            for i in range(0, len(subdomain_ids), batch_size):
-                batch_ids = subdomain_ids[i:i + batch_size]
-                
-                # 直接删除子域名，数据库自动级联删除所有关联数据
-                count, _ = Subdomain.all_objects.filter(id__in=batch_ids).delete()
-                total_deleted += count
-                
-                logger.debug(f"批次删除完成: {len(batch_ids)} 个子域名，删除 {count} 条记录")
-            
-            # 由于使用数据库 CASCADE，无法获取详细统计
-            deleted_details = {
-                'subdomains': len(subdomain_ids),
-                'total': total_deleted,
-                'note': 'Database CASCADE - detailed stats unavailable'
-            }
-            
-            logger.debug(
-                "批量硬删除成功（CASCADE）- 子域名数: %s, 总删除记录: %s",
-                len(subdomain_ids),
-                total_deleted
-            )
-            
-            return total_deleted, deleted_details
-        
-        except Exception as e:
-            logger.error(
-                "批量硬删除失败（CASCADE）- 子域名数: %s, 错误: %s",
-                len(subdomain_ids),
-                str(e),
-                exc_info=True
-            )
-            raise
-
-
+        for row in qs.iterator(chunk_size=batch_size):
+            yield row

backend/apps/asset/repositories/asset/website_repository.py

@@ -3,110 +3,87 @@ Django ORM 实现的 WebSite Repository
 """
 
 import logging
-from typing import List, Generator, Tuple, Dict, Optional
-from django.db import transaction, IntegrityError, OperationalError, DatabaseError
-from django.utils import timezone
+from typing import List, Generator, Optional, Iterator
+from django.db import transaction
 
 from apps.asset.models.asset_models import WebSite
 from apps.asset.dtos import WebSiteDTO
 from apps.common.decorators import auto_ensure_db_connection
+from apps.common.utils import deduplicate_for_bulk
 
 logger = logging.getLogger(__name__)
 
 
-
 @auto_ensure_db_connection
 class DjangoWebSiteRepository:
     """Django ORM 实现的 WebSite Repository"""
 
-    def bulk_create_ignore_conflicts(self, items: List[WebSiteDTO]) -> None:
+    def bulk_upsert(self, items: List[WebSiteDTO]) -> int:
         """
-        批量创建 WebSite，忽略冲突
+        批量创建或更新 WebSite（upsert）
+        
+        存在则更新所有字段，不存在则创建。
+        使用 Django 原生 update_conflicts。
+        
+        注意：自动按模型唯一约束去重，保留最后一条记录。
         
         Args:
             items: WebSite DTO 列表
             
-        Raises:
-            IntegrityError: 数据完整性错误
-            OperationalError: 数据库操作错误
-            DatabaseError: 数据库错误
+        Returns:
+            int: 处理的记录数
         """
         if not items:
-            return
-
+            return 0
+        
         try:
-            # 转换为 Django 模型对象
-            website_objects = [
+            # 自动按模型唯一约束去重
+            unique_items = deduplicate_for_bulk(items, WebSite)
+            
+            # 直接从 DTO 字段构建 Model
+            websites = [
                 WebSite(
                     target_id=item.target_id,
                     url=item.url,
-                    host=item.host,
-                    location=item.location,
-                    title=item.title,
-                    webserver=item.webserver,
-                    body_preview=item.body_preview,
-                    content_type=item.content_type,
-                    tech=item.tech,
+                    host=item.host or '',
+                    location=item.location or '',
+                    title=item.title or '',
+                    webserver=item.webserver or '',
+                    body_preview=item.body_preview or '',
+                    content_type=item.content_type or '',
+                    tech=item.tech if item.tech else [],
                     status_code=item.status_code,
                     content_length=item.content_length,
                     vhost=item.vhost
                 )
-                for item in items
+                for item in unique_items
             ]
-
+            
             with transaction.atomic():
-                # 批量插入或更新
-                # 如果URL和目标已存在，忽略冲突
                 WebSite.objects.bulk_create(
-                    website_objects,
-                    ignore_conflicts=True
+                    websites,
+                    update_conflicts=True,
+                    unique_fields=['url', 'target'],
+                    update_fields=[
+                        'host', 'location', 'title', 'webserver',
+                        'body_preview', 'content_type', 'tech',
+                        'status_code', 'content_length', 'vhost'
+                    ],
+                    batch_size=1000
                 )
-
-            logger.debug(f"成功处理 {len(items)} 条 WebSite 记录")
-
-        except IntegrityError as e:
-            logger.error(
-                f"批量插入 WebSite 失败 - 数据完整性错误: {e}, "
-                f"记录数: {len(items)}"
-            )
-            raise
-
-        except OperationalError as e:
-            logger.error(
-                f"批量插入 WebSite 失败 - 数据库操作错误: {e}, "
-                f"记录数: {len(items)}"
-            )
-            raise
-
-        except DatabaseError as e:
-            logger.error(
-                f"批量插入 WebSite 失败 - 数据库错误: {e}, "
-                f"记录数: {len(items)}"
-            )
-            raise
-
+            
+            logger.debug(f"批量 upsert WebSite 成功: {len(unique_items)} 条")
+            return len(unique_items)
+                
         except Exception as e:
-            logger.error(
-                f"批量插入 WebSite 失败 - 未知错误: {e}, "
-                f"记录数: {len(items)}, "
-                f"错误类型: {type(e).__name__}",
-                exc_info=True
-            )
+            logger.error(f"批量 upsert WebSite 失败: {e}")
             raise
 
     def get_urls_for_export(self, target_id: int, batch_size: int = 1000) -> Generator[str, None, None]:
         """
         流式导出目标下的所有站点 URL
-        
-        Args:
-            target_id: 目标 ID  
-            batch_size: 批次大小
-            
-        Yields:
-            str: 站点 URL
         """
         try:
-            # 查询目标下的站点，只选择 URL 字段，避免不必要的数据传输
             queryset = WebSite.objects.filter(
                 target_id=target_id
             ).values_list('url', flat=True).iterator(chunk_size=batch_size)
@@ -117,144 +94,93 @@ class DjangoWebSiteRepository:
             logger.error(f"流式导出站点 URL 失败 - Target ID: {target_id}, 错误: {e}")
             raise
 
+    def get_all(self):
+        """获取所有网站"""
+        return WebSite.objects.all().order_by('-created_at')
+
     def get_by_target(self, target_id: int):
-        return WebSite.objects.filter(target_id=target_id).order_by('-discovered_at')
+        """获取目标下的所有网站"""
+        return WebSite.objects.filter(target_id=target_id).order_by('-created_at')
 
     def count_by_target(self, target_id: int) -> int:
-        """
-        统计目标下的站点总数
-        
-        Args:
-            target_id: 目标 ID
-            
-        Returns:
-            int: 站点总数
-        """
-        try:
-            count = WebSite.objects.filter(target_id=target_id).count()
-            logger.debug(f"Target {target_id} 的站点总数: {count}")
-            return count
-            
-        except Exception as e:
-            logger.error(f"统计站点数量失败 - Target ID: {target_id}, 错误: {e}")
-            raise
-
-    def count_by_scan(self, scan_id: int) -> int:
-        """
-        统计扫描下的站点总数
-        """
-        try:
-            count = WebSite.objects.filter(scan_id=scan_id).count()
-            logger.debug(f"Scan {scan_id} 的站点总数: {count}")
-            return count
-        except Exception as e:
-            logger.error(f"统计站点数量失败 - Scan ID: {scan_id}, 错误: {e}")
-            raise
+        """统计目标下的站点总数"""
+        return WebSite.objects.filter(target_id=target_id).count()
 
     def get_by_url(self, url: str, target_id: int) -> Optional[int]:
+        """根据 URL 和 target_id 查找站点 ID"""
+        website = WebSite.objects.filter(url=url, target_id=target_id).first()
+        return website.id if website else None
+
+    def bulk_create_ignore_conflicts(self, items: List[WebSiteDTO]) -> int:
         """
-        根据 URL 和 target_id 查找站点 ID
+        批量创建 WebSite（存在即跳过）
+        
+        注意：自动按模型唯一约束去重，保留最后一条记录。
+        """
+        if not items:
+            return 0
+        
+        try:
+            # 自动按模型唯一约束去重
+            unique_items = deduplicate_for_bulk(items, WebSite)
+            
+            websites = [
+                WebSite(
+                    target_id=item.target_id,
+                    url=item.url,
+                    host=item.host or '',
+                    location=item.location or '',
+                    title=item.title or '',
+                    webserver=item.webserver or '',
+                    body_preview=item.body_preview or '',
+                    content_type=item.content_type or '',
+                    tech=item.tech if item.tech else [],
+                    status_code=item.status_code,
+                    content_length=item.content_length,
+                    vhost=item.vhost
+                )
+                for item in unique_items
+            ]
+            
+            with transaction.atomic():
+                WebSite.objects.bulk_create(
+                    websites,
+                    ignore_conflicts=True,
+                    batch_size=1000
+                )
+            
+            logger.debug(f"批量创建 WebSite 成功（ignore_conflicts）: {len(unique_items)} 条")
+            return len(unique_items)
+                
+        except Exception as e:
+            logger.error(f"批量创建 WebSite 失败: {e}")
+            raise
+
+    def iter_raw_data_for_export(
+        self, 
+        target_id: int,
+        batch_size: int = 1000
+    ) -> Iterator[dict]:
+        """
+        流式获取原始数据用于 CSV 导出
         
         Args:
-            url: 站点 URL
             target_id: 目标 ID
-            
-        Returns:
-            Optional[int]: 站点 ID，如果不存在返回 None
-            
-        Raises:
-            ValueError: 发现多个站点时
-        """
-        try:
-            website = WebSite.objects.filter(url=url, target_id=target_id).first()
-            if website:
-                return website.id
-            return None
-            
-        except Exception as e:
-            logger.error(f"查询站点失败 - URL: {url}, Target ID: {target_id}, 错误: {e}")
-            raise
-    
-    def get_all(self):
-        """
-        获取所有网站
+            batch_size: 每批数据量
         
-        Returns:
-            QuerySet: 网站查询集
+        Yields:
+            包含所有网站字段的字典
         """
-        return WebSite.objects.all()
-    
-    def soft_delete_by_ids(self, website_ids: List[int]) -> int:
-        """
-        根据 ID 列表批量软删除WebSite
-        
-        Args:
-            website_ids: WebSite ID 列表
-        
-        Returns:
-            软删除的记录数
-        """
-        try:
-            updated_count = (
-                WebSite.objects
-                .filter(id__in=website_ids)
-                .update(deleted_at=timezone.now())
+        qs = (
+            WebSite.objects
+            .filter(target_id=target_id)
+            .values(
+                'url', 'host', 'location', 'title', 'status_code',
+                'content_length', 'content_type', 'webserver', 'tech',
+                'body_preview', 'vhost', 'created_at'
             )
-            logger.debug(
-                "批量软删除WebSite成功 - Count: %s, 更新记录: %s",
-                len(website_ids),
-                updated_count
-            )
-            return updated_count
-        except Exception as e:
-            logger.error(
-                "批量软删除WebSite失败 - IDs: %s, 错误: %s",
-                website_ids,
-                e
-            )
-            raise
-    
-    def hard_delete_by_ids(self, website_ids: List[int]) -> Tuple[int, Dict[str, int]]:
-        """
-        根据 ID 列表硬删除WebSite（使用数据库级 CASCADE）
+            .order_by('url')
+        )
         
-        Args:
-            website_ids: WebSite ID 列表
-        
-        Returns:
-            (删除的记录数, 删除详情字典)
-        """
-        try:
-            batch_size = 1000
-            total_deleted = 0
-            
-            logger.debug(f"开始批量删除 {len(website_ids)} 个WebSite（数据库 CASCADE）...")
-            
-            for i in range(0, len(website_ids), batch_size):
-                batch_ids = website_ids[i:i + batch_size]
-                count, _ = WebSite.all_objects.filter(id__in=batch_ids).delete()
-                total_deleted += count
-                logger.debug(f"批次删除完成: {len(batch_ids)} 个WebSite，删除 {count} 条记录")
-            
-            deleted_details = {
-                'websites': len(website_ids),
-                'total': total_deleted,
-                'note': 'Database CASCADE - detailed stats unavailable'
-            }
-            
-            logger.debug(
-                "批量硬删除成功（CASCADE）- WebSite数: %s, 总删除记录: %s",
-                len(website_ids),
-                total_deleted
-            )
-            
-            return total_deleted, deleted_details
-        
-        except Exception as e:
-            logger.error(
-                "批量硬删除失败（CASCADE）- WebSite数: %s, 错误: %s",
-                len(website_ids),
-                str(e),
-                exc_info=True
-            )
-            raise
+        for row in qs.iterator(chunk_size=batch_size):
+            yield row

backend/apps/asset/repositories/snapshot/directory_snapshot_repository.py

@@ -1,12 +1,13 @@
 """Directory Snapshot Repository - 目录快照数据访问层"""
 
 import logging
-from typing import List
+from typing import List, Iterator
 from django.db import transaction
 
 from apps.asset.models import DirectorySnapshot
 from apps.asset.dtos.snapshot import DirectorySnapshotDTO
 from apps.common.decorators import auto_ensure_db_connection
+from apps.common.utils import deduplicate_for_bulk
 
 logger = logging.getLogger(__name__)
 
@@ -25,6 +26,8 @@ class DjangoDirectorySnapshotRepository:
         
         使用 ignore_conflicts 策略，如果快照已存在（相同 scan + url）则跳过
         
+        注意：会自动按 (scan_id, url) 去重，保留最后一条记录。
+        
         Args:
             items: 目录快照 DTO 列表
         
@@ -37,6 +40,9 @@ class DjangoDirectorySnapshotRepository:
             return
         
         try:
+            # 根据模型唯一约束自动去重
+            unique_items = deduplicate_for_bulk(items, DirectorySnapshot)
+            
             # 转换为 Django 模型对象
             snapshot_objects = [
                 DirectorySnapshot(
@@ -49,7 +55,7 @@ class DjangoDirectorySnapshotRepository:
                     content_type=item.content_type,
                     duration=item.duration
                 )
-                for item in items
+                for item in unique_items
             ]
             
             with transaction.atomic():
@@ -60,7 +66,7 @@ class DjangoDirectorySnapshotRepository:
                     ignore_conflicts=True
                 )
             
-            logger.debug("成功保存 %d 条目录快照记录", len(items))
+            logger.debug("成功保存 %d 条目录快照记录", len(unique_items))
             
         except Exception as e:
             logger.error(
@@ -72,7 +78,35 @@ class DjangoDirectorySnapshotRepository:
             raise
     
     def get_by_scan(self, scan_id: int):
-        return DirectorySnapshot.objects.filter(scan_id=scan_id).order_by('-discovered_at')
+        return DirectorySnapshot.objects.filter(scan_id=scan_id).order_by('-created_at')
 
     def get_all(self):
-        return DirectorySnapshot.objects.all().order_by('-discovered_at')
+        return DirectorySnapshot.objects.all().order_by('-created_at')
+
+    def iter_raw_data_for_export(
+        self, 
+        scan_id: int,
+        batch_size: int = 1000
+    ) -> Iterator[dict]:
+        """
+        流式获取原始数据用于 CSV 导出
+        
+        Args:
+            scan_id: 扫描 ID
+            batch_size: 每批数据量
+        
+        Yields:
+            包含所有目录字段的字典
+        """
+        qs = (
+            DirectorySnapshot.objects
+            .filter(scan_id=scan_id)
+            .values(
+                'url', 'status', 'content_length', 'words',
+                'lines', 'content_type', 'duration', 'created_at'
+            )
+            .order_by('url')
+        )
+        
+        for row in qs.iterator(chunk_size=batch_size):
+            yield row

backend/apps/asset/repositories/snapshot/endpoint_snapshot_repository.py

@@ -1,11 +1,12 @@
 """EndpointSnapshot Repository - Django ORM 实现"""
 
 import logging
-from typing import List
+from typing import List, Iterator
 
 from apps.asset.models.snapshot_models import EndpointSnapshot
 from apps.asset.dtos.snapshot import EndpointSnapshotDTO
 from apps.common.decorators import auto_ensure_db_connection
+from apps.common.utils import deduplicate_for_bulk
 
 logger = logging.getLogger(__name__)
 
@@ -18,6 +19,8 @@ class DjangoEndpointSnapshotRepository:
         """
         保存端点快照
         
+        注意：会自动按 (scan_id, url) 去重，保留最后一条记录。
+        
         Args:
             items: 端点快照 DTO 列表
         
@@ -31,10 +34,13 @@ class DjangoEndpointSnapshotRepository:
             if not items:
                 logger.debug("端点快照为空，跳过保存")
                 return
+            
+            # 根据模型唯一约束自动去重
+            unique_items = deduplicate_for_bulk(items, EndpointSnapshot)
                 
             # 构建快照对象
             snapshots = []
-            for item in items:
+            for item in unique_items:
                 snapshots.append(EndpointSnapshot(
                     scan_id=item.scan_id,
                     url=item.url,
@@ -68,7 +74,36 @@ class DjangoEndpointSnapshotRepository:
             raise
     
     def get_by_scan(self, scan_id: int):
-        return EndpointSnapshot.objects.filter(scan_id=scan_id).order_by('-discovered_at')
+        return EndpointSnapshot.objects.filter(scan_id=scan_id).order_by('-created_at')
 
     def get_all(self):
-        return EndpointSnapshot.objects.all().order_by('-discovered_at')
+        return EndpointSnapshot.objects.all().order_by('-created_at')
+
+    def iter_raw_data_for_export(
+        self, 
+        scan_id: int,
+        batch_size: int = 1000
+    ) -> Iterator[dict]:
+        """
+        流式获取原始数据用于 CSV 导出
+        
+        Args:
+            scan_id: 扫描 ID
+            batch_size: 每批数据量
+        
+        Yields:
+            包含所有端点字段的字典
+        """
+        qs = (
+            EndpointSnapshot.objects
+            .filter(scan_id=scan_id)
+            .values(
+                'url', 'host', 'location', 'title', 'status_code',
+                'content_length', 'content_type', 'webserver', 'tech',
+                'body_preview', 'vhost', 'matched_gf_patterns', 'created_at'
+            )
+            .order_by('url')
+        )
+        
+        for row in qs.iterator(chunk_size=batch_size):
+            yield row

backend/apps/asset/repositories/snapshot/host_port_mapping_snapshot_repository.py

@@ -6,6 +6,7 @@ from typing import List, Iterator
 from apps.asset.models.snapshot_models import HostPortMappingSnapshot
 from apps.asset.dtos.snapshot import HostPortMappingSnapshotDTO
 from apps.common.decorators import auto_ensure_db_connection
+from apps.common.utils import deduplicate_for_bulk
 
 logger = logging.getLogger(__name__)
 
@@ -18,6 +19,8 @@ class DjangoHostPortMappingSnapshotRepository:
         """
         保存主机端口关联快照
         
+        注意：会自动按 (scan_id, host, ip, port) 去重，保留最后一条记录。
+        
         Args:
             items: 主机端口关联快照 DTO 列表
         
@@ -31,10 +34,13 @@ class DjangoHostPortMappingSnapshotRepository:
             if not items:
                 logger.debug("主机端口关联快照为空，跳过保存")
                 return
+            
+            # 根据模型唯一约束自动去重
+            unique_items = deduplicate_for_bulk(items, HostPortMappingSnapshot)
                 
             # 构建快照对象
             snapshots = []
-            for item in items:
+            for item in unique_items:
                 snapshots.append(HostPortMappingSnapshot(
                     scan_id=item.scan_id,
                     host=item.host,
@@ -59,20 +65,28 @@ class DjangoHostPortMappingSnapshotRepository:
             )
             raise
     
-    def get_ip_aggregation_by_scan(self, scan_id: int, search: str = None):
+    def get_ip_aggregation_by_scan(self, scan_id: int, filter_query: str = None):
         from django.db.models import Min
+        from apps.common.utils.filter_utils import apply_filters
 
         qs = HostPortMappingSnapshot.objects.filter(scan_id=scan_id)
-        if search:
-            qs = qs.filter(ip__icontains=search)
+        
+        # 应用智能过滤
+        if filter_query:
+            field_mapping = {
+                'ip': 'ip',
+                'port': 'port',
+                'host': 'host',
+            }
+            qs = apply_filters(qs, filter_query, field_mapping)
 
         ip_aggregated = (
             qs
             .values('ip')
             .annotate(
-                discovered_at=Min('discovered_at')
+                created_at=Min('created_at')
             )
-            .order_by('-discovered_at')
+            .order_by('-created_at')
         )
 
         results = []
@@ -92,24 +106,32 @@ class DjangoHostPortMappingSnapshotRepository:
                 'ip': ip,
                 'hosts': hosts,
                 'ports': ports,
-                'discovered_at': item['discovered_at'],
+                'created_at': item['created_at'],
             })
 
         return results
 
-    def get_all_ip_aggregation(self, search: str = None):
+    def get_all_ip_aggregation(self, filter_query: str = None):
         """获取所有 IP 聚合数据"""
         from django.db.models import Min
+        from apps.common.utils.filter_utils import apply_filters
 
         qs = HostPortMappingSnapshot.objects.all()
-        if search:
-            qs = qs.filter(ip__icontains=search)
+        
+        # 应用智能过滤
+        if filter_query:
+            field_mapping = {
+                'ip': 'ip',
+                'port': 'port',
+                'host': 'host',
+            }
+            qs = apply_filters(qs, filter_query, field_mapping)
 
         ip_aggregated = (
             qs
             .values('ip')
-            .annotate(discovered_at=Min('discovered_at'))
-            .order_by('-discovered_at')
+            .annotate(created_at=Min('created_at'))
+            .order_by('-created_at')
         )
 
         results = []
@@ -127,7 +149,7 @@ class DjangoHostPortMappingSnapshotRepository:
                 'ip': ip,
                 'hosts': hosts,
                 'ports': ports,
-                'discovered_at': item['discovered_at'],
+                'created_at': item['created_at'],
             })
         return results
 
@@ -143,3 +165,33 @@ class DjangoHostPortMappingSnapshotRepository:
         )
         for ip in queryset:
             yield ip
+
+    def iter_raw_data_for_export(
+        self, 
+        scan_id: int,
+        batch_size: int = 1000
+    ) -> Iterator[dict]:
+        """
+        流式获取原始数据用于 CSV 导出
+        
+        Args:
+            scan_id: 扫描 ID
+            batch_size: 每批数据量
+        
+        Yields:
+            {
+                'ip': '192.168.1.1',
+                'host': 'example.com',
+                'port': 80,
+                'created_at': datetime
+            }
+        """
+        qs = (
+            HostPortMappingSnapshot.objects
+            .filter(scan_id=scan_id)
+            .values('ip', 'host', 'port', 'created_at')
+            .order_by('ip', 'host', 'port')
+        )
+        
+        for row in qs.iterator(chunk_size=batch_size):
+            yield row

backend/apps/asset/repositories/snapshot/subdomain_snapshot_repository.py

@@ -1,11 +1,12 @@
 """Django ORM 实现的 SubdomainSnapshot Repository"""
 
 import logging
-from typing import List
+from typing import List, Iterator
 
 from apps.asset.models.snapshot_models import SubdomainSnapshot
 from apps.asset.dtos import SubdomainSnapshotDTO
 from apps.common.decorators import auto_ensure_db_connection
+from apps.common.utils import deduplicate_for_bulk
 
 logger = logging.getLogger(__name__)
 
@@ -18,6 +19,8 @@ class DjangoSubdomainSnapshotRepository:
         """
         保存子域名快照
         
+        注意：会自动按 (scan_id, name) 去重，保留最后一条记录。
+        
         Args:
             items: 子域名快照 DTO 列表
         
@@ -31,10 +34,13 @@ class DjangoSubdomainSnapshotRepository:
             if not items:
                 logger.debug("子域名快照为空，跳过保存")
                 return
+            
+            # 根据模型唯一约束自动去重
+            unique_items = deduplicate_for_bulk(items, SubdomainSnapshot)
                 
             # 构建快照对象
             snapshots = []
-            for item in items:
+            for item in unique_items:
                 snapshots.append(SubdomainSnapshot(
                     scan_id=item.scan_id,
                     name=item.name,
@@ -55,7 +61,32 @@ class DjangoSubdomainSnapshotRepository:
             raise
     
     def get_by_scan(self, scan_id: int):
-        return SubdomainSnapshot.objects.filter(scan_id=scan_id).order_by('-discovered_at')
+        return SubdomainSnapshot.objects.filter(scan_id=scan_id).order_by('-created_at')
 
     def get_all(self):
-        return SubdomainSnapshot.objects.all().order_by('-discovered_at')
+        return SubdomainSnapshot.objects.all().order_by('-created_at')
+
+    def iter_raw_data_for_export(
+        self, 
+        scan_id: int,
+        batch_size: int = 1000
+    ) -> Iterator[dict]:
+        """
+        流式获取原始数据用于 CSV 导出
+        
+        Args:
+            scan_id: 扫描 ID
+            batch_size: 每批数据量
+        
+        Yields:
+            {'name': 'sub.example.com', 'created_at': datetime}
+        """
+        qs = (
+            SubdomainSnapshot.objects
+            .filter(scan_id=scan_id)
+            .values('name', 'created_at')
+            .order_by('name')
+        )
+        
+        for row in qs.iterator(chunk_size=batch_size):
+            yield row

backend/apps/asset/repositories/snapshot/vulnerability_snapshot_repository.py

@@ -8,6 +8,7 @@ from django.db import transaction
 from apps.asset.models import VulnerabilitySnapshot
 from apps.asset.dtos.snapshot import VulnerabilitySnapshotDTO
 from apps.common.decorators import auto_ensure_db_connection
+from apps.common.utils import deduplicate_for_bulk
 
 logger = logging.getLogger(__name__)
 
@@ -21,12 +22,17 @@ class DjangoVulnerabilitySnapshotRepository:
 
         使用 ``ignore_conflicts`` 策略，如果快照已存在则跳过。
         具体唯一约束由数据库模型控制。
+        
+        注意：会自动按唯一约束字段去重，保留最后一条记录。
         """
         if not items:
             logger.warning("漏洞快照列表为空，跳过保存")
             return
 
         try:
+            # 根据模型唯一约束自动去重
+            unique_items = deduplicate_for_bulk(items, VulnerabilitySnapshot)
+            
             snapshot_objects = [
                 VulnerabilitySnapshot(
                     scan_id=item.scan_id,
@@ -38,7 +44,7 @@ class DjangoVulnerabilitySnapshotRepository:
                     description=item.description,
                     raw_output=item.raw_output,
                 )
-                for item in items
+                for item in unique_items
             ]
 
             with transaction.atomic():
@@ -47,7 +53,7 @@ class DjangoVulnerabilitySnapshotRepository:
                     ignore_conflicts=True,
                 )
 
-            logger.debug("成功保存 %d 条漏洞快照记录", len(items))
+            logger.debug("成功保存 %d 条漏洞快照记录", len(unique_items))
 
         except Exception as e:
             logger.error(
@@ -60,7 +66,7 @@ class DjangoVulnerabilitySnapshotRepository:
 
     def get_by_scan(self, scan_id: int):
         """按扫描任务获取漏洞快照 QuerySet。"""
-        return VulnerabilitySnapshot.objects.filter(scan_id=scan_id).order_by("-discovered_at")
+        return VulnerabilitySnapshot.objects.filter(scan_id=scan_id).order_by("-created_at")
 
     def get_all(self):
-        return VulnerabilitySnapshot.objects.all().order_by('-discovered_at')
+        return VulnerabilitySnapshot.objects.all().order_by('-created_at')

backend/apps/asset/repositories/snapshot/website_snapshot_repository.py

@@ -1,11 +1,12 @@
 """WebsiteSnapshot Repository - Django ORM 实现"""
 
 import logging
-from typing import List
+from typing import List, Iterator
 
 from apps.asset.models.snapshot_models import WebsiteSnapshot
 from apps.asset.dtos.snapshot import WebsiteSnapshotDTO
 from apps.common.decorators import auto_ensure_db_connection
+from apps.common.utils import deduplicate_for_bulk
 
 logger = logging.getLogger(__name__)
 
@@ -18,6 +19,8 @@ class DjangoWebsiteSnapshotRepository:
         """
         保存网站快照
         
+        注意：会自动按 (scan_id, url) 去重，保留最后一条记录。
+        
         Args:
             items: 网站快照 DTO 列表
         
@@ -31,10 +34,13 @@ class DjangoWebsiteSnapshotRepository:
             if not items:
                 logger.debug("网站快照为空，跳过保存")
                 return
+            
+            # 根据模型唯一约束自动去重
+            unique_items = deduplicate_for_bulk(items, WebsiteSnapshot)
                 
             # 构建快照对象
             snapshots = []
-            for item in items:
+            for item in unique_items:
                 snapshots.append(WebsiteSnapshot(
                     scan_id=item.scan_id,
                     url=item.url,
@@ -68,7 +74,50 @@ class DjangoWebsiteSnapshotRepository:
             raise
     
     def get_by_scan(self, scan_id: int):
-        return WebsiteSnapshot.objects.filter(scan_id=scan_id).order_by('-discovered_at')
+        return WebsiteSnapshot.objects.filter(scan_id=scan_id).order_by('-created_at')
 
     def get_all(self):
-        return WebsiteSnapshot.objects.all().order_by('-discovered_at')
+        return WebsiteSnapshot.objects.all().order_by('-created_at')
+
+    def iter_raw_data_for_export(
+        self, 
+        scan_id: int,
+        batch_size: int = 1000
+    ) -> Iterator[dict]:
+        """
+        流式获取原始数据用于 CSV 导出
+        
+        Args:
+            scan_id: 扫描 ID
+            batch_size: 每批数据量
+        
+        Yields:
+            包含所有网站字段的字典
+        """
+        qs = (
+            WebsiteSnapshot.objects
+            .filter(scan_id=scan_id)
+            .values(
+                'url', 'host', 'location', 'title', 'status',
+                'content_length', 'content_type', 'web_server', 'tech',
+                'body_preview', 'vhost', 'created_at'
+            )
+            .order_by('url')
+        )
+        
+        for row in qs.iterator(chunk_size=batch_size):
+            # 重命名字段以匹配 CSV 表头
+            yield {
+                'url': row['url'],
+                'host': row['host'],
+                'location': row['location'],
+                'title': row['title'],
+                'status_code': row['status'],
+                'content_length': row['content_length'],
+                'content_type': row['content_type'],
+                'webserver': row['web_server'],
+                'tech': row['tech'],
+                'body_preview': row['body_preview'],
+                'vhost': row['vhost'],
+                'created_at': row['created_at'],
+            }

backend/apps/asset/serializers.py

@@ -26,9 +26,9 @@ class SubdomainSerializer(serializers.ModelSerializer):
     class Meta:
         model = Subdomain
         fields = [
-            'id', 'name', 'discovered_at', 'target'
+            'id', 'name', 'created_at', 'target'
         ]
-        read_only_fields = ['id', 'discovered_at']
+        read_only_fields = ['id', 'created_at']
 
 
 class SubdomainListSerializer(serializers.ModelSerializer):
@@ -41,9 +41,9 @@ class SubdomainListSerializer(serializers.ModelSerializer):
     class Meta:
         model = Subdomain
         fields = [
-            'id', 'name', 'discovered_at'
+            'id', 'name', 'created_at'
         ]
-        read_only_fields = ['id', 'discovered_at']
+        read_only_fields = ['id', 'created_at']
 
 
 # class IPAddressListSerializer(serializers.ModelSerializer):
@@ -87,7 +87,7 @@ class WebSiteSerializer(serializers.ModelSerializer):
             'tech',
             'vhost',
             'subdomain',
-            'discovered_at',
+            'created_at',
         ]
         read_only_fields = fields
 
@@ -107,7 +107,7 @@ class VulnerabilitySerializer(serializers.ModelSerializer):
             'cvss_score',
             'description',
             'raw_output',
-            'discovered_at',
+            'created_at',
         ]
         read_only_fields = fields
 
@@ -126,7 +126,7 @@ class VulnerabilitySnapshotSerializer(serializers.ModelSerializer):
             'cvss_score',
             'description',
             'raw_output',
-            'discovered_at',
+            'created_at',
         ]
         read_only_fields = fields
 
@@ -134,8 +134,8 @@ class VulnerabilitySnapshotSerializer(serializers.ModelSerializer):
 class EndpointListSerializer(serializers.ModelSerializer):
     """端点列表序列化器（用于目标端点列表页）"""
 
-    # 将 GF 匹配模式映射为前端使用的 tags 字段
-    tags = serializers.ListField(
+    # GF 匹配模式（gf-patterns 工具匹配的敏感 URL 模式）
+    gfPatterns = serializers.ListField(
         child=serializers.CharField(),
         source='matched_gf_patterns',
         read_only=True,
@@ -155,8 +155,8 @@ class EndpointListSerializer(serializers.ModelSerializer):
             'body_preview',
             'tech',
             'vhost',
-            'tags',
-            'discovered_at',
+            'gfPatterns',
+            'created_at',
         ]
         read_only_fields = fields
 
@@ -164,8 +164,7 @@ class EndpointListSerializer(serializers.ModelSerializer):
 class DirectorySerializer(serializers.ModelSerializer):
     """目录序列化器"""
     
-    website_url = serializers.CharField(source='website.url', read_only=True)
-    discovered_at = serializers.DateTimeField(read_only=True)
+    created_at = serializers.DateTimeField(read_only=True)
     
     class Meta:
         model = Directory
@@ -178,8 +177,7 @@ class DirectorySerializer(serializers.ModelSerializer):
             'lines',
             'content_type',
             'duration',
-            'website_url',
-            'discovered_at',
+            'created_at',
         ]
         read_only_fields = fields
 
@@ -192,12 +190,12 @@ class IPAddressAggregatedSerializer(serializers.Serializer):
     - ip: IP 地址
     - hosts: 该 IP 关联的所有主机名列表
     - ports: 该 IP 关联的所有端口列表
-    - discovered_at: 首次发现时间
+    - created_at: 创建时间
     """
     ip = serializers.IPAddressField(read_only=True)
     hosts = serializers.ListField(child=serializers.CharField(), read_only=True)
     ports = serializers.ListField(child=serializers.IntegerField(), read_only=True)
-    discovered_at = serializers.DateTimeField(read_only=True)
+    created_at = serializers.DateTimeField(read_only=True)
 
 
 # ==================== 快照序列化器 ====================
@@ -207,7 +205,7 @@ class SubdomainSnapshotSerializer(serializers.ModelSerializer):
     
     class Meta:
         model = SubdomainSnapshot
-        fields = ['id', 'name', 'discovered_at']
+        fields = ['id', 'name', 'created_at']
         read_only_fields = fields
 
 
@@ -233,7 +231,7 @@ class WebsiteSnapshotSerializer(serializers.ModelSerializer):
             'tech',
             'vhost',
             'subdomain_name',
-            'discovered_at',
+            'created_at',
         ]
         read_only_fields = fields
 
@@ -241,9 +239,6 @@ class WebsiteSnapshotSerializer(serializers.ModelSerializer):
 class DirectorySnapshotSerializer(serializers.ModelSerializer):
     """目录快照序列化器（用于扫描历史）"""
     
-    # DirectorySnapshot 当前不再关联 Website，这里暂时将 website_url 映射为自身的 url，保证字段兼容
-    website_url = serializers.CharField(source='url', read_only=True)
-    
     class Meta:
         model = DirectorySnapshot
         fields = [
@@ -255,8 +250,7 @@ class DirectorySnapshotSerializer(serializers.ModelSerializer):
             'lines',
             'content_type',
             'duration',
-            'website_url',
-            'discovered_at',
+            'created_at',
         ]
         read_only_fields = fields
 
@@ -264,8 +258,8 @@ class DirectorySnapshotSerializer(serializers.ModelSerializer):
 class EndpointSnapshotSerializer(serializers.ModelSerializer):
     """端点快照序列化器（用于扫描历史）"""
 
-    # 将 GF 匹配模式映射为前端使用的 tags 字段
-    tags = serializers.ListField(
+    # GF 匹配模式（gf-patterns 工具匹配的敏感 URL 模式）
+    gfPatterns = serializers.ListField(
         child=serializers.CharField(),
         source='matched_gf_patterns',
         read_only=True,
@@ -286,7 +280,7 @@ class EndpointSnapshotSerializer(serializers.ModelSerializer):
             'body_preview',
             'tech',
             'vhost',
-            'tags',
-            'discovered_at',
+            'gfPatterns',
+            'created_at',
         ]
         read_only_fields = fields

backend/apps/asset/services/asset/directory_service.py

@@ -1,8 +1,12 @@
-import logging
-from typing import Tuple, Iterator
+"""Directory Service - 目录业务逻辑层"""
+
+import logging
+from typing import List, Iterator, Optional
 
-from apps.asset.models.asset_models import Directory
 from apps.asset.repositories import DjangoDirectoryRepository
+from apps.asset.dtos import DirectoryDTO
+from apps.common.validators import is_valid_url, is_url_match_target
+from apps.common.utils.filter_utils import apply_filters
 
 logger = logging.getLogger(__name__)
 
@@ -10,46 +14,122 @@ logger = logging.getLogger(__name__)
 class DirectoryService:
     """目录业务逻辑层"""
     
+    # 智能过滤字段映射
+    FILTER_FIELD_MAPPING = {
+        'url': 'url',
+        'status': 'status',
+    }
+    
     def __init__(self, repository=None):
-        """
-        初始化目录服务
-        
-        Args:
-            repository: 目录仓储实例（用于依赖注入）
-        """
+        """初始化目录服务"""
         self.repo = repository or DjangoDirectoryRepository()
     
-    # ==================== 创建操作 ====================
-    
-    def bulk_create_ignore_conflicts(self, directory_dtos: list) -> None:
+    def bulk_upsert(self, directory_dtos: List[DirectoryDTO]) -> int:
         """
-        批量创建目录记录，忽略冲突（用于扫描任务）
+        批量创建或更新目录（upsert）
+        
+        存在则更新所有字段，不存在则创建。
         
         Args:
             directory_dtos: DirectoryDTO 列表
-        """
-        return self.repo.bulk_create_ignore_conflicts(directory_dtos)
-    
-    # ==================== 查询操作 ====================
-
-    def get_all(self):
-        """
-        获取所有目录
-        
+            
         Returns:
-            QuerySet: 目录查询集
+            int: 处理的记录数
         """
-        logger.debug("获取所有目录")
-        return self.repo.get_all()
+        if not directory_dtos:
+            return 0
+        
+        try:
+            return self.repo.bulk_upsert(directory_dtos)
+        except Exception as e:
+            logger.error(f"批量 upsert 目录失败: {e}")
+            raise
     
-    def get_directories_by_target(self, target_id: int):
-        logger.debug("获取目标下所有目录 - Target ID: %d", target_id)
-        return self.repo.get_by_target(target_id)
+    def bulk_create_urls(self, target_id: int, target_name: str, target_type: str, urls: List[str]) -> int:
+        """
+        批量创建目录（仅 URL，使用 ignore_conflicts）
+        
+        验证 URL 格式和匹配，过滤无效/不匹配 URL，去重后批量创建。
+        已存在的记录会被跳过。
+        
+        Args:
+            target_id: 目标 ID
+            target_name: 目标名称（用于匹配验证）
+            target_type: 目标类型 ('domain', 'ip', 'cidr')
+            urls: URL 列表
+            
+        Returns:
+            int: 实际创建的记录数
+        """
+        if not urls:
+            return 0
+        
+        # 过滤有效 URL 并去重
+        valid_urls = []
+        seen = set()
+        
+        for url in urls:
+            if not isinstance(url, str):
+                continue
+            url = url.strip()
+            if not url or url in seen:
+                continue
+            if not is_valid_url(url):
+                continue
+            
+            # 匹配验证（前端已阻止不匹配的提交，后端作为双重保障）
+            if not is_url_match_target(url, target_name, target_type):
+                continue
+            
+            seen.add(url)
+            valid_urls.append(url)
+        
+        if not valid_urls:
+            return 0
+        
+        # 获取创建前的数量
+        count_before = self.repo.count_by_target(target_id)
+        
+        # 创建 DTO 列表并批量创建
+        directory_dtos = [
+            DirectoryDTO(url=url, target_id=target_id)
+            for url in valid_urls
+        ]
+        self.repo.bulk_create_ignore_conflicts(directory_dtos)
+        
+        # 获取创建后的数量
+        count_after = self.repo.count_by_target(target_id)
+        return count_after - count_before
+    
+    def get_directories_by_target(self, target_id: int, filter_query: Optional[str] = None):
+        """获取目标下的所有目录"""
+        queryset = self.repo.get_by_target(target_id)
+        if filter_query:
+            queryset = apply_filters(queryset, filter_query, self.FILTER_FIELD_MAPPING)
+        return queryset
+    
+    def get_all(self, filter_query: Optional[str] = None):
+        """获取所有目录"""
+        queryset = self.repo.get_all()
+        if filter_query:
+            queryset = apply_filters(queryset, filter_query, self.FILTER_FIELD_MAPPING)
+        return queryset
 
     def iter_directory_urls_by_target(self, target_id: int, chunk_size: int = 1000) -> Iterator[str]:
-        """流式获取目标下的所有目录 URL，用于导出大批量数据。"""
-        logger.debug("流式导出目标下目录 URL - Target ID: %d", target_id)
+        """流式获取目标下的所有目录 URL"""
         return self.repo.get_urls_for_export(target_id=target_id, batch_size=chunk_size)
 
+    def iter_raw_data_for_csv_export(self, target_id: int) -> Iterator[dict]:
+        """
+        流式获取原始数据用于 CSV 导出
+        
+        Args:
+            target_id: 目标 ID
+        
+        Yields:
+            原始数据字典
+        """
+        return self.repo.iter_raw_data_for_export(target_id=target_id)
+
 
 __all__ = ['DirectoryService']

backend/apps/asset/services/asset/endpoint_service.py

@@ -5,10 +5,12 @@ Endpoint 服务层
 """
 
 import logging
-from typing import List, Optional, Dict, Any, Iterator
+from typing import List, Iterator, Optional
 
 from apps.asset.dtos.asset import EndpointDTO
 from apps.asset.repositories.asset import DjangoEndpointRepository
+from apps.common.validators import is_valid_url, is_url_match_target
+from apps.common.utils.filter_utils import apply_filters
 
 logger = logging.getLogger(__name__)
 
@@ -20,101 +22,101 @@ class EndpointService:
     提供 Endpoint（URL/端点）相关的业务逻辑
     """
     
+    # 智能过滤字段映射
+    FILTER_FIELD_MAPPING = {
+        'url': 'url',
+        'host': 'host',
+        'title': 'title',
+        'status': 'status_code',
+    }
+    
     def __init__(self):
         """初始化 Endpoint 服务"""
         self.repo = DjangoEndpointRepository()
     
-    def bulk_create_endpoints(
-        self,
-        endpoints: List[EndpointDTO],
-        ignore_conflicts: bool = True
-    ) -> int:
+    def bulk_upsert(self, endpoints: List[EndpointDTO]) -> int:
         """
-        批量创建端点记录
+        批量创建或更新端点（upsert）
+        
+        存在则更新所有字段，不存在则创建。
         
         Args:
             endpoints: 端点数据列表
-            ignore_conflicts: 是否忽略冲突（去重）
             
         Returns:
-            int: 创建的记录数
+            int: 处理的记录数
         """
         if not endpoints:
             return 0
         
         try:
-            if ignore_conflicts:
-                return self.repo.bulk_create_ignore_conflicts(endpoints)
-            else:
-                # 如果需要非忽略冲突的版本，可以在 repository 中添加
-                return self.repo.bulk_create_ignore_conflicts(endpoints)
+            return self.repo.bulk_upsert(endpoints)
         except Exception as e:
-            logger.error(f"批量创建端点失败: {e}")
+            logger.error(f"批量 upsert 端点失败: {e}")
             raise
     
-    def get_endpoints_by_website(
-        self,
-        website_id: int,
-        limit: Optional[int] = None
-    ) -> List[Dict[str, Any]]:
+    def bulk_create_urls(self, target_id: int, target_name: str, target_type: str, urls: List[str]) -> int:
         """
-        获取网站下的端点列表
+        批量创建端点（仅 URL，使用 ignore_conflicts）
         
-        Args:
-            website_id: 网站 ID
-            limit: 返回数量限制
-            
-        Returns:
-            List[Dict]: 端点列表
-        """
-        endpoints_dto = self.repo.get_by_website(website_id)
-        
-        if limit:
-            endpoints_dto = endpoints_dto[:limit]
-        
-        endpoints = []
-        for dto in endpoints_dto:
-            endpoints.append({
-                'url': dto.url,
-                'title': dto.title,
-                'status_code': dto.status_code,
-                'content_length': dto.content_length,
-                'webserver': dto.webserver
-            })
-        
-        return endpoints
-    
-    def get_endpoints_by_target(
-        self,
-        target_id: int,
-        limit: Optional[int] = None
-    ) -> List[Dict[str, Any]]:
-        """
-        获取目标下的端点列表
+        验证 URL 格式和匹配，过滤无效/不匹配 URL，去重后批量创建。
+        已存在的记录会被跳过。
         
         Args:
             target_id: 目标 ID
-            limit: 返回数量限制
+            target_name: 目标名称（用于匹配验证）
+            target_type: 目标类型 ('domain', 'ip', 'cidr')
+            urls: URL 列表
             
         Returns:
-            List[Dict]: 端点列表
+            int: 实际创建的记录数
         """
-        endpoints_dto = self.repo.get_by_target(target_id)
+        if not urls:
+            return 0
         
-        if limit:
-            endpoints_dto = endpoints_dto[:limit]
+        # 过滤有效 URL 并去重
+        valid_urls = []
+        seen = set()
         
-        endpoints = []
-        for dto in endpoints_dto:
-            endpoints.append({
-                'url': dto.url,
-                'title': dto.title,
-                'status_code': dto.status_code,
-                'content_length': dto.content_length,
-                'webserver': dto.webserver
-            })
+        for url in urls:
+            if not isinstance(url, str):
+                continue
+            url = url.strip()
+            if not url or url in seen:
+                continue
+            if not is_valid_url(url):
+                continue
+            
+            # 匹配验证（前端已阻止不匹配的提交，后端作为双重保障）
+            if not is_url_match_target(url, target_name, target_type):
+                continue
+            
+            seen.add(url)
+            valid_urls.append(url)
         
-        return endpoints
+        if not valid_urls:
+            return 0
+        
+        # 获取创建前的数量
+        count_before = self.repo.count_by_target(target_id)
+        
+        # 创建 DTO 列表并批量创建
+        endpoint_dtos = [
+            EndpointDTO(url=url, target_id=target_id)
+            for url in valid_urls
+        ]
+        self.repo.bulk_create_ignore_conflicts(endpoint_dtos)
+        
+        # 获取创建后的数量
+        count_after = self.repo.count_by_target(target_id)
+        return count_after - count_before
+    
+    def get_endpoints_by_target(self, target_id: int, filter_query: Optional[str] = None):
+        """获取目标下的所有端点"""
+        queryset = self.repo.get_by_target(target_id)
+        if filter_query:
+            queryset = apply_filters(queryset, filter_query, self.FILTER_FIELD_MAPPING)
+        return queryset
     
     def count_endpoints_by_target(self, target_id: int) -> int:
         """
@@ -127,52 +129,28 @@ class EndpointService:
             int: 端点数量
         """
         return self.repo.count_by_target(target_id)
-    
-    def get_queryset_by_target(self, target_id: int):
-        return self.repo.get_queryset_by_target(target_id)
 
-    def get_all(self):
+    def get_all(self, filter_query: Optional[str] = None):
         """获取所有端点（全局查询）"""
-        return self.repo.get_all()
+        queryset = self.repo.get_all()
+        if filter_query:
+            queryset = apply_filters(queryset, filter_query, self.FILTER_FIELD_MAPPING)
+        return queryset
     
     def iter_endpoint_urls_by_target(self, target_id: int, chunk_size: int = 1000) -> Iterator[str]:
         """流式获取目标下的所有端点 URL，用于导出。"""
-        queryset = self.repo.get_queryset_by_target(target_id)
+        queryset = self.repo.get_by_target(target_id)
         for url in queryset.values_list('url', flat=True).iterator(chunk_size=chunk_size):
             yield url
-    
-    def count_endpoints_by_website(self, website_id: int) -> int:
+
+    def iter_raw_data_for_csv_export(self, target_id: int) -> Iterator[dict]:
         """
-        统计网站下的端点数量
+        流式获取原始数据用于 CSV 导出
         
         Args:
-            website_id: 网站 ID
-            
-        Returns:
-            int: 端点数量
-        """
-        return self.repo.count_by_website(website_id)
-    
-    def soft_delete_endpoints(self, endpoint_ids: List[int]) -> int:
-        """
-        软删除端点
+            target_id: 目标 ID
         
-        Args:
-            endpoint_ids: 端点 ID 列表
-            
-        Returns:
-            int: 更新的数量
+        Yields:
+            原始数据字典
         """
-        return self.repo.soft_delete_by_ids(endpoint_ids)
-    
-    def hard_delete_endpoints(self, endpoint_ids: List[int]) -> tuple:
-        """
-        硬删除端点
-        
-        Args:
-            endpoint_ids: 端点 ID 列表
-            
-        Returns:
-            tuple: (删除总数, 详细信息)
-        """
-        return self.repo.hard_delete_by_ids(endpoint_ids)
+        return self.repo.iter_raw_data_for_export(target_id=target_id)

backend/apps/asset/services/asset/host_port_mapping_service.py

@@ -1,16 +1,31 @@
 """HostPortMapping Service - 业务逻辑层"""
 
 import logging
-from typing import List, Iterator
+from typing import List, Iterator, Optional, Dict
+
+from django.db.models import Min
 
 from apps.asset.repositories.asset import DjangoHostPortMappingRepository
 from apps.asset.dtos.asset import HostPortMappingDTO
+from apps.common.utils.filter_utils import apply_filters
 
 logger = logging.getLogger(__name__)
 
 
 class HostPortMappingService:
-    """主机端口映射服务 - 负责主机端口映射数据的业务逻辑"""
+    """主机端口映射服务 - 负责主机端口映射数据的业务逻辑
+    
+    职责：
+    - 业务逻辑处理（过滤、聚合）
+    - 调用 Repository 进行数据访问
+    """
+    
+    # 智能过滤字段映射
+    FILTER_FIELD_MAPPING = {
+        'ip': 'ip',
+        'port': 'port',
+        'host': 'host',
+    }
     
     def __init__(self):
         self.repo = DjangoHostPortMappingRepository()
@@ -49,13 +64,106 @@ class HostPortMappingService:
     def iter_host_port_by_target(self, target_id: int, batch_size: int = 1000):
         return self.repo.get_for_export(target_id=target_id, batch_size=batch_size)
 
-    def get_ip_aggregation_by_target(self, target_id: int, search: str = None):
-        return self.repo.get_ip_aggregation_by_target(target_id, search=search)
+    def get_ip_aggregation_by_target(
+        self, 
+        target_id: int, 
+        filter_query: Optional[str] = None
+    ) -> List[Dict]:
+        """获取目标下的 IP 聚合数据
+        
+        Args:
+            target_id: 目标 ID
+            filter_query: 智能过滤语法字符串
+        
+        Returns:
+            聚合后的 IP 数据列表
+        """
+        # 从 Repository 获取基础 QuerySet
+        qs = self.repo.get_queryset_by_target(target_id)
+        
+        # Service 层应用过滤逻辑
+        if filter_query:
+            qs = apply_filters(qs, filter_query, self.FILTER_FIELD_MAPPING)
+        
+        # Service 层处理聚合逻辑
+        return self._aggregate_by_ip(qs, filter_query, target_id=target_id)
 
-    def get_all_ip_aggregation(self, search: str = None):
-        """获取所有 IP 聚合数据（全局查询）"""
-        return self.repo.get_all_ip_aggregation(search=search)
+    def get_all_ip_aggregation(self, filter_query: Optional[str] = None) -> List[Dict]:
+        """获取所有 IP 聚合数据（全局查询）
+        
+        Args:
+            filter_query: 智能过滤语法字符串
+        
+        Returns:
+            聚合后的 IP 数据列表
+        """
+        # 从 Repository 获取基础 QuerySet
+        qs = self.repo.get_all_queryset()
+        
+        # Service 层应用过滤逻辑
+        if filter_query:
+            qs = apply_filters(qs, filter_query, self.FILTER_FIELD_MAPPING)
+        
+        # Service 层处理聚合逻辑
+        return self._aggregate_by_ip(qs, filter_query)
+
+    def _aggregate_by_ip(
+        self, 
+        qs, 
+        filter_query: Optional[str] = None,
+        target_id: Optional[int] = None
+    ) -> List[Dict]:
+        """按 IP 聚合数据
+        
+        Args:
+            qs: 已过滤的 QuerySet
+            filter_query: 过滤条件（用于子查询）
+            target_id: 目标 ID（用于子查询限定范围）
+        
+        Returns:
+            聚合后的数据列表
+        """
+        ip_aggregated = (
+            qs
+            .values('ip')
+            .annotate(created_at=Min('created_at'))
+            .order_by('-created_at')
+        )
+
+        results = []
+        for item in ip_aggregated:
+            ip = item['ip']
+            
+            # 获取该 IP 的所有 host 和 port（也需要应用过滤条件）
+            mappings_qs = self.repo.get_queryset_by_ip(ip, target_id=target_id)
+            if filter_query:
+                mappings_qs = apply_filters(mappings_qs, filter_query, self.FILTER_FIELD_MAPPING)
+            
+            mappings = mappings_qs.values('host', 'port').distinct()
+            hosts = sorted({m['host'] for m in mappings})
+            ports = sorted({m['port'] for m in mappings})
+            
+            results.append({
+                'ip': ip,
+                'hosts': hosts,
+                'ports': ports,
+                'created_at': item['created_at'],
+            })
+        
+        return results
 
     def iter_ips_by_target(self, target_id: int, batch_size: int = 1000) -> Iterator[str]:
         """流式获取目标下的所有唯一 IP 地址。"""
         return self.repo.get_ips_for_export(target_id=target_id, batch_size=batch_size)
+
+    def iter_raw_data_for_csv_export(self, target_id: int) -> Iterator[dict]:
+        """
+        流式获取原始数据用于 CSV 导出
+        
+        Args:
+            target_id: 目标 ID
+        
+        Yields:
+            原始数据字典 {ip, host, port, created_at}
+        """
+        return self.repo.iter_raw_data_for_export(target_id=target_id)

backend/apps/asset/services/asset/subdomain_service.py

@@ -1,15 +1,33 @@
 import logging
-from typing import Tuple, List, Dict
+from typing import List, Dict, Optional
+from dataclasses import dataclass
 
 from apps.asset.repositories import DjangoSubdomainRepository
 from apps.asset.dtos import SubdomainDTO
+from apps.common.validators import is_valid_domain
+from apps.common.utils.filter_utils import apply_filters
 
 logger = logging.getLogger(__name__)
 
 
+@dataclass
+class BulkCreateResult:
+    """批量创建结果"""
+    created_count: int
+    skipped_count: int
+    invalid_count: int
+    mismatched_count: int
+    total_received: int
+
+
 class SubdomainService:
     """子域名业务逻辑层"""
     
+    # 智能过滤字段映射
+    FILTER_FIELD_MAPPING = {
+        'name': 'name',
+    }
+    
     def __init__(self, repository=None):
         """
         初始化子域名服务
@@ -21,44 +39,50 @@ class SubdomainService:
     
     # ==================== 查询操作 ====================
     
-    def get_all(self):
+    def get_all(self, filter_query: Optional[str] = None):
         """
         获取所有子域名
         
+        Args:
+            filter_query: 智能过滤语法字符串
+        
         Returns:
             QuerySet: 子域名查询集
         """
         logger.debug("获取所有子域名")
-        return self.repo.get_all()
+        queryset = self.repo.get_all()
+        if filter_query:
+            queryset = apply_filters(queryset, filter_query, self.FILTER_FIELD_MAPPING)
+        return queryset
     
-    # ==================== 创建操作 ====================
-    
-    def get_or_create(self, name: str, target_id: int) -> Tuple[any, bool]:
+    def get_subdomains_by_target(self, target_id: int, filter_query: Optional[str] = None):
         """
-        获取或创建子域名
+        获取目标下的子域名
+        
+        Args:
+            target_id: 目标 ID
+            filter_query: 智能过滤语法字符串
+        
+        Returns:
+            QuerySet: 子域名查询集
+        """
+        queryset = self.repo.get_by_target(target_id)
+        if filter_query:
+            queryset = apply_filters(queryset, filter_query, self.FILTER_FIELD_MAPPING)
+        return queryset
+
+    def count_subdomains_by_target(self, target_id: int) -> int:
+        """
+        统计目标下的子域名数量
         
         Args:
-            name: 子域名名称
             target_id: 目标 ID
         
         Returns:
-            (Subdomain对象, 是否新创建)
+            int: 子域名数量
         """
-        logger.debug("获取或创建子域名 - Name: %s, Target ID: %d", name, target_id)
-        return self.repo.get_or_create(name, target_id)
-
-    def bulk_create_ignore_conflicts(self, items: List[SubdomainDTO]) -> None:
-        """
-        批量创建子域名，忽略冲突
-        
-        Args:
-            items: 子域名 DTO 列表
-        
-        Note:
-            使用 ignore_conflicts 策略，重复记录会被跳过
-        """
-        logger.debug("批量创建子域名 - 数量: %d", len(items))
-        return self.repo.bulk_create_ignore_conflicts(items)
+        logger.debug("统计目标下子域名数量 - Target ID: %d", target_id)
+        return self.repo.count_by_target(target_id)
     
     def get_by_names_and_target_id(self, names: set, target_id: int) -> dict:
         """
@@ -85,25 +109,8 @@ class SubdomainService:
             List[str]: 子域名名称列表
         """
         logger.debug("获取目标下所有子域名 - Target ID: %d", target_id)
-        # 通过仓储层统一访问数据库，内部已使用 iterator() 做流式查询
         return list(self.repo.get_domains_for_export(target_id=target_id))
     
-    def get_subdomains_by_target(self, target_id: int):
-        return self.repo.get_by_target(target_id)
-    
-    def count_subdomains_by_target(self, target_id: int) -> int:
-        """
-        统计目标下的子域名数量
-        
-        Args:
-            target_id: 目标 ID
-        
-        Returns:
-            int: 子域名数量
-        """
-        logger.debug("统计目标下子域名数量 - Target ID: %d", target_id)
-        return self.repo.count_by_target(target_id)
-    
     def iter_subdomain_names_by_target(self, target_id: int, chunk_size: int = 1000):
         """
         流式获取目标下的所有子域名名称（内存优化）
@@ -116,8 +123,123 @@ class SubdomainService:
             str: 子域名名称
         """
         logger.debug("流式获取目标下所有子域名 - Target ID: %d, 批次大小: %d", target_id, chunk_size)
-        # 通过仓储层统一访问数据库，内部已使用 iterator() 做流式查询
         return self.repo.get_domains_for_export(target_id=target_id, batch_size=chunk_size)
 
+    def iter_raw_data_for_csv_export(self, target_id: int):
+        """
+        流式获取原始数据用于 CSV 导出
+        
+        Args:
+            target_id: 目标 ID
+        
+        Yields:
+            原始数据字典 {name, created_at}
+        """
+        return self.repo.iter_raw_data_for_export(target_id=target_id)
 
-__all__ = ['SubdomainService']
+    # ==================== 创建操作 ====================
+
+    def bulk_create_ignore_conflicts(self, items: List[SubdomainDTO]) -> None:
+        """
+        批量创建子域名，忽略冲突
+        
+        Args:
+            items: 子域名 DTO 列表
+        
+        Note:
+            使用 ignore_conflicts 策略，重复记录会被跳过
+        """
+        logger.debug("批量创建子域名 - 数量: %d", len(items))
+        return self.repo.bulk_create_ignore_conflicts(items)
+
+    def bulk_create_subdomains(
+        self,
+        target_id: int,
+        target_name: str,
+        subdomains: List[str]
+    ) -> BulkCreateResult:
+        """
+        批量创建子域名（带验证）
+        
+        Args:
+            target_id: 目标 ID
+            target_name: 目标域名（用于匹配验证）
+            subdomains: 子域名列表
+        
+        Returns:
+            BulkCreateResult: 创建结果统计
+        """
+        total_received = len(subdomains)
+        target_name = target_name.lower().strip()
+        
+        def is_subdomain_match(subdomain: str) -> bool:
+            """验证子域名是否匹配目标域名"""
+            if subdomain == target_name:
+                return True
+            if subdomain.endswith('.' + target_name):
+                return True
+            return False
+        
+        # 过滤有效的子域名
+        valid_subdomains = []
+        invalid_count = 0
+        mismatched_count = 0
+        
+        for subdomain in subdomains:
+            if not isinstance(subdomain, str) or not subdomain.strip():
+                continue
+            
+            subdomain = subdomain.lower().strip()
+            
+            # 验证格式
+            if not is_valid_domain(subdomain):
+                invalid_count += 1
+                continue
+            
+            # 验证匹配
+            if not is_subdomain_match(subdomain):
+                mismatched_count += 1
+                continue
+            
+            valid_subdomains.append(subdomain)
+        
+        # 去重
+        unique_subdomains = list(set(valid_subdomains))
+        duplicate_count = len(valid_subdomains) - len(unique_subdomains)
+        
+        if not unique_subdomains:
+            return BulkCreateResult(
+                created_count=0,
+                skipped_count=duplicate_count,
+                invalid_count=invalid_count,
+                mismatched_count=mismatched_count,
+                total_received=total_received,
+            )
+        
+        # 获取创建前的数量
+        count_before = self.repo.count_by_target(target_id)
+        
+        # 创建 DTO 列表并批量创建
+        subdomain_dtos = [
+            SubdomainDTO(name=name, target_id=target_id)
+            for name in unique_subdomains
+        ]
+        self.repo.bulk_create_ignore_conflicts(subdomain_dtos)
+        
+        # 获取创建后的数量
+        count_after = self.repo.count_by_target(target_id)
+        created_count = count_after - count_before
+        
+        # 计算因数据库冲突跳过的数量
+        db_skipped = len(unique_subdomains) - created_count
+        
+        return BulkCreateResult(
+            created_count=created_count,
+            skipped_count=duplicate_count + db_skipped,
+            invalid_count=invalid_count,
+            mismatched_count=mismatched_count,
+            total_received=total_received,
+        )
+
+
+__all__ = ['SubdomainService', 'BulkCreateResult']

backend/apps/asset/services/asset/vulnerability_service.py

@@ -1,11 +1,13 @@
 """Vulnerability Service - 漏洞资产业务逻辑层"""
 
 import logging
-from typing import List
+from typing import List, Optional
 
 from apps.asset.models import Vulnerability
 from apps.asset.dtos.asset import VulnerabilityDTO
 from apps.common.decorators import auto_ensure_db_connection
+from apps.common.utils import deduplicate_for_bulk
+from apps.common.utils.filter_utils import apply_filters
 
 logger = logging.getLogger(__name__)
 
@@ -16,10 +18,20 @@ class VulnerabilityService:
 
     当前提供基础的批量创建能力，使用 ignore_conflicts 依赖数据库唯一约束去重。
     """
+    
+    # 智能过滤字段映射
+    FILTER_FIELD_MAPPING = {
+        'type': 'vuln_type',
+        'severity': 'severity',
+        'source': 'source',
+        'url': 'url',
+    }
 
     def bulk_create_ignore_conflicts(self, items: List[VulnerabilityDTO]) -> None:
         """批量创建漏洞资产记录，忽略冲突。
 
+        注意：会自动按 (target_id, url, vuln_type, source) 去重，保留最后一条记录。
+
         Note:
             - 是否去重取决于模型上的唯一/部分唯一约束；
             - 当前 Vulnerability 模型未定义唯一约束，因此会保留全部记录。
@@ -29,6 +41,9 @@ class VulnerabilityService:
             return
 
         try:
+            # 根据模型唯一约束自动去重（如果模型没有唯一约束则跳过）
+            unique_items = deduplicate_for_bulk(items, Vulnerability)
+            
             vulns = [
                 Vulnerability(
                     target_id=item.target_id,
@@ -40,7 +55,7 @@ class VulnerabilityService:
                     description=item.description,
                     raw_output=item.raw_output,
                 )
-                for item in items
+                for item in unique_items
             ]
 
             Vulnerability.objects.bulk_create(vulns, ignore_conflicts=True)
@@ -57,24 +72,34 @@ class VulnerabilityService:
 
     # ==================== 查询方法 ====================
 
-    def get_all(self):
+    def get_all(self, filter_query: Optional[str] = None):
         """获取所有漏洞 QuerySet（用于全局漏洞列表）。
 
-        Returns:
-            QuerySet[Vulnerability]: 所有漏洞，按发现时间倒序
-        """
-        return Vulnerability.objects.filter(deleted_at__isnull=True).order_by("-discovered_at")
+        Args:
+            filter_query: 智能过滤语法字符串
 
-    def get_queryset_by_target(self, target_id: int):
+        Returns:
+            QuerySet[Vulnerability]: 所有漏洞，按创建时间倒序
+        """
+        queryset = Vulnerability.objects.all().order_by("-created_at")
+        if filter_query:
+            queryset = apply_filters(queryset, filter_query, self.FILTER_FIELD_MAPPING)
+        return queryset
+
+    def get_vulnerabilities_by_target(self, target_id: int, filter_query: Optional[str] = None):
         """按目标获取漏洞 QuerySet（用于分页）。
 
         Args:
             target_id: 目标 ID
+            filter_query: 智能过滤语法字符串
 
         Returns:
-            QuerySet[Vulnerability]: 目标下的所有漏洞，按发现时间倒序
+            QuerySet[Vulnerability]: 目标下的所有漏洞，按创建时间倒序
         """
-        return Vulnerability.objects.filter(target_id=target_id).order_by("-discovered_at")
+        queryset = Vulnerability.objects.filter(target_id=target_id).order_by("-created_at")
+        if filter_query:
+            queryset = apply_filters(queryset, filter_query, self.FILTER_FIELD_MAPPING)
+        return queryset
 
     def count_by_target(self, target_id: int) -> int:
         """统计目标下的漏洞数量。"""

backend/apps/asset/services/asset/website_service.py

@@ -1,8 +1,12 @@
+"""WebSite Service - 网站业务逻辑层"""
+
 import logging
-from typing import Tuple, List
+from typing import List, Iterator, Optional
 
 from apps.asset.repositories import DjangoWebSiteRepository
 from apps.asset.dtos import WebSiteDTO
+from apps.common.validators import is_valid_url, is_url_match_target
+from apps.common.utils.filter_utils import apply_filters
 
 logger = logging.getLogger(__name__)
 
@@ -10,82 +14,128 @@ logger = logging.getLogger(__name__)
 class WebSiteService:
     """网站业务逻辑层"""
     
+    # 智能过滤字段映射
+    FILTER_FIELD_MAPPING = {
+        'url': 'url',
+        'host': 'host',
+        'title': 'title',
+        'status': 'status_code',
+    }
+    
     def __init__(self, repository=None):
-        """
-        初始化网站服务
-        
-        Args:
-            repository: 网站仓储实例（用于依赖注入）
-        """
+        """初始化网站服务"""
         self.repo = repository or DjangoWebSiteRepository()
     
-    # ==================== 创建操作 ====================
-    
-    def bulk_create_ignore_conflicts(self, website_dtos: List[WebSiteDTO]) -> None:
+    def bulk_upsert(self, website_dtos: List[WebSiteDTO]) -> int:
         """
-        批量创建网站记录，忽略冲突（用于扫描任务）
+        批量创建或更新网站（upsert）
+        
+        存在则更新所有字段，不存在则创建。
         
         Args:
             website_dtos: WebSiteDTO 列表
-        
-        Note:
-            使用 ignore_conflicts 策略，重复记录会被跳过
-        """
-        logger.debug("批量创建网站 - 数量: %d", len(website_dtos))
-        return self.repo.bulk_create_ignore_conflicts(website_dtos)
-    
-    # ==================== 查询操作 ====================
-    
-    def get_by_url(self, url: str, target_id: int) -> int:
-        """
-        根据 URL 和 target_id 查找网站 ID
-        
-        Args:
-            url: 网站 URL
-            target_id: 目标 ID
             
         Returns:
-            int: 网站 ID，如果不存在返回 None
+            int: 处理的记录数
         """
-        return self.repo.get_by_url(url=url, target_id=target_id)
-    
-    # ==================== 查询操作 ====================
-
-    def get_all(self):
-        """
-        获取所有网站
+        if not website_dtos:
+            return 0
         
-        Returns:
-            QuerySet: 网站查询集
-        """
-        logger.debug("获取所有网站")
-        return self.repo.get_all()
+        try:
+            return self.repo.bulk_upsert(website_dtos)
+        except Exception as e:
+            logger.error(f"批量 upsert 网站失败: {e}")
+            raise
     
-    def get_websites_by_target(self, target_id: int):
-        return self.repo.get_by_target(target_id)
-    
-    def count_websites_by_scan(self, scan_id: int) -> int:
+    def bulk_create_urls(self, target_id: int, target_name: str, target_type: str, urls: List[str]) -> int:
         """
-        统计扫描下的网站数量
+        批量创建网站（仅 URL，使用 ignore_conflicts）
+        
+        验证 URL 格式和匹配，过滤无效/不匹配 URL，去重后批量创建。
+        已存在的记录会被跳过。
         
         Args:
-            scan_id: 扫描 ID
-        
+            target_id: 目标 ID
+            target_name: 目标名称（用于匹配验证）
+            target_type: 目标类型 ('domain', 'ip', 'cidr')
+            urls: URL 列表
+            
         Returns:
-            int: 网站数量
+            int: 实际创建的记录数
         """
-        logger.debug("统计扫描下网站数量 - Scan ID: %d", scan_id)
-        return self.repo.count_by_scan(scan_id)
+        if not urls:
+            return 0
+        
+        # 过滤有效 URL 并去重
+        valid_urls = []
+        seen = set()
+        
+        for url in urls:
+            if not isinstance(url, str):
+                continue
+            url = url.strip()
+            if not url or url in seen:
+                continue
+            if not is_valid_url(url):
+                continue
+            
+            # 匹配验证（前端已阻止不匹配的提交，后端作为双重保障）
+            if not is_url_match_target(url, target_name, target_type):
+                continue
+            
+            seen.add(url)
+            valid_urls.append(url)
+        
+        if not valid_urls:
+            return 0
+        
+        # 获取创建前的数量
+        count_before = self.repo.count_by_target(target_id)
+        
+        # 创建 DTO 列表并批量创建
+        website_dtos = [
+            WebSiteDTO(url=url, target_id=target_id)
+            for url in valid_urls
+        ]
+        self.repo.bulk_create_ignore_conflicts(website_dtos)
+        
+        # 获取创建后的数量
+        count_after = self.repo.count_by_target(target_id)
+        return count_after - count_before
+    
+    def get_websites_by_target(self, target_id: int, filter_query: Optional[str] = None):
+        """获取目标下的所有网站"""
+        queryset = self.repo.get_by_target(target_id)
+        if filter_query:
+            queryset = apply_filters(queryset, filter_query, self.FILTER_FIELD_MAPPING)
+        return queryset
+    
+    def get_all(self, filter_query: Optional[str] = None):
+        """获取所有网站"""
+        queryset = self.repo.get_all()
+        if filter_query:
+            queryset = apply_filters(queryset, filter_query, self.FILTER_FIELD_MAPPING)
+        return queryset
+    
+    def get_by_url(self, url: str, target_id: int) -> int:
+        """根据 URL 和 target_id 查找网站 ID"""
+        return self.repo.get_by_url(url=url, target_id=target_id)
     
     def iter_website_urls_by_target(self, target_id: int, chunk_size: int = 1000):
-        """流式获取目标下的所有站点 URL（内存优化，委托给 Repository 层）"""
-        logger.debug(
-            "流式获取目标下所有站点 URL - Target ID: %d, 批次大小: %d",
-            target_id,
-            chunk_size,
-        )
-        # 通过仓储层统一访问数据库，避免 Service 直接依赖 ORM
+        """流式获取目标下的所有站点 URL"""
         return self.repo.get_urls_for_export(target_id=target_id, batch_size=chunk_size)
 
+    def iter_raw_data_for_csv_export(self, target_id: int) -> Iterator[dict]:
+        """
+        流式获取原始数据用于 CSV 导出
+        
+        Args:
+            target_id: 目标 ID
+        
+        Yields:
+            原始数据字典
+        """
+        return self.repo.iter_raw_data_for_export(target_id=target_id)
+
 
 __all__ = ['WebSiteService']

backend/apps/asset/services/snapshot/directory_snapshots_service.py

@@ -26,10 +26,9 @@ class DirectorySnapshotsService:
         2. 同步到资产表（去重，不包含 scan_id）
         
         Args:
-            items: 目录快照 DTO 列表（必须包含 website_id）
+            items: 目录快照 DTO 列表（必须包含 target_id）
         
         Raises:
-            ValueError: 如果 items 中的 website_id 为 None
             Exception: 数据库操作失败
         """
         if not items:
@@ -49,14 +48,13 @@ class DirectorySnapshotsService:
             logger.debug("步骤 1: 保存到快照表")
             self.snapshot_repo.save_snapshots(items)
             
-            # 步骤 2: 转换为资产 DTO 并保存到资产表
-            # 注意：去重是通过数据库的 UNIQUE 约束 + ignore_conflicts 实现的
+            # 步骤 2: 转换为资产 DTO 并保存到资产表（upsert）
             # - 新记录：插入资产表
-            # - 已存在的记录：自动跳过
-            logger.debug("步骤 2: 同步到资产表（通过 Service 层）")
+            # - 已存在的记录：更新字段（created_at 不更新，保留创建时间）
+            logger.debug("步骤 2: 同步到资产表（通过 Service 层，upsert）")
             asset_items = [item.to_asset_dto() for item in items]
             
-            self.asset_service.bulk_create_ignore_conflicts(asset_items)
+            self.asset_service.bulk_upsert(asset_items)
             
             logger.info("目录快照和资产数据保存成功 - 数量: %d", len(items))
             
@@ -69,15 +67,44 @@ class DirectorySnapshotsService:
             )
             raise
     
-    def get_by_scan(self, scan_id: int):
-        return self.snapshot_repo.get_by_scan(scan_id)
+    # 智能过滤字段映射
+    FILTER_FIELD_MAPPING = {
+        'url': 'url',
+        'status': 'status',
+        'content_type': 'content_type',
+    }
+    
+    def get_by_scan(self, scan_id: int, filter_query: str = None):
+        from apps.common.utils.filter_utils import apply_filters
+        
+        queryset = self.snapshot_repo.get_by_scan(scan_id)
+        if filter_query:
+            queryset = apply_filters(queryset, filter_query, self.FILTER_FIELD_MAPPING)
+        return queryset
 
-    def get_all(self):
+    def get_all(self, filter_query: str = None):
         """获取所有目录快照"""
-        return self.snapshot_repo.get_all()
+        from apps.common.utils.filter_utils import apply_filters
+        
+        queryset = self.snapshot_repo.get_all()
+        if filter_query:
+            queryset = apply_filters(queryset, filter_query, self.FILTER_FIELD_MAPPING)
+        return queryset
 
     def iter_directory_urls_by_scan(self, scan_id: int, chunk_size: int = 1000) -> Iterator[str]:
         """流式获取某次扫描下的所有目录 URL。"""
         queryset = self.snapshot_repo.get_by_scan(scan_id)
         for snapshot in queryset.iterator(chunk_size=chunk_size):
             yield snapshot.url
+
+    def iter_raw_data_for_csv_export(self, scan_id: int) -> Iterator[dict]:
+        """
+        流式获取原始数据用于 CSV 导出
+        
+        Args:
+            scan_id: 扫描 ID
+        
+        Yields:
+            原始数据字典
+        """
+        return self.snapshot_repo.iter_raw_data_for_export(scan_id=scan_id)

backend/apps/asset/services/snapshot/endpoint_snapshots_service.py

@@ -50,13 +50,11 @@ class EndpointSnapshotsService:
             self.snapshot_repo.save_snapshots(items)
             
             # 步骤 2: 转换为资产 DTO 并保存到资产表
-            # 注意：去重是通过数据库的 UNIQUE 约束 + ignore_conflicts 实现的
-            # - 新记录：插入资产表
-            # - 已存在的记录：自动跳过
+            # 使用 upsert：新记录插入，已存在的记录更新
             logger.debug("步骤 2: 同步到资产表（通过 Service 层）")
             asset_items = [item.to_asset_dto() for item in items]
             
-            self.asset_service.bulk_create_endpoints(asset_items)
+            self.asset_service.bulk_upsert(asset_items)
             
             logger.info("端点快照和资产数据保存成功 - 数量: %d", len(items))
             
@@ -69,15 +67,47 @@ class EndpointSnapshotsService:
             )
             raise
     
-    def get_by_scan(self, scan_id: int):
-        return self.snapshot_repo.get_by_scan(scan_id)
+    # 智能过滤字段映射
+    FILTER_FIELD_MAPPING = {
+        'url': 'url',
+        'host': 'host',
+        'title': 'title',
+        'status': 'status_code',
+        'webserver': 'webserver',
+        'tech': 'tech',
+    }
+    
+    def get_by_scan(self, scan_id: int, filter_query: str = None):
+        from apps.common.utils.filter_utils import apply_filters
+        
+        queryset = self.snapshot_repo.get_by_scan(scan_id)
+        if filter_query:
+            queryset = apply_filters(queryset, filter_query, self.FILTER_FIELD_MAPPING)
+        return queryset
 
-    def get_all(self):
+    def get_all(self, filter_query: str = None):
         """获取所有端点快照"""
-        return self.snapshot_repo.get_all()
+        from apps.common.utils.filter_utils import apply_filters
+        
+        queryset = self.snapshot_repo.get_all()
+        if filter_query:
+            queryset = apply_filters(queryset, filter_query, self.FILTER_FIELD_MAPPING)
+        return queryset
 
     def iter_endpoint_urls_by_scan(self, scan_id: int, chunk_size: int = 1000) -> Iterator[str]:
         """流式获取某次扫描下的所有端点 URL。"""
         queryset = self.snapshot_repo.get_by_scan(scan_id)
         for snapshot in queryset.iterator(chunk_size=chunk_size):
             yield snapshot.url
+
+    def iter_raw_data_for_csv_export(self, scan_id: int) -> Iterator[dict]:
+        """
+        流式获取原始数据用于 CSV 导出
+        
+        Args:
+            scan_id: 扫描 ID
+        
+        Yields:
+            原始数据字典
+        """
+        return self.snapshot_repo.iter_raw_data_for_export(scan_id=scan_id)

backend/apps/asset/services/snapshot/host_port_mapping_snapshots_service.py

@@ -69,13 +69,25 @@ class HostPortMappingSnapshotsService:
             )
             raise
     
-    def get_ip_aggregation_by_scan(self, scan_id: int, search: str = None):
-        return self.snapshot_repo.get_ip_aggregation_by_scan(scan_id, search=search)
+    def get_ip_aggregation_by_scan(self, scan_id: int, filter_query: str = None):
+        return self.snapshot_repo.get_ip_aggregation_by_scan(scan_id, filter_query=filter_query)
 
-    def get_all_ip_aggregation(self, search: str = None):
+    def get_all_ip_aggregation(self, filter_query: str = None):
         """获取所有 IP 聚合数据"""
-        return self.snapshot_repo.get_all_ip_aggregation(search=search)
+        return self.snapshot_repo.get_all_ip_aggregation(filter_query=filter_query)
 
     def iter_ips_by_scan(self, scan_id: int, batch_size: int = 1000) -> Iterator[str]:
         """流式获取某次扫描下的所有唯一 IP 地址。"""
         return self.snapshot_repo.get_ips_for_export(scan_id=scan_id, batch_size=batch_size)
+
+    def iter_raw_data_for_csv_export(self, scan_id: int) -> Iterator[dict]:
+        """
+        流式获取原始数据用于 CSV 导出
+        
+        Args:
+            scan_id: 扫描 ID
+        
+        Yields:
+            原始数据字典 {ip, host, port, created_at}
+        """
+        return self.snapshot_repo.iter_raw_data_for_export(scan_id=scan_id)

backend/apps/asset/services/snapshot/subdomain_snapshots_service.py

@@ -66,14 +66,41 @@ class SubdomainSnapshotsService:
             )
             raise
     
-    def get_by_scan(self, scan_id: int):
-        return self.subdomain_snapshot_repo.get_by_scan(scan_id)
+    # 智能过滤字段映射
+    FILTER_FIELD_MAPPING = {
+        'name': 'name',
+    }
+    
+    def get_by_scan(self, scan_id: int, filter_query: str = None):
+        from apps.common.utils.filter_utils import apply_filters
+        
+        queryset = self.subdomain_snapshot_repo.get_by_scan(scan_id)
+        if filter_query:
+            queryset = apply_filters(queryset, filter_query, self.FILTER_FIELD_MAPPING)
+        return queryset
 
-    def get_all(self):
+    def get_all(self, filter_query: str = None):
         """获取所有子域名快照"""
-        return self.subdomain_snapshot_repo.get_all()
+        from apps.common.utils.filter_utils import apply_filters
+        
+        queryset = self.subdomain_snapshot_repo.get_all()
+        if filter_query:
+            queryset = apply_filters(queryset, filter_query, self.FILTER_FIELD_MAPPING)
+        return queryset
 
     def iter_subdomain_names_by_scan(self, scan_id: int, chunk_size: int = 1000) -> Iterator[str]:
         queryset = self.subdomain_snapshot_repo.get_by_scan(scan_id)
         for snapshot in queryset.iterator(chunk_size=chunk_size):
-            yield snapshot.name
+            yield snapshot.name
+
+    def iter_raw_data_for_csv_export(self, scan_id: int) -> Iterator[dict]:
+        """
+        流式获取原始数据用于 CSV 导出
+        
+        Args:
+            scan_id: 扫描 ID
+        
+        Yields:
+            原始数据字典 {name, created_at}
+        """
+        return self.subdomain_snapshot_repo.iter_raw_data_for_export(scan_id=scan_id)

backend/apps/asset/services/snapshot/vulnerability_snapshots_service.py

@@ -66,13 +66,31 @@ class VulnerabilitySnapshotsService:
             )
             raise
 
-    def get_by_scan(self, scan_id: int):
-        """按扫描任务获取所有漏洞快照。"""
-        return self.snapshot_repo.get_by_scan(scan_id)
+    # 智能过滤字段映射
+    FILTER_FIELD_MAPPING = {
+        'type': 'vuln_type',
+        'url': 'url',
+        'severity': 'severity',
+        'source': 'source',
+    }
 
-    def get_all(self):
+    def get_by_scan(self, scan_id: int, filter_query: str = None):
+        """按扫描任务获取所有漏洞快照。"""
+        from apps.common.utils.filter_utils import apply_filters
+        
+        queryset = self.snapshot_repo.get_by_scan(scan_id)
+        if filter_query:
+            queryset = apply_filters(queryset, filter_query, self.FILTER_FIELD_MAPPING)
+        return queryset
+
+    def get_all(self, filter_query: str = None):
         """获取所有漏洞快照"""
-        return self.snapshot_repo.get_all()
+        from apps.common.utils.filter_utils import apply_filters
+        
+        queryset = self.snapshot_repo.get_all()
+        if filter_query:
+            queryset = apply_filters(queryset, filter_query, self.FILTER_FIELD_MAPPING)
+        return queryset
 
     def iter_vuln_urls_by_scan(self, scan_id: int, chunk_size: int = 1000) -> Iterator[str]:
         """流式获取某次扫描下的所有漏洞 URL。"""

backend/apps/asset/services/snapshot/website_snapshots_service.py

@@ -49,14 +49,13 @@ class WebsiteSnapshotsService:
             logger.debug("步骤 1: 保存到快照表")
             self.snapshot_repo.save_snapshots(items)
             
-            # 步骤 2: 转换为资产 DTO 并保存到资产表
-            # 注意：去重是通过数据库的 UNIQUE 约束 + ignore_conflicts 实现的
+            # 步骤 2: 转换为资产 DTO 并保存到资产表（upsert）
             # - 新记录：插入资产表
-            # - 已存在的记录：自动跳过
-            logger.debug("步骤 2: 同步到资产表（通过 Service 层）")
+            # - 已存在的记录：更新字段（created_at 不更新，保留创建时间）
+            logger.debug("步骤 2: 同步到资产表（通过 Service 层，upsert）")
             asset_items = [item.to_asset_dto() for item in items]
             
-            self.asset_service.bulk_create_ignore_conflicts(asset_items)
+            self.asset_service.bulk_upsert(asset_items)
             
             logger.info("网站快照和资产数据保存成功 - 数量: %d", len(items))
             
@@ -69,15 +68,47 @@ class WebsiteSnapshotsService:
             )
             raise
     
-    def get_by_scan(self, scan_id: int):
-        return self.snapshot_repo.get_by_scan(scan_id)
+    # 智能过滤字段映射
+    FILTER_FIELD_MAPPING = {
+        'url': 'url',
+        'host': 'host',
+        'title': 'title',
+        'status': 'status',
+        'webserver': 'web_server',
+        'tech': 'tech',
+    }
+    
+    def get_by_scan(self, scan_id: int, filter_query: str = None):
+        from apps.common.utils.filter_utils import apply_filters
+        
+        queryset = self.snapshot_repo.get_by_scan(scan_id)
+        if filter_query:
+            queryset = apply_filters(queryset, filter_query, self.FILTER_FIELD_MAPPING)
+        return queryset
 
-    def get_all(self):
+    def get_all(self, filter_query: str = None):
         """获取所有网站快照"""
-        return self.snapshot_repo.get_all()
+        from apps.common.utils.filter_utils import apply_filters
+        
+        queryset = self.snapshot_repo.get_all()
+        if filter_query:
+            queryset = apply_filters(queryset, filter_query, self.FILTER_FIELD_MAPPING)
+        return queryset
 
     def iter_website_urls_by_scan(self, scan_id: int, chunk_size: int = 1000) -> Iterator[str]:
-        """流式获取某次扫描下的所有站点 URL（按发现时间倒序）。"""
+        """流式获取某次扫描下的所有站点 URL（按创建时间倒序）。"""
         queryset = self.snapshot_repo.get_by_scan(scan_id)
         for snapshot in queryset.iterator(chunk_size=chunk_size):
             yield snapshot.url
+
+    def iter_raw_data_for_csv_export(self, scan_id: int) -> Iterator[dict]:
+        """
+        流式获取原始数据用于 CSV 导出
+        
+        Args:
+            scan_id: 扫描 ID
+        
+        Yields:
+            原始数据字典
+        """
+        return self.snapshot_repo.iter_raw_data_for_export(scan_id=scan_id)

backend/apps/common/container_bootstrap.py

@@ -66,12 +66,19 @@ def fetch_config_and_setup_django():
         os.environ.setdefault("ENABLE_COMMAND_LOGGING", str(config['logging']['enableCommandLogging']).lower())
         os.environ.setdefault("DEBUG", str(config['debug']))
         
+        # Git 加速配置（用于 Git clone 加速）
+        git_mirror = config.get('gitMirror', '')
+        if git_mirror:
+            os.environ.setdefault("GIT_MIRROR", git_mirror)
+        
         print(f"[CONFIG] ✓ 配置获取成功")
         print(f"[CONFIG]   DB_HOST: {db_host}")
         print(f"[CONFIG]   DB_PORT: {db_port}")
         print(f"[CONFIG]   DB_NAME: {db_name}")
         print(f"[CONFIG]   DB_USER: {db_user}")
         print(f"[CONFIG]   REDIS_URL: {config['redisUrl']}")
+        if git_mirror:
+            print(f"[CONFIG]   GIT_MIRROR: {git_mirror}")
         
     except Exception as e:
         print(f"[ERROR] 获取配置失败: {config_url} - {e}", file=sys.stderr)

backend/apps/common/prefect_django_setup.py

@@ -16,6 +16,7 @@ def setup_django_for_prefect():
     1. 添加项目根目录到 Python 路径
     2. 设置 DJANGO_SETTINGS_MODULE 环境变量
     3. 调用 django.setup() 初始化 Django
+    4. 关闭旧的数据库连接，确保使用新连接
     
     使用方式：
         from apps.common.prefect_django_setup import setup_django_for_prefect
@@ -36,6 +37,25 @@ def setup_django_for_prefect():
     # 初始化 Django
     import django
     django.setup()
+    
+    # 关闭所有旧的数据库连接，确保 Worker 进程使用新连接
+    # 解决 "server closed the connection unexpectedly" 问题
+    from django.db import connections
+    connections.close_all()
+
+
+def close_old_db_connections():
+    """
+    关闭旧的数据库连接
+    
+    在长时间运行的任务中调用此函数，可以确保使用有效的数据库连接。
+    适用于：
+    - Flow 开始前
+    - Task 开始前
+    - 长时间空闲后恢复操作前
+    """
+    from django.db import connections
+    connections.close_all()
 
 
 # 自动执行初始化（导入即生效）

backend/apps/common/services/__init__.py

@@ -3,8 +3,13 @@
 
 提供系统级别的公共服务，包括：
 - SystemLogService: 系统日志读取服务
+
+注意：FilterService 已移至 apps.common.utils.filter_utils
+推荐使用: from apps.common.utils.filter_utils import apply_filters
 """
 
 from .system_log_service import SystemLogService
 
-__all__ = ['SystemLogService']
+__all__ = [
+    'SystemLogService',
+]

backend/apps/common/services/system_log_service.py

@@ -21,8 +21,8 @@ class SystemLogService:
     """
     
     def __init__(self):
-        # 日志文件路径（容器内路径，通过 volume 挂载到宿主机 /opt/xingrin/logs）
-        self.log_file = "/app/backend/logs/xingrin.log"
+        # 日志文件路径（统一使用 /opt/xingrin/logs）
+        self.log_file = "/opt/xingrin/logs/xingrin.log"
         self.default_lines = 200        # 默认返回行数
         self.max_lines = 10000          # 最大返回行数限制
         self.timeout_seconds = 3        # tail 命令超时时间

backend/apps/common/utils/__init__.py

@@ -0,0 +1,30 @@
+"""Common utilities"""
+
+from .dedup import deduplicate_for_bulk, get_unique_fields
+from .hash import (
+    calc_file_sha256,
+    calc_stream_sha256,
+    safe_calc_file_sha256,
+    is_file_hash_match,
+)
+from .csv_utils import (
+    generate_csv_rows,
+    format_list_field,
+    format_datetime,
+    UTF8_BOM,
+)
+from .git_proxy import get_git_proxy_url
+
+__all__ = [
+    'deduplicate_for_bulk',
+    'get_unique_fields',
+    'calc_file_sha256',
+    'calc_stream_sha256',
+    'safe_calc_file_sha256',
+    'is_file_hash_match',
+    'generate_csv_rows',
+    'format_list_field',
+    'format_datetime',
+    'UTF8_BOM',
+    'get_git_proxy_url',
+]

backend/apps/common/utils/csv_utils.py

@@ -0,0 +1,116 @@
+"""CSV 导出工具模块
+
+提供流式 CSV 生成功能，支持：
+- UTF-8 BOM（Excel 兼容）
+- RFC 4180 规范转义
+- 流式生成（内存友好）
+"""
+
+import csv
+import io
+from datetime import datetime
+from typing import Iterator, Dict, Any, List, Callable, Optional
+
+# UTF-8 BOM，确保 Excel 正确识别编码
+UTF8_BOM = '\ufeff'
+
+
+def generate_csv_rows(
+    data_iterator: Iterator[Dict[str, Any]],
+    headers: List[str],
+    field_formatters: Optional[Dict[str, Callable]] = None
+) -> Iterator[str]:
+    """
+    流式生成 CSV 行
+    
+    Args:
+        data_iterator: 数据迭代器，每个元素是一个字典
+        headers: CSV 表头列表
+        field_formatters: 字段格式化函数字典，key 为字段名，value 为格式化函数
+    
+    Yields:
+        CSV 行字符串（包含换行符）
+    
+    Example:
+        >>> data = [{'ip': '192.168.1.1', 'hosts': ['a.com', 'b.com']}]
+        >>> headers = ['ip', 'hosts']
+        >>> formatters = {'hosts': format_list_field}
+        >>> for row in generate_csv_rows(iter(data), headers, formatters):
+        ...     print(row, end='')
+    """
+    # 输出 BOM + 表头
+    output = io.StringIO()
+    writer = csv.writer(output, quoting=csv.QUOTE_MINIMAL)
+    writer.writerow(headers)
+    yield UTF8_BOM + output.getvalue()
+    
+    # 输出数据行
+    for row_data in data_iterator:
+        output = io.StringIO()
+        writer = csv.writer(output, quoting=csv.QUOTE_MINIMAL)
+        
+        row = []
+        for header in headers:
+            value = row_data.get(header, '')
+            if field_formatters and header in field_formatters:
+                value = field_formatters[header](value)
+            row.append(value if value is not None else '')
+        
+        writer.writerow(row)
+        yield output.getvalue()
+
+
+def format_list_field(values: List, separator: str = ';') -> str:
+    """
+    将列表字段格式化为分号分隔的字符串
+    
+    Args:
+        values: 值列表
+        separator: 分隔符，默认为分号
+    
+    Returns:
+        分隔符连接的字符串
+    
+    Example:
+        >>> format_list_field(['a.com', 'b.com'])
+        'a.com;b.com'
+        >>> format_list_field([80, 443])
+        '80;443'
+        >>> format_list_field([])
+        ''
+        >>> format_list_field(None)
+        ''
+    """
+    if not values:
+        return ''
+    return separator.join(str(v) for v in values)
+
+
+def format_datetime(dt: Optional[datetime]) -> str:
+    """
+    格式化日期时间为字符串（转换为本地时区）
+    
+    Args:
+        dt: datetime 对象或 None
+    
+    Returns:
+        格式化的日期时间字符串，格式为 YYYY-MM-DD HH:MM:SS（本地时区）
+    
+    Example:
+        >>> from datetime import datetime
+        >>> format_datetime(datetime(2024, 1, 15, 10, 30, 0))
+        '2024-01-15 10:30:00'
+        >>> format_datetime(None)
+        ''
+    """
+    if dt is None:
+        return ''
+    if isinstance(dt, str):
+        return dt
+    
+    # 转换为本地时区（从 Django settings 获取）
+    from django.utils import timezone
+    if timezone.is_aware(dt):
+        dt = timezone.localtime(dt)
+    
+    return dt.strftime('%Y-%m-%d %H:%M:%S')

backend/apps/common/utils/dedup.py

@@ -0,0 +1,101 @@
+"""
+批量数据去重工具
+
+用于 bulk_create 前的批次内去重，避免 PostgreSQL ON CONFLICT 错误。
+自动从 Django 模型读取唯一约束字段，无需手动指定。
+"""
+
+import logging
+from typing import List, TypeVar, Tuple, Optional
+
+from django.db import models
+
+logger = logging.getLogger(__name__)
+
+T = TypeVar('T')
+
+
+def get_unique_fields(model: type[models.Model]) -> Optional[Tuple[str, ...]]:
+    """
+    从 Django 模型获取唯一约束字段
+    
+    按优先级查找：
+    1. Meta.constraints 中的 UniqueConstraint
+    2. Meta.unique_together
+    
+    Args:
+        model: Django 模型类
+        
+    Returns:
+        唯一约束字段元组，如果没有则返回 None
+    """
+    meta = model._meta
+    
+    # 1. 优先查找 UniqueConstraint
+    for constraint in getattr(meta, 'constraints', []):
+        if isinstance(constraint, models.UniqueConstraint):
+            # 跳过条件约束（partial unique）
+            if getattr(constraint, 'condition', None) is None:
+                return tuple(constraint.fields)
+    
+    # 2. 回退到 unique_together
+    unique_together = getattr(meta, 'unique_together', None)
+    if unique_together:
+        # unique_together 可能是 (('a', 'b'),) 或 ('a', 'b')
+        if unique_together and isinstance(unique_together[0], (list, tuple)):
+            return tuple(unique_together[0])
+        return tuple(unique_together)
+    
+    return None
+
+
+def deduplicate_for_bulk(items: List[T], model: type[models.Model]) -> List[T]:
+    """
+    根据模型唯一约束对数据去重
+    
+    自动从模型读取唯一约束字段，生成去重 key。
+    保留最后一条记录（后面的数据通常是更新的）。
+    
+    Args:
+        items: 待去重的数据列表（DTO 或 Model 对象）
+        model: Django 模型类（用于读取唯一约束）
+        
+    Returns:
+        去重后的数据列表
+        
+    Example:
+        # 自动从 Endpoint 模型读取唯一约束 (url, target)
+        unique_items = deduplicate_for_bulk(items, Endpoint)
+    """
+    if not items:
+        return items
+    
+    unique_fields = get_unique_fields(model)
+    if unique_fields is None:
+        # 模型没有唯一约束，无需去重
+        logger.debug(f"{model.__name__} 没有唯一约束，跳过去重")
+        return items
+    
+    # 处理外键字段名（target -> target_id）
+    def make_key(item: T) -> tuple:
+        key_parts = []
+        for field in unique_fields:
+            # 尝试 field_id（外键）和 field 两种形式
+            value = getattr(item, f'{field}_id', None)
+            if value is None:
+                value = getattr(item, field, None)
+            key_parts.append(value)
+        return tuple(key_parts)
+    
+    # 使用字典去重，保留最后一条
+    seen = {}
+    for item in items:
+        key = make_key(item)
+        seen[key] = item
+    
+    unique_items = list(seen.values())
+    
+    if len(unique_items) < len(items):
+        logger.debug(f"{model.__name__} 去重: {len(items)} -> {len(unique_items)} 条")
+    
+    return unique_items

backend/apps/common/utils/filter_utils.py

@@ -0,0 +1,281 @@
+"""智能过滤工具 - 通用查询语法解析和 Django ORM 查询构建
+
+支持的语法：
+- field="value"     模糊匹配（包含）
+- field=="value"    精确匹配
+- field!="value"    不等于
+
+逻辑运算符：
+- AND: && 或 and 或 空格（默认）
+- OR:  || 或 or
+
+示例：
+    type="xss" || type="sqli"           # OR
+    type="xss" or type="sqli"           # OR（等价）
+    severity="high" && source="nuclei"  # AND
+    severity="high" source="nuclei"     # AND（空格默认为 AND）
+    severity="high" and source="nuclei" # AND（等价）
+
+使用示例：
+    from apps.common.utils.filter_utils import apply_filters
+    
+    field_mapping = {'ip': 'ip', 'port': 'port', 'host': 'host'}
+    queryset = apply_filters(queryset, 'ip="192" || port="80"', field_mapping)
+"""
+
+import re
+import logging
+from dataclasses import dataclass
+from typing import List, Dict, Optional, Union
+from enum import Enum
+
+from django.db.models import QuerySet, Q
+
+logger = logging.getLogger(__name__)
+
+
+class LogicalOp(Enum):
+    """逻辑运算符"""
+    AND = 'AND'
+    OR = 'OR'
+
+
+@dataclass
+class ParsedFilter:
+    """解析后的过滤条件"""
+    field: str      # 字段名
+    operator: str   # 操作符: '=', '==', '!='
+    value: str      # 原始值
+
+
+@dataclass
+class FilterGroup:
+    """过滤条件组（带逻辑运算符）"""
+    filter: ParsedFilter
+    logical_op: LogicalOp  # 与前一个条件的逻辑关系
+
+
+class QueryParser:
+    """查询语法解析器
+    
+    支持 ||/or (OR) 和 &&/and/空格 (AND) 逻辑运算符
+    """
+    
+    # 正则匹配: field="value", field=="value", field!="value"
+    FILTER_PATTERN = re.compile(r'(\w+)(==|!=|=)"([^"]*)"')
+    
+    # 逻辑运算符模式（带空格）
+    OR_PATTERN = re.compile(r'\s*(\|\||(?<![a-zA-Z])or(?![a-zA-Z]))\s*', re.IGNORECASE)
+    AND_PATTERN = re.compile(r'\s*(&&|(?<![a-zA-Z])and(?![a-zA-Z]))\s*', re.IGNORECASE)
+    
+    @classmethod
+    def parse(cls, query_string: str) -> List[FilterGroup]:
+        """解析查询语法字符串
+        
+        Args:
+            query_string: 查询语法字符串
+        
+        Returns:
+            解析后的过滤条件组列表
+        
+        Examples:
+            >>> QueryParser.parse('type="xss" || type="sqli"')
+            [FilterGroup(filter=..., logical_op=AND),  # 第一个默认 AND
+             FilterGroup(filter=..., logical_op=OR)]
+        """
+        if not query_string or not query_string.strip():
+            return []
+        
+        # 标准化逻辑运算符
+        # 先处理 || 和 or -> __OR__
+        normalized = cls.OR_PATTERN.sub(' __OR__ ', query_string)
+        # 再处理 && 和 and -> __AND__
+        normalized = cls.AND_PATTERN.sub(' __AND__ ', normalized)
+        
+        # 分词：按空格分割，保留逻辑运算符标记
+        tokens = normalized.split()
+        
+        groups = []
+        pending_op = LogicalOp.AND  # 默认 AND
+        
+        for token in tokens:
+            if token == '__OR__':
+                pending_op = LogicalOp.OR
+            elif token == '__AND__':
+                pending_op = LogicalOp.AND
+            else:
+                # 尝试解析为过滤条件
+                match = cls.FILTER_PATTERN.match(token)
+                if match:
+                    field, operator, value = match.groups()
+                    groups.append(FilterGroup(
+                        filter=ParsedFilter(
+                            field=field.lower(),
+                            operator=operator,
+                            value=value
+                        ),
+                        logical_op=pending_op if groups else LogicalOp.AND  # 第一个条件默认 AND
+                    ))
+                    pending_op = LogicalOp.AND  # 重置为默认 AND
+        
+        return groups
+
+
+class QueryBuilder:
+    """Django ORM 查询构建器
+    
+    将解析后的过滤条件转换为 Django ORM 查询，支持 AND/OR 逻辑
+    """
+    
+    @classmethod
+    def build_query(
+        cls,
+        queryset: QuerySet,
+        filter_groups: List[FilterGroup],
+        field_mapping: Dict[str, str],
+        json_array_fields: List[str] = None
+    ) -> QuerySet:
+        """构建 Django ORM 查询
+        
+        Args:
+            queryset: Django QuerySet
+            filter_groups: 解析后的过滤条件组列表
+            field_mapping: 字段映射
+            json_array_fields: JSON 数组字段列表（使用 __contains 查询）
+        
+        Returns:
+            过滤后的 QuerySet
+        """
+        if not filter_groups:
+            return queryset
+        
+        json_array_fields = json_array_fields or []
+        
+        # 构建 Q 对象
+        combined_q = None
+        
+        for group in filter_groups:
+            f = group.filter
+            
+            # 字段映射
+            db_field = field_mapping.get(f.field)
+            if not db_field:
+                logger.debug(f"忽略未知字段: {f.field}")
+                continue
+            
+            # 判断是否为 JSON 数组字段
+            is_json_array = db_field in json_array_fields
+            
+            # 构建单个条件的 Q 对象
+            q = cls._build_single_q(db_field, f.operator, f.value, is_json_array)
+            if q is None:
+                continue
+            
+            # 组合 Q 对象
+            if combined_q is None:
+                combined_q = q
+            elif group.logical_op == LogicalOp.OR:
+                combined_q = combined_q | q
+            else:  # AND
+                combined_q = combined_q & q
+        
+        if combined_q is not None:
+            return queryset.filter(combined_q)
+        return queryset
+    
+    @classmethod
+    def _build_single_q(cls, field: str, operator: str, value: str, is_json_array: bool = False) -> Optional[Q]:
+        """构建单个条件的 Q 对象"""
+        if is_json_array:
+            # JSON 数组字段使用 __contains 查询
+            return Q(**{f'{field}__contains': [value]})
+        
+        if operator == '!=':
+            return cls._build_not_equal_q(field, value)
+        elif operator == '==':
+            return cls._build_exact_q(field, value)
+        else:  # '='
+            return cls._build_fuzzy_q(field, value)
+    
+    @classmethod
+    def _try_convert_to_int(cls, value: str) -> Optional[int]:
+        """尝试将值转换为整数"""
+        try:
+            return int(value.strip())
+        except (ValueError, TypeError):
+            return None
+    
+    @classmethod
+    def _build_fuzzy_q(cls, field: str, value: str) -> Q:
+        """模糊匹配: 包含"""
+        return Q(**{f'{field}__icontains': value})
+    
+    @classmethod
+    def _build_exact_q(cls, field: str, value: str) -> Q:
+        """精确匹配"""
+        int_val = cls._try_convert_to_int(value)
+        if int_val is not None:
+            return Q(**{f'{field}__exact': int_val})
+        return Q(**{f'{field}__exact': value})
+    
+    @classmethod
+    def _build_not_equal_q(cls, field: str, value: str) -> Q:
+        """不等于"""
+        int_val = cls._try_convert_to_int(value)
+        if int_val is not None:
+            return ~Q(**{f'{field}__exact': int_val})
+        return ~Q(**{f'{field}__exact': value})
+
+
+def apply_filters(
+    queryset: QuerySet,
+    query_string: str,
+    field_mapping: Dict[str, str],
+    json_array_fields: List[str] = None
+) -> QuerySet:
+    """应用过滤条件到 QuerySet
+    
+    Args:
+        queryset: Django QuerySet
+        query_string: 查询语法字符串
+        field_mapping: 字段映射
+        json_array_fields: JSON 数组字段列表（使用 __contains 查询）
+    
+    Returns:
+        过滤后的 QuerySet
+    
+    Examples:
+        # OR 查询
+        apply_filters(qs, 'type="xss" || type="sqli"', mapping)
+        apply_filters(qs, 'type="xss" or type="sqli"', mapping)
+        
+        # AND 查询
+        apply_filters(qs, 'severity="high" && source="nuclei"', mapping)
+        apply_filters(qs, 'severity="high" source="nuclei"', mapping)
+        
+        # 混合查询
+        apply_filters(qs, 'type="xss" || type="sqli" && severity="high"', mapping)
+        
+        # JSON 数组字段查询
+        apply_filters(qs, 'implies="PHP"', mapping, json_array_fields=['implies'])
+    """
+    if not query_string or not query_string.strip():
+        return queryset
+    
+    try:
+        filter_groups = QueryParser.parse(query_string)
+        if not filter_groups:
+            logger.debug(f"未解析到有效过滤条件: {query_string}")
+            return queryset
+        
+        logger.debug(f"解析过滤条件: {filter_groups}")
+        return QueryBuilder.build_query(
+            queryset, 
+            filter_groups, 
+            field_mapping,
+            json_array_fields=json_array_fields
+        )
+    
+    except Exception as e:
+        logger.warning(f"过滤解析错误: {e}, query: {query_string}")
+        return queryset  # 静默降级

backend/apps/common/utils/git_proxy.py

@@ -0,0 +1,39 @@
+"""Git proxy utilities for URL acceleration."""
+
+import os
+from urllib.parse import urlparse
+
+
+def get_git_proxy_url(original_url: str) -> str:
+    """
+    Convert Git repository URL to proxy format for acceleration.
+    
+    Supports multiple mirror services (standard format):
+    - gh-proxy.org: https://gh-proxy.org/https://github.com/user/repo.git
+    - ghproxy.com: https://ghproxy.com/https://github.com/user/repo.git
+    - mirror.ghproxy.com: https://mirror.ghproxy.com/https://github.com/user/repo.git
+    - ghps.cc: https://ghps.cc/https://github.com/user/repo.git
+    
+    Args:
+        original_url: Original repository URL, e.g., https://github.com/user/repo.git
+        
+    Returns:
+        Converted URL based on GIT_MIRROR setting.
+        If GIT_MIRROR is not set, returns the original URL unchanged.
+    """
+    git_mirror = os.getenv("GIT_MIRROR", "").strip()
+    if not git_mirror:
+        return original_url
+    
+    # Remove trailing slash from mirror URL if present
+    git_mirror = git_mirror.rstrip("/")
+    
+    parsed = urlparse(original_url)
+    host = parsed.netloc.lower()
+    
+    # Only support GitHub for now
+    if "github.com" not in host:
+        return original_url
+    
+    # Standard format: https://mirror.example.com/https://github.com/user/repo.git
+    return f"{git_mirror}/{original_url}"

backend/apps/common/utils/hash.py

@@ -7,7 +7,6 @@
 
 import hashlib
 import logging
-from pathlib import Path
 from typing import Optional, BinaryIO
 
 logger = logging.getLogger(__name__)
@@ -91,11 +90,3 @@ def is_file_hash_match(file_path: str, expected_hash: str) -> bool:
         return False
 
     return actual_hash.lower() == expected_hash.lower()
-
-
-__all__ = [
-    "calc_file_sha256",
-    "calc_stream_sha256",
-    "safe_calc_file_sha256",
-    "is_file_hash_match",
-]

backend/apps/common/validators.py

@@ -1,6 +1,8 @@
-"""域名、IP、端口和目标验证工具函数"""
+"""域名、IP、端口、URL 和目标验证工具函数"""
 import ipaddress
 import logging
+from urllib.parse import urlparse
+
 import validators
 
 logger = logging.getLogger(__name__)
@@ -25,6 +27,21 @@ def validate_domain(domain: str) -> None:
         raise ValueError(f"域名格式无效: {domain}")
 
 
+def is_valid_domain(domain: str) -> bool:
+    """
+    判断是否为有效域名（不抛异常）
+    
+    Args:
+        domain: 域名字符串
+        
+    Returns:
+        bool: 是否为有效域名
+    """
+    if not domain or len(domain) > 253:
+        return False
+    return bool(validators.domain(domain))
+
+
 def validate_ip(ip: str) -> None:
     """
     验证 IP 地址格式（支持 IPv4 和 IPv6）
@@ -44,6 +61,25 @@ def validate_ip(ip: str) -> None:
         raise ValueError(f"IP 地址格式无效: {ip}")
 
 
+def is_valid_ip(ip: str) -> bool:
+    """
+    判断是否为有效 IP 地址（不抛异常）
+    
+    Args:
+        ip: IP 地址字符串
+        
+    Returns:
+        bool: 是否为有效 IP 地址
+    """
+    if not ip:
+        return False
+    try:
+        ipaddress.ip_address(ip)
+        return True
+    except ValueError:
+        return False
+
+
 def validate_cidr(cidr: str) -> None:
     """
     验证 CIDR 格式（支持 IPv4 和 IPv6）
@@ -140,3 +176,136 @@ def validate_port(port: any) -> tuple[bool, int | None]:
     except (ValueError, TypeError):
         logger.warning("端口号格式错误，无法转换为整数: %s", port)
         return False, None
+
+
+# ==================== URL 验证函数 ====================
+
+def validate_url(url: str) -> None:
+    """
+    验证 URL 格式，必须包含 scheme（http:// 或 https://）
+    
+    Args:
+        url: URL 字符串
+        
+    Raises:
+        ValueError: URL 格式无效或缺少 scheme
+    """
+    if not url:
+        raise ValueError("URL 不能为空")
+    
+    # 检查是否包含 scheme
+    if not url.startswith('http://') and not url.startswith('https://'):
+        raise ValueError("URL 必须包含协议（http:// 或 https://）")
+    
+    try:
+        parsed = urlparse(url)
+        if not parsed.hostname:
+            raise ValueError("URL 必须包含主机名")
+    except Exception:
+        raise ValueError(f"URL 格式无效: {url}")
+
+
+def is_valid_url(url: str, max_length: int = 2000) -> bool:
+    """
+    判断是否为有效 URL（不抛异常）
+    
+    Args:
+        url: URL 字符串
+        max_length: URL 最大长度，默认 2000
+        
+    Returns:
+        bool: 是否为有效 URL
+    """
+    if not url or len(url) > max_length:
+        return False
+    try:
+        validate_url(url)
+        return True
+    except ValueError:
+        return False
+
+
+def is_url_match_target(url: str, target_name: str, target_type: str) -> bool:
+    """
+    判断 URL 是否匹配目标
+    
+    Args:
+        url: URL 字符串
+        target_name: 目标名称（域名、IP 或 CIDR）
+        target_type: 目标类型 ('domain', 'ip', 'cidr')
+        
+    Returns:
+        bool: 是否匹配
+    """
+    try:
+        parsed = urlparse(url)
+        hostname = parsed.hostname
+        if not hostname:
+            return False
+        
+        hostname = hostname.lower()
+        target_name = target_name.lower()
+        
+        if target_type == 'domain':
+            # 域名类型：hostname 等于 target_name 或以 .target_name 结尾
+            return hostname == target_name or hostname.endswith('.' + target_name)
+        
+        elif target_type == 'ip':
+            # IP 类型：hostname 必须完全等于 target_name
+            return hostname == target_name
+        
+        elif target_type == 'cidr':
+            # CIDR 类型：hostname 必须是 IP 且在 CIDR 范围内
+            try:
+                ip = ipaddress.ip_address(hostname)
+                network = ipaddress.ip_network(target_name, strict=False)
+                return ip in network
+            except ValueError:
+                # hostname 不是有效 IP
+                return False
+        
+        return False
+    except Exception:
+        return False
+
+
+def detect_input_type(input_str: str) -> str:
+    """
+    检测输入类型（用于快速扫描输入解析）
+    
+    Args:
+        input_str: 输入字符串（应该已经 strip）
+        
+    Returns:
+        str: 输入类型 ('url', 'domain', 'ip', 'cidr')
+    """
+    if not input_str:
+        raise ValueError("输入不能为空")
+    
+    # 1. 包含 :// 一定是 URL
+    if '://' in input_str:
+        return 'url'
+    
+    # 2. 包含 / 需要判断是 CIDR 还是 URL（缺少 scheme）
+    if '/' in input_str:
+        # CIDR 格式: IP/prefix，如 10.0.0.0/8
+        parts = input_str.split('/')
+        if len(parts) == 2:
+            ip_part, prefix_part = parts
+            # 如果斜杠后是纯数字且在 0-32 范围内，检查是否是 CIDR
+            if prefix_part.isdigit() and 0 <= int(prefix_part) <= 32:
+                ip_parts = ip_part.split('.')
+                if len(ip_parts) == 4 and all(p.isdigit() for p in ip_parts):
+                    return 'cidr'
+        # 不是 CIDR，视为 URL（缺少 scheme，后续验证会报错）
+        return 'url'
+    
+    # 3. 检查是否是 IP 地址
+    try:
+        ipaddress.ip_address(input_str)
+        return 'ip'
+    except ValueError:
+        pass
+    
+    # 4. 默认为域名
+    return 'domain'

backend/apps/engine/consumers/worker_deploy_consumer.py

@@ -242,8 +242,9 @@ class WorkerDeployConsumer(AsyncWebsocketConsumer):
             return
 
         # 远程 Worker 通过 nginx HTTPS 访问（nginx 反代到后端 8888）
-        # 使用 https://{PUBLIC_HOST} 而不是直连 8888 端口
-        heartbeat_api_url = f"https://{public_host}"  # 基础 URL，agent 会加 /api/...
+        # 使用 https://{PUBLIC_HOST}:{PUBLIC_PORT} 而不是直连 8888 端口
+        public_port = getattr(settings, 'PUBLIC_PORT', '8083')
+        heartbeat_api_url = f"https://{public_host}:{public_port}"
 
         session_name = f'xingrin_deploy_{self.worker_id}'
         remote_script_path = '/tmp/xingrin_deploy.sh'

backend/apps/engine/management/commands/init_fingerprints.py

@@ -0,0 +1,160 @@
+"""初始化内置指纹库
+
+- EHole 指纹: ehole.json -> 导入到数据库
+- Goby 指纹: goby.json -> 导入到数据库
+- Wappalyzer 指纹: wappalyzer.json -> 导入到数据库
+
+可重复执行：如果数据库已有数据则跳过，只在空库时导入。
+"""
+
+import json
+import logging
+from pathlib import Path
+
+from django.conf import settings
+from django.core.management.base import BaseCommand
+
+from apps.engine.models import EholeFingerprint, GobyFingerprint, WappalyzerFingerprint
+from apps.engine.services.fingerprints import (
+    EholeFingerprintService,
+    GobyFingerprintService,
+    WappalyzerFingerprintService,
+)
+
+
+logger = logging.getLogger(__name__)
+
+
+# 内置指纹配置
+DEFAULT_FINGERPRINTS = [
+    {
+        "type": "ehole",
+        "filename": "ehole.json",
+        "model": EholeFingerprint,
+        "service": EholeFingerprintService,
+        "data_key": "fingerprint",  # JSON 中指纹数组的 key
+    },
+    {
+        "type": "goby",
+        "filename": "goby.json",
+        "model": GobyFingerprint,
+        "service": GobyFingerprintService,
+        "data_key": None,  # Goby 是数组格式，直接使用整个 JSON
+    },
+    {
+        "type": "wappalyzer",
+        "filename": "wappalyzer.json",
+        "model": WappalyzerFingerprint,
+        "service": WappalyzerFingerprintService,
+        "data_key": "apps",  # Wappalyzer 使用 apps 对象
+    },
+]
+
+
+class Command(BaseCommand):
+    help = "初始化内置指纹库"
+
+    def handle(self, *args, **options):
+        project_base = Path(settings.BASE_DIR).parent  # /app/backend -> /app
+        fingerprints_dir = project_base / "backend" / "fingerprints"
+
+        initialized = 0
+        skipped = 0
+        failed = 0
+
+        for item in DEFAULT_FINGERPRINTS:
+            fp_type = item["type"]
+            filename = item["filename"]
+            model = item["model"]
+            service_class = item["service"]
+            data_key = item["data_key"]
+
+            # 检查数据库是否已有数据
+            existing_count = model.objects.count()
+            if existing_count > 0:
+                self.stdout.write(self.style.SUCCESS(
+                    f"[{fp_type}] 数据库已有 {existing_count} 条记录，跳过初始化"
+                ))
+                skipped += 1
+                continue
+
+            # 查找源文件
+            src_path = fingerprints_dir / filename
+            if not src_path.exists():
+                self.stdout.write(self.style.WARNING(
+                    f"[{fp_type}] 未找到内置指纹文件: {src_path}，跳过"
+                ))
+                failed += 1
+                continue
+
+            # 读取并解析 JSON
+            try:
+                with open(src_path, "r", encoding="utf-8") as f:
+                    json_data = json.load(f)
+            except (json.JSONDecodeError, OSError) as exc:
+                self.stdout.write(self.style.ERROR(
+                    f"[{fp_type}] 读取指纹文件失败: {exc}"
+                ))
+                failed += 1
+                continue
+
+            # 提取指纹数据（根据不同格式处理）
+            fingerprints = self._extract_fingerprints(json_data, data_key, fp_type)
+            if not fingerprints:
+                self.stdout.write(self.style.WARNING(
+                    f"[{fp_type}] 指纹文件中没有有效数据，跳过"
+                ))
+                failed += 1
+                continue
+
+            # 使用 Service 批量导入
+            try:
+                service = service_class()
+                result = service.batch_create_fingerprints(fingerprints)
+                created = result.get("created", 0)
+                failed_count = result.get("failed", 0)
+
+                self.stdout.write(self.style.SUCCESS(
+                    f"[{fp_type}] 导入成功: 创建 {created} 条，失败 {failed_count} 条"
+                ))
+                initialized += 1
+            except Exception as exc:
+                self.stdout.write(self.style.ERROR(
+                    f"[{fp_type}] 导入失败: {exc}"
+                ))
+                failed += 1
+                continue
+
+        self.stdout.write(self.style.SUCCESS(
+            f"指纹初始化完成: 成功 {initialized}, 已存在跳过 {skipped}, 失败 {failed}"
+        ))
+
+    def _extract_fingerprints(self, json_data, data_key, fp_type):
+        """
+        根据不同格式提取指纹数据，兼容数组和对象两种格式
+        
+        支持的格式：
+        - 数组格式: [...] 或 {"key": [...]}
+        - 对象格式: {...} 或 {"key": {...}} -> 转换为 [{"name": k, ...v}]
+        """
+        # 获取目标数据
+        if data_key is None:
+            # 直接使用整个 JSON
+            target = json_data
+        else:
+            # 从指定 key 获取，支持多个可能的 key（如 apps/technologies）
+            if data_key == "apps":
+                target = json_data.get("apps") or json_data.get("technologies") or {}
+            else:
+                target = json_data.get(data_key, [])
+        
+        # 根据数据类型处理
+        if isinstance(target, list):
+            # 已经是数组格式，直接返回
+            return target
+        elif isinstance(target, dict):
+            # 对象格式，转换为数组 [{"name": key, ...value}]
+            return [{"name": name, **data} if isinstance(data, dict) else {"name": name}
+                    for name, data in target.items()]
+        
+        return []

backend/apps/engine/management/commands/init_nuclei_templates.py

@@ -3,12 +3,17 @@
 项目安装后执行此命令，自动创建官方模板仓库记录。
 
 使用方式：
-    python manage.py init_nuclei_templates           # 只创建记录
+    python manage.py init_nuclei_templates           # 只创建记录（检测本地已有仓库）
     python manage.py init_nuclei_templates --sync    # 创建并同步（git clone）
 """
 
 import logging
+import subprocess
+from pathlib import Path
+
+from django.conf import settings
 from django.core.management.base import BaseCommand
+from django.utils import timezone
 
 from apps.engine.models import NucleiTemplateRepo
 from apps.engine.services import NucleiTemplateRepoService
@@ -26,6 +31,20 @@ DEFAULT_REPOS = [
 ]
 
 
+def get_local_commit_hash(local_path: Path) -> str:
+    """获取本地 Git 仓库的 commit hash"""
+    if not (local_path / ".git").is_dir():
+        return ""
+    result = subprocess.run(
+        ["git", "-C", str(local_path), "rev-parse", "HEAD"],
+        check=False,
+        stdout=subprocess.PIPE,
+        stderr=subprocess.PIPE,
+        text=True,
+    )
+    return result.stdout.strip() if result.returncode == 0 else ""
+
+
 class Command(BaseCommand):
     help = "初始化 Nuclei 模板仓库（创建官方模板仓库记录）"
 
@@ -46,6 +65,8 @@ class Command(BaseCommand):
         force = options.get("force", False)
 
         service = NucleiTemplateRepoService()
+        base_dir = Path(getattr(settings, "NUCLEI_TEMPLATES_REPOS_BASE_DIR", "/opt/xingrin/nuclei-repos"))
+        
         created = 0
         skipped = 0
         synced = 0
@@ -87,20 +108,30 @@ class Command(BaseCommand):
 
             # 创建新仓库记录
             try:
+                # 检查本地是否已有仓库（由 install.sh 预下载）
+                local_path = base_dir / name
+                local_commit = get_local_commit_hash(local_path)
+                
                 repo = NucleiTemplateRepo.objects.create(
                     name=name,
                     repo_url=repo_url,
+                    local_path=str(local_path) if local_commit else "",
+                    commit_hash=local_commit,
+                    last_synced_at=timezone.now() if local_commit else None,
                 )
-                self.stdout.write(self.style.SUCCESS(
-                    f"[{name}] 创建成功: id={repo.id}"
-                ))
+                
+                if local_commit:
+                    self.stdout.write(self.style.SUCCESS(
+                        f"[{name}] 创建成功（检测到本地仓库）: commit={local_commit[:8]}"
+                    ))
+                else:
+                    self.stdout.write(self.style.SUCCESS(
+                        f"[{name}] 创建成功: id={repo.id}"
+                    ))
                 created += 1
 
-                # 初始化本地路径
-                service.ensure_local_path(repo)
-
-                # 如果需要同步
-                if do_sync:
+                # 如果本地没有仓库且需要同步
+                if not local_commit and do_sync:
                     try:
                         self.stdout.write(self.style.WARNING(
                             f"[{name}] 正在同步（首次可能需要几分钟）..."

backend/apps/engine/management/commands/init_wordlists.py

@@ -1,7 +1,8 @@
 """初始化所有内置字典 Wordlist 记录
 
-- 目录扫描默认字典: dir_default.txt -> /app/backend/wordlist/dir_default.txt
-- 子域名爆破默认字典: subdomains-top1million-110000.txt -> /app/backend/wordlist/subdomains-top1million-110000.txt
+内置字典从镜像内 /app/backend/wordlist/ 复制到运行时目录 /opt/xingrin/wordlists/：
+- 目录扫描默认字典: dir_default.txt
+- 子域名爆破默认字典: subdomains-top1million-110000.txt
 
 可重复执行：如果已存在同名记录且文件有效则跳过，只在缺失或文件丢失时创建/修复。
 """
@@ -13,7 +14,7 @@ from pathlib import Path
 from django.conf import settings
 from django.core.management.base import BaseCommand
 
-from apps.common.hash_utils import safe_calc_file_sha256
+from apps.common.utils import safe_calc_file_sha256
 from apps.engine.models import Wordlist
 
 

backend/apps/engine/models/__init__.py

@@ -0,0 +1,19 @@
+"""Engine Models
+
+导出所有 Engine 模块的 Models
+"""
+
+from .engine import WorkerNode, ScanEngine, Wordlist, NucleiTemplateRepo
+from .fingerprints import EholeFingerprint, GobyFingerprint, WappalyzerFingerprint
+
+__all__ = [
+    # 核心 Models
+    "WorkerNode",
+    "ScanEngine",
+    "Wordlist",
+    "NucleiTemplateRepo",
+    # 指纹 Models
+    "EholeFingerprint",
+    "GobyFingerprint",
+    "WappalyzerFingerprint",
+]

backend/apps/engine/models/engine.py

@@ -1,3 +1,8 @@
+"""Engine 模块核心 Models
+
+包含 WorkerNode, ScanEngine, Wordlist, NucleiTemplateRepo
+"""
+
 from django.db import models
 
 
@@ -78,6 +83,7 @@ class ScanEngine(models.Model):
         indexes = [
             models.Index(fields=['-created_at']),
         ]
+
     def __str__(self):
         return str(self.name or f'ScanEngine {self.id}')
 

backend/apps/engine/models/fingerprints.py

@@ -0,0 +1,108 @@
+"""指纹相关 Models
+
+包含 EHole、Goby、Wappalyzer 等指纹格式的数据模型
+"""
+
+from django.db import models
+
+
+class GobyFingerprint(models.Model):
+    """Goby 格式指纹规则
+    
+    Goby 使用逻辑表达式和规则数组进行匹配：
+    - logic: 逻辑表达式，如 "a||b", "(a&&b)||c"
+    - rule: 规则数组，每条规则包含 label, feature, is_equal
+    """
+    
+    name = models.CharField(max_length=300, unique=True, help_text='产品名称')
+    logic = models.CharField(max_length=500, help_text='逻辑表达式')
+    rule = models.JSONField(default=list, help_text='规则数组')
+    created_at = models.DateTimeField(auto_now_add=True)
+    
+    class Meta:
+        db_table = 'goby_fingerprint'
+        verbose_name = 'Goby 指纹'
+        verbose_name_plural = 'Goby 指纹'
+        ordering = ['-created_at']
+        indexes = [
+            models.Index(fields=['name']),
+            models.Index(fields=['logic']),
+            models.Index(fields=['-created_at']),
+        ]
+    
+    def __str__(self) -> str:
+        return f"{self.name} ({self.logic})"
+
+
+class EholeFingerprint(models.Model):
+    """EHole 格式指纹规则（字段与 ehole.json 一致）"""
+    
+    cms = models.CharField(max_length=200, help_text='产品/CMS名称')
+    method = models.CharField(max_length=200, default='keyword', help_text='匹配方式')
+    location = models.CharField(max_length=200, default='body', help_text='匹配位置')
+    keyword = models.JSONField(default=list, help_text='关键词列表')
+    is_important = models.BooleanField(default=False, help_text='是否重点资产')
+    type = models.CharField(max_length=100, blank=True, default='-', help_text='分类')
+    created_at = models.DateTimeField(auto_now_add=True)
+    
+    class Meta:
+        db_table = 'ehole_fingerprint'
+        verbose_name = 'EHole 指纹'
+        verbose_name_plural = 'EHole 指纹'
+        ordering = ['-created_at']
+        indexes = [
+            # 搜索过滤字段索引
+            models.Index(fields=['cms']),
+            models.Index(fields=['method']),
+            models.Index(fields=['location']),
+            models.Index(fields=['type']),
+            models.Index(fields=['is_important']),
+            # 排序字段索引
+            models.Index(fields=['-created_at']),
+        ]
+        constraints = [
+            # 唯一约束：cms + method + location 组合不能重复
+            models.UniqueConstraint(
+                fields=['cms', 'method', 'location'],
+                name='unique_ehole_fingerprint'
+            ),
+        ]
+    
+    def __str__(self) -> str:
+        return f"{self.cms} ({self.method}@{self.location})"
+
+
+class WappalyzerFingerprint(models.Model):
+    """Wappalyzer 格式指纹规则
+    
+    Wappalyzer 支持多种检测方式：cookies, headers, scriptSrc, js, meta, html 等
+    """
+    
+    name = models.CharField(max_length=300, unique=True, help_text='应用名称')
+    cats = models.JSONField(default=list, help_text='分类 ID 数组')
+    cookies = models.JSONField(default=dict, blank=True, help_text='Cookie 检测规则')
+    headers = models.JSONField(default=dict, blank=True, help_text='HTTP Header 检测规则')
+    script_src = models.JSONField(default=list, blank=True, help_text='脚本 URL 正则数组')
+    js = models.JSONField(default=list, blank=True, help_text='JavaScript 变量检测规则')
+    implies = models.JSONField(default=list, blank=True, help_text='依赖关系数组')
+    meta = models.JSONField(default=dict, blank=True, help_text='HTML meta 标签检测规则')
+    html = models.JSONField(default=list, blank=True, help_text='HTML 内容正则数组')
+    description = models.TextField(blank=True, default='', help_text='应用描述')
+    website = models.URLField(max_length=500, blank=True, default='', help_text='官网链接')
+    cpe = models.CharField(max_length=300, blank=True, default='', help_text='CPE 标识符')
+    created_at = models.DateTimeField(auto_now_add=True)
+    
+    class Meta:
+        db_table = 'wappalyzer_fingerprint'
+        verbose_name = 'Wappalyzer 指纹'
+        verbose_name_plural = 'Wappalyzer 指纹'
+        ordering = ['-created_at']
+        indexes = [
+            models.Index(fields=['name']),
+            models.Index(fields=['website']),
+            models.Index(fields=['cpe']),
+            models.Index(fields=['-created_at']),
+        ]
+    
+    def __str__(self) -> str:
+        return f"{self.name}"

backend/apps/engine/serializers/fingerprints/__init__.py

@@ -0,0 +1,14 @@
+"""指纹管理 Serializers
+
+导出所有指纹相关的 Serializer 类
+"""
+
+from .ehole import EholeFingerprintSerializer
+from .goby import GobyFingerprintSerializer
+from .wappalyzer import WappalyzerFingerprintSerializer
+
+__all__ = [
+    "EholeFingerprintSerializer",
+    "GobyFingerprintSerializer",
+    "WappalyzerFingerprintSerializer",
+]

backend/apps/engine/serializers/fingerprints/ehole.py

@@ -0,0 +1,27 @@
+"""EHole 指纹 Serializer"""
+
+from rest_framework import serializers
+
+from apps.engine.models import EholeFingerprint
+
+
+class EholeFingerprintSerializer(serializers.ModelSerializer):
+    """EHole 指纹序列化器"""
+    
+    class Meta:
+        model = EholeFingerprint
+        fields = ['id', 'cms', 'method', 'location', 'keyword', 
+                  'is_important', 'type', 'created_at']
+        read_only_fields = ['id', 'created_at']
+    
+    def validate_cms(self, value):
+        """校验 cms 字段"""
+        if not value or not value.strip():
+            raise serializers.ValidationError("cms 字段不能为空")
+        return value.strip()
+    
+    def validate_keyword(self, value):
+        """校验 keyword 字段"""
+        if not isinstance(value, list):
+            raise serializers.ValidationError("keyword 必须是数组")
+        return value

backend/apps/engine/serializers/fingerprints/goby.py

@@ -0,0 +1,26 @@
+"""Goby 指纹 Serializer"""
+
+from rest_framework import serializers
+
+from apps.engine.models import GobyFingerprint
+
+
+class GobyFingerprintSerializer(serializers.ModelSerializer):
+    """Goby 指纹序列化器"""
+    
+    class Meta:
+        model = GobyFingerprint
+        fields = ['id', 'name', 'logic', 'rule', 'created_at']
+        read_only_fields = ['id', 'created_at']
+    
+    def validate_name(self, value):
+        """校验 name 字段"""
+        if not value or not value.strip():
+            raise serializers.ValidationError("name 字段不能为空")
+        return value.strip()
+    
+    def validate_rule(self, value):
+        """校验 rule 字段"""
+        if not isinstance(value, list):
+            raise serializers.ValidationError("rule 必须是数组")
+        return value

backend/apps/engine/serializers/fingerprints/wappalyzer.py

@@ -0,0 +1,24 @@
+"""Wappalyzer 指纹 Serializer"""
+
+from rest_framework import serializers
+
+from apps.engine.models import WappalyzerFingerprint
+
+
+class WappalyzerFingerprintSerializer(serializers.ModelSerializer):
+    """Wappalyzer 指纹序列化器"""
+    
+    class Meta:
+        model = WappalyzerFingerprint
+        fields = [
+            'id', 'name', 'cats', 'cookies', 'headers', 'script_src',
+            'js', 'implies', 'meta', 'html', 'description', 'website',
+            'cpe', 'created_at'
+        ]
+        read_only_fields = ['id', 'created_at']
+    
+    def validate_name(self, value):
+        """校验 name 字段"""
+        if not value or not value.strip():
+            raise serializers.ValidationError("name 字段不能为空")
+        return value.strip()

backend/apps/engine/services/fingerprints/__init__.py

@@ -0,0 +1,16 @@
+"""指纹管理 Services
+
+导出所有指纹相关的 Service 类
+"""
+
+from .base import BaseFingerprintService
+from .ehole import EholeFingerprintService
+from .goby import GobyFingerprintService
+from .wappalyzer import WappalyzerFingerprintService
+
+__all__ = [
+    "BaseFingerprintService",
+    "EholeFingerprintService",
+    "GobyFingerprintService",
+    "WappalyzerFingerprintService",
+]

backend/apps/engine/services/fingerprints/base.py

@@ -0,0 +1,144 @@
+"""指纹管理基类 Service
+
+提供通用的批量操作和缓存逻辑，供 EHole/Goby/Wappalyzer 等子类继承
+"""
+
+import json
+import logging
+from typing import Any
+
+logger = logging.getLogger(__name__)
+
+
+class BaseFingerprintService:
+    """指纹管理基类 Service，提供通用的批量操作和缓存逻辑"""
+    
+    model = None  # 子类必须指定
+    BATCH_SIZE = 1000  # 每批处理数量
+    
+    def validate_fingerprint(self, item: dict) -> bool:
+        """
+        校验单条指纹，子类必须实现
+        
+        Args:
+            item: 单条指纹数据
+            
+        Returns:
+            bool: 是否有效
+        """
+        raise NotImplementedError("子类必须实现 validate_fingerprint 方法")
+    
+    def validate_fingerprints(self, raw_data: list) -> tuple[list, list]:
+        """
+        批量校验指纹数据
+        
+        Args:
+            raw_data: 原始指纹数据列表
+            
+        Returns:
+            tuple: (valid_items, invalid_items)
+        """
+        valid, invalid = [], []
+        for item in raw_data:
+            if self.validate_fingerprint(item):
+                valid.append(item)
+            else:
+                invalid.append(item)
+        return valid, invalid
+    
+    def to_model_data(self, item: dict) -> dict:
+        """
+        转换为 Model 字段，子类必须实现
+        
+        Args:
+            item: 原始指纹数据
+            
+        Returns:
+            dict: Model 字段数据
+        """
+        raise NotImplementedError("子类必须实现 to_model_data 方法")
+
+    def bulk_create(self, fingerprints: list) -> int:
+        """
+        批量创建指纹记录（已校验的数据）
+        
+        Args:
+            fingerprints: 已校验的指纹数据列表
+            
+        Returns:
+            int: 成功创建数量
+        """
+        if not fingerprints:
+            return 0
+        
+        objects = [self.model(**self.to_model_data(item)) for item in fingerprints]
+        created = self.model.objects.bulk_create(objects, ignore_conflicts=True)
+        return len(created)
+    
+    def batch_create_fingerprints(self, raw_data: list) -> dict:
+        """
+        完整流程：分批校验 + 批量创建
+        
+        Args:
+            raw_data: 原始指纹数据列表
+            
+        Returns:
+            dict: {'created': int, 'failed': int}
+        """
+        total_created = 0
+        total_failed = 0
+        
+        for i in range(0, len(raw_data), self.BATCH_SIZE):
+            batch = raw_data[i:i + self.BATCH_SIZE]
+            valid, invalid = self.validate_fingerprints(batch)
+            total_created += self.bulk_create(valid)
+            total_failed += len(invalid)
+        
+        logger.info(
+            "批量创建指纹完成: created=%d, failed=%d, total=%d",
+            total_created, total_failed, len(raw_data)
+        )
+        return {'created': total_created, 'failed': total_failed}
+    
+    def get_export_data(self) -> dict:
+        """
+        获取导出数据，子类必须实现
+        
+        Returns:
+            dict: 导出的 JSON 数据
+        """
+        raise NotImplementedError("子类必须实现 get_export_data 方法")
+    
+    def export_to_file(self, output_path: str) -> int:
+        """
+        导出所有指纹到 JSON 文件
+        
+        Args:
+            output_path: 输出文件路径
+            
+        Returns:
+            int: 导出的指纹数量
+        """
+        data = self.get_export_data()
+        with open(output_path, 'w', encoding='utf-8') as f:
+            json.dump(data, f, ensure_ascii=False)
+        count = len(data.get('fingerprint', []))
+        logger.info("导出指纹文件: %s, 数量: %d", output_path, count)
+        return count
+    
+    def get_fingerprint_version(self) -> str:
+        """
+        获取指纹库版本标识（用于缓存校验）
+        
+        Returns:
+            str: 版本标识，格式 "{count}_{latest_timestamp}"
+        
+        版本变化场景：
+        - 新增记录 → count 变化
+        - 删除记录 → count 变化
+        - 清空全部 → count 变为 0
+        """
+        count = self.model.objects.count()
+        latest = self.model.objects.order_by('-created_at').first()
+        latest_ts = int(latest.created_at.timestamp()) if latest else 0
+        return f"{count}_{latest_ts}"

backend/apps/engine/services/fingerprints/ehole.py

@@ -0,0 +1,84 @@
+"""EHole 指纹管理 Service
+
+实现 EHole 格式指纹的校验、转换和导出逻辑
+"""
+
+from apps.engine.models import EholeFingerprint
+from .base import BaseFingerprintService
+
+
+class EholeFingerprintService(BaseFingerprintService):
+    """EHole 指纹管理服务（继承基类，实现 EHole 特定逻辑）"""
+    
+    model = EholeFingerprint
+    
+    def validate_fingerprint(self, item: dict) -> bool:
+        """
+        校验单条 EHole 指纹
+        
+        校验规则：
+        - cms 字段必须存在且非空
+        - keyword 字段必须是数组
+        
+        Args:
+            item: 单条指纹数据
+            
+        Returns:
+            bool: 是否有效
+        """
+        cms = item.get('cms', '')
+        keyword = item.get('keyword')
+        return bool(cms and str(cms).strip()) and isinstance(keyword, list)
+    
+    def to_model_data(self, item: dict) -> dict:
+        """
+        转换 EHole JSON 格式为 Model 字段
+        
+        字段映射：
+        - isImportant (JSON) → is_important (Model)
+        
+        Args:
+            item: 原始 EHole JSON 数据
+            
+        Returns:
+            dict: Model 字段数据
+        """
+        return {
+            'cms': str(item.get('cms', '')).strip(),
+            'method': item.get('method', 'keyword'),
+            'location': item.get('location', 'body'),
+            'keyword': item.get('keyword', []),
+            'is_important': item.get('isImportant', False),
+            'type': item.get('type', '-'),
+        }
+    
+    def get_export_data(self) -> dict:
+        """
+        获取导出数据（EHole JSON 格式）
+        
+        Returns:
+            dict: EHole 格式的 JSON 数据
+            {
+                "fingerprint": [
+                    {"cms": "...", "method": "...", "location": "...", 
+                     "keyword": [...], "isImportant": false, "type": "..."},
+                    ...
+                ],
+                "version": "1000_1703836800"
+            }
+        """
+        fingerprints = self.model.objects.all()
+        data = []
+        for fp in fingerprints:
+            data.append({
+                'cms': fp.cms,
+                'method': fp.method,
+                'location': fp.location,
+                'keyword': fp.keyword,
+                'isImportant': fp.is_important,  # 转回 JSON 格式
+                'type': fp.type,
+            })
+        return {
+            'fingerprint': data,
+            'version': self.get_fingerprint_version(),
+        }

backend/apps/engine/services/fingerprints/goby.py

@@ -0,0 +1,70 @@
+"""Goby 指纹管理 Service
+
+实现 Goby 格式指纹的校验、转换和导出逻辑
+"""
+
+from apps.engine.models import GobyFingerprint
+from .base import BaseFingerprintService
+
+
+class GobyFingerprintService(BaseFingerprintService):
+    """Goby 指纹管理服务（继承基类，实现 Goby 特定逻辑）"""
+    
+    model = GobyFingerprint
+    
+    def validate_fingerprint(self, item: dict) -> bool:
+        """
+        校验单条 Goby 指纹
+        
+        校验规则：
+        - name 字段必须存在且非空
+        - logic 字段必须存在
+        - rule 字段必须是数组
+        
+        Args:
+            item: 单条指纹数据
+            
+        Returns:
+            bool: 是否有效
+        """
+        name = item.get('name', '')
+        logic = item.get('logic', '')
+        rule = item.get('rule')
+        return bool(name and str(name).strip()) and bool(logic) and isinstance(rule, list)
+    
+    def to_model_data(self, item: dict) -> dict:
+        """
+        转换 Goby JSON 格式为 Model 字段
+        
+        Args:
+            item: 原始 Goby JSON 数据
+            
+        Returns:
+            dict: Model 字段数据
+        """
+        return {
+            'name': str(item.get('name', '')).strip(),
+            'logic': item.get('logic', ''),
+            'rule': item.get('rule', []),
+        }
+    
+    def get_export_data(self) -> list:
+        """
+        获取导出数据（Goby JSON 格式 - 数组）
+        
+        Returns:
+            list: Goby 格式的 JSON 数据（数组格式）
+            [
+                {"name": "...", "logic": "...", "rule": [...]},
+                ...
+            ]
+        """
+        fingerprints = self.model.objects.all()
+        return [
+            {
+                'name': fp.name,
+                'logic': fp.logic,
+                'rule': fp.rule,
+            }
+            for fp in fingerprints
+        ]

backend/apps/engine/services/fingerprints/wappalyzer.py

@@ -0,0 +1,99 @@
+"""Wappalyzer 指纹管理 Service
+
+实现 Wappalyzer 格式指纹的校验、转换和导出逻辑
+"""
+
+from apps.engine.models import WappalyzerFingerprint
+from .base import BaseFingerprintService
+
+
+class WappalyzerFingerprintService(BaseFingerprintService):
+    """Wappalyzer 指纹管理服务（继承基类，实现 Wappalyzer 特定逻辑）"""
+    
+    model = WappalyzerFingerprint
+    
+    def validate_fingerprint(self, item: dict) -> bool:
+        """
+        校验单条 Wappalyzer 指纹
+        
+        校验规则：
+        - name 字段必须存在且非空（从 apps 对象的 key 传入）
+        
+        Args:
+            item: 单条指纹数据
+            
+        Returns:
+            bool: 是否有效
+        """
+        name = item.get('name', '')
+        return bool(name and str(name).strip())
+    
+    def to_model_data(self, item: dict) -> dict:
+        """
+        转换 Wappalyzer JSON 格式为 Model 字段
+        
+        字段映射：
+        - scriptSrc (JSON) → script_src (Model)
+        
+        Args:
+            item: 原始 Wappalyzer JSON 数据
+            
+        Returns:
+            dict: Model 字段数据
+        """
+        return {
+            'name': str(item.get('name', '')).strip(),
+            'cats': item.get('cats', []),
+            'cookies': item.get('cookies', {}),
+            'headers': item.get('headers', {}),
+            'script_src': item.get('scriptSrc', []),  # JSON: scriptSrc -> Model: script_src
+            'js': item.get('js', []),
+            'implies': item.get('implies', []),
+            'meta': item.get('meta', {}),
+            'html': item.get('html', []),
+            'description': item.get('description', ''),
+            'website': item.get('website', ''),
+            'cpe': item.get('cpe', ''),
+        }
+    
+    def get_export_data(self) -> dict:
+        """
+        获取导出数据（Wappalyzer JSON 格式）
+        
+        Returns:
+            dict: Wappalyzer 格式的 JSON 数据
+            {
+                "apps": {
+                    "AppName": {"cats": [...], "cookies": {...}, ...},
+                    ...
+                }
+            }
+        """
+        fingerprints = self.model.objects.all()
+        apps = {}
+        for fp in fingerprints:
+            app_data = {}
+            if fp.cats:
+                app_data['cats'] = fp.cats
+            if fp.cookies:
+                app_data['cookies'] = fp.cookies
+            if fp.headers:
+                app_data['headers'] = fp.headers
+            if fp.script_src:
+                app_data['scriptSrc'] = fp.script_src  # Model: script_src -> JSON: scriptSrc
+            if fp.js:
+                app_data['js'] = fp.js
+            if fp.implies:
+                app_data['implies'] = fp.implies
+            if fp.meta:
+                app_data['meta'] = fp.meta
+            if fp.html:
+                app_data['html'] = fp.html
+            if fp.description:
+                app_data['description'] = fp.description
+            if fp.website:
+                app_data['website'] = fp.website
+            if fp.cpe:
+                app_data['cpe'] = fp.cpe
+            apps[fp.name] = app_data
+        return {'apps': apps}

backend/apps/engine/services/nuclei_template_repo_service.py

@@ -186,6 +186,7 @@ class NucleiTemplateRepoService:
             RuntimeError: Git 命令执行失败
         """
         import subprocess
+        from apps.common.utils.git_proxy import get_git_proxy_url
 
         obj = self._get_repo_obj(repo_id)
 
@@ -196,9 +197,14 @@ class NucleiTemplateRepoService:
         cmd: List[str]
         action: str
 
+        # 获取代理后的 URL（如果启用了 Git 加速）
+        proxied_url = get_git_proxy_url(obj.repo_url)
+        if proxied_url != obj.repo_url:
+            logger.info("使用 Git 加速: %s -> %s", obj.repo_url, proxied_url)
+
         # 判断是 clone 还是 pull
         if git_dir.is_dir():
-            # 检查远程地址是否变化
+            # 检查远程地址是否变化（比较原始 URL，不是代理 URL）
             current_remote = subprocess.run(
                 ["git", "-C", str(local_path), "remote", "get-url", "origin"],
                 check=False,
@@ -208,12 +214,13 @@ class NucleiTemplateRepoService:
             )
             current_url = current_remote.stdout.strip() if current_remote.returncode == 0 else ""
             
-            if current_url != obj.repo_url:
+            # 检查是否需要重新 clone（原始 URL 或代理 URL 变化都需要）
+            if current_url not in [obj.repo_url, proxied_url]:
                 # 远程地址变化，删除旧目录重新 clone
                 logger.info("nuclei 模板仓库 %s 远程地址变化，重新 clone: %s -> %s", obj.id, current_url, obj.repo_url)
                 shutil.rmtree(local_path)
                 local_path.mkdir(parents=True, exist_ok=True)
-                cmd = ["git", "clone", "--depth", "1", obj.repo_url, str(local_path)]
+                cmd = ["git", "clone", "--depth", "1", proxied_url, str(local_path)]
                 action = "clone"
             else:
                 # 已有仓库且地址未变，执行 pull
@@ -224,7 +231,7 @@ class NucleiTemplateRepoService:
             if local_path.exists() and not local_path.is_dir():
                 raise RuntimeError(f"本地路径已存在且不是目录: {local_path}")
             # --depth 1 浅克隆，只获取最新提交，节省空间和时间
-            cmd = ["git", "clone", "--depth", "1", obj.repo_url, str(local_path)]
+            cmd = ["git", "clone", "--depth", "1", proxied_url, str(local_path)]
             action = "clone"
 
         # 执行 Git 命令

backend/apps/engine/services/task_distributor.py

@@ -76,8 +76,8 @@ class TaskDistributor:
         self.docker_image = settings.TASK_EXECUTOR_IMAGE
         if not self.docker_image:
             raise ValueError("TASK_EXECUTOR_IMAGE 未配置，请确保 IMAGE_TAG 环境变量已设置")
-        self.results_mount = getattr(settings, 'CONTAINER_RESULTS_MOUNT', '/app/backend/results')
-        self.logs_mount = getattr(settings, 'CONTAINER_LOGS_MOUNT', '/app/backend/logs')
+        # 统一使用 /opt/xingrin 下的路径
+        self.logs_mount = "/opt/xingrin/logs"
         self.submit_interval = getattr(settings, 'TASK_SUBMIT_INTERVAL', 5)
     
     def get_online_workers(self) -> list[WorkerNode]:
@@ -153,30 +153,68 @@ class TaskDistributor:
             else:
                 scored_workers.append((worker, score, cpu, mem))
         
-        # 降级策略：如果没有正常负载的，等待后重新选择
+        # 降级策略：如果没有正常负载的，循环等待后重新检测
         if not scored_workers:
             if high_load_workers:
-                # 高负载时先等待，给系统喘息时间（默认 60 秒）
+                # 高负载等待参数（默认每 60 秒检测一次，最多 10 次）
                 high_load_wait = getattr(settings, 'HIGH_LOAD_WAIT_SECONDS', 60)
-                logger.warning("所有 Worker 高负载，等待 %d 秒后重试...", high_load_wait)
-                time.sleep(high_load_wait)
+                high_load_max_retries = getattr(settings, 'HIGH_LOAD_MAX_RETRIES', 10)
                 
-                # 重新选择（递归调用，可能负载已降下来）
-                # 为避免无限递归，这里直接使用高负载中最低的
+                # 开始等待前发送高负载通知
                 high_load_workers.sort(key=lambda x: x[1])
-                best_worker, _, cpu, mem = high_load_workers[0]
-                
-                # 发送高负载通知
+                _, _, first_cpu, first_mem = high_load_workers[0]
                 from apps.common.signals import all_workers_high_load
                 all_workers_high_load.send(
                     sender=self.__class__,
-                    worker_name=best_worker.name,
-                    cpu=cpu,
-                    mem=mem
+                    worker_name="所有节点",
+                    cpu=first_cpu,
+                    mem=first_mem
                 )
                 
-                logger.info("选择 Worker: %s (CPU: %.1f%%, MEM: %.1f%%)", best_worker.name, cpu, mem)
-                return best_worker
+                for retry in range(high_load_max_retries):
+                    logger.warning(
+                        "所有 Worker 高负载，等待 %d 秒后重试... (%d/%d)",
+                        high_load_wait, retry + 1, high_load_max_retries
+                    )
+                    time.sleep(high_load_wait)
+                    
+                    # 重新获取负载数据
+                    loads = worker_load_service.get_all_loads(worker_ids)
+                    
+                    # 重新评估
+                    scored_workers = []
+                    high_load_workers = []
+                    
+                    for worker in workers:
+                        load = loads.get(worker.id)
+                        if not load:
+                            continue
+                        
+                        cpu = load.get('cpu', 0)
+                        mem = load.get('mem', 0)
+                        score = cpu * 0.7 + mem * 0.3
+                        
+                        if cpu > 85 or mem > 85:
+                            high_load_workers.append((worker, score, cpu, mem))
+                        else:
+                            scored_workers.append((worker, score, cpu, mem))
+                    
+                    # 如果有正常负载的 Worker，跳出循环
+                    if scored_workers:
+                        logger.info("检测到正常负载 Worker，结束等待")
+                        break
+                
+                # 超时或仍然高负载，选择负载最低的
+                if not scored_workers and high_load_workers:
+                    high_load_workers.sort(key=lambda x: x[1])
+                    best_worker, _, cpu, mem = high_load_workers[0]
+                    
+                    logger.warning(
+                        "等待超时，强制分发到高负载 Worker: %s (CPU: %.1f%%, MEM: %.1f%%)",
+                        best_worker.name, cpu, mem
+                    )
+                    return best_worker
+                    return best_worker
             else:
                 logger.warning("没有可用的 Worker")
                 return None
@@ -234,11 +272,10 @@ class TaskDistributor:
         else:
             # 远程：通过 Nginx 反向代理访问（HTTPS，不直连 8888 端口）
             network_arg = ""
-            server_url = f"https://{settings.PUBLIC_HOST}"
+            server_url = f"https://{settings.PUBLIC_HOST}:{settings.PUBLIC_PORT}"
         
-        # 挂载路径（所有节点统一使用固定路径）
-        host_results_dir = settings.HOST_RESULTS_DIR  # /opt/xingrin/results
-        host_logs_dir = settings.HOST_LOGS_DIR  # /opt/xingrin/logs
+        # 挂载路径（统一挂载 /opt/xingrin）
+        host_xingrin_dir = "/opt/xingrin"
         
         # 环境变量：SERVER_URL + IS_LOCAL，其他配置容器启动时从配置中心获取
         # IS_LOCAL 用于 Worker 向配置中心声明身份，决定返回的数据库地址
@@ -251,15 +288,12 @@ class TaskDistributor:
             "-e PREFECT_SERVER_EPHEMERAL_ENABLED=true",  # 启用 ephemeral server（本地临时服务器）
             "-e PREFECT_SERVER_EPHEMERAL_STARTUP_TIMEOUT_SECONDS=120",  # 增加启动超时时间
             "-e PREFECT_SERVER_DATABASE_CONNECTION_URL=sqlite+aiosqlite:////tmp/.prefect/prefect.db",  # 使用 /tmp 下的 SQLite
-            "-e PREFECT_LOGGING_LEVEL=DEBUG",  # 启用 DEBUG 级别日志
-            "-e PREFECT_LOGGING_SERVER_LEVEL=DEBUG",  # Server 日志级别
-            "-e PREFECT_DEBUG_MODE=true",  # 启用调试模式
+            "-e PREFECT_LOGGING_LEVEL=WARNING",  # 日志级别（减少 DEBUG 噪音）
         ]
         
-        # 挂载卷
+        # 挂载卷（统一挂载整个 /opt/xingrin 目录）
         volumes = [
-            f"-v {host_results_dir}:{self.results_mount}",
-            f"-v {host_logs_dir}:{self.logs_mount}",
+            f"-v {host_xingrin_dir}:{host_xingrin_dir}",
         ]
         
         # 构建命令行参数
@@ -520,7 +554,7 @@ class TaskDistributor:
             try:
                 # 构建 docker run 命令（清理过期扫描结果目录）
                 script_args = {
-                    'results_dir': '/app/backend/results',
+                    'results_dir': '/opt/xingrin/results',
                     'retention_days': retention_days,
                 }
                 

backend/apps/engine/services/wordlist_service.py

@@ -13,7 +13,7 @@ from django.conf import settings
 from django.core.exceptions import ValidationError
 from django.core.files.uploadedfile import UploadedFile
 
-from apps.common.hash_utils import safe_calc_file_sha256
+from apps.common.utils import safe_calc_file_sha256
 from apps.engine.models import Wordlist
 from apps.engine.repositories import DjangoWordlistRepository
 

backend/apps/engine/urls.py

@@ -7,6 +7,11 @@ from .views import (
     WordlistViewSet,
     NucleiTemplateRepoViewSet,
 )
+from .views.fingerprints import (
+    EholeFingerprintViewSet,
+    GobyFingerprintViewSet,
+    WappalyzerFingerprintViewSet,
+)
 
 
 # 创建路由器
@@ -15,6 +20,10 @@ router.register(r"engines", ScanEngineViewSet, basename="engine")
 router.register(r"workers", WorkerNodeViewSet, basename="worker")
 router.register(r"wordlists", WordlistViewSet, basename="wordlist")
 router.register(r"nuclei/repos", NucleiTemplateRepoViewSet, basename="nuclei-repos")
+# 指纹管理
+router.register(r"fingerprints/ehole", EholeFingerprintViewSet, basename="ehole-fingerprint")
+router.register(r"fingerprints/goby", GobyFingerprintViewSet, basename="goby-fingerprint")
+router.register(r"fingerprints/wappalyzer", WappalyzerFingerprintViewSet, basename="wappalyzer-fingerprint")
 
 urlpatterns = [
     path("", include(router.urls)),

backend/apps/engine/views/fingerprints/__init__.py

@@ -0,0 +1,16 @@
+"""指纹管理 ViewSets
+
+导出所有指纹相关的 ViewSet 类
+"""
+
+from .base import BaseFingerprintViewSet
+from .ehole import EholeFingerprintViewSet
+from .goby import GobyFingerprintViewSet
+from .wappalyzer import WappalyzerFingerprintViewSet
+
+__all__ = [
+    "BaseFingerprintViewSet",
+    "EholeFingerprintViewSet",
+    "GobyFingerprintViewSet",
+    "WappalyzerFingerprintViewSet",
+]

backend/apps/engine/views/fingerprints/base.py

@@ -0,0 +1,202 @@
+"""指纹管理基类 ViewSet
+
+提供通用的 CRUD 和批量操作，供 EHole/Goby/Wappalyzer 等子类继承
+"""
+
+import json
+import logging
+
+from django.http import HttpResponse
+from rest_framework import viewsets, status, filters
+from rest_framework.decorators import action
+from rest_framework.response import Response
+from rest_framework.exceptions import ValidationError
+
+from apps.common.pagination import BasePagination
+from apps.common.utils.filter_utils import apply_filters
+
+logger = logging.getLogger(__name__)
+
+
+class BaseFingerprintViewSet(viewsets.ModelViewSet):
+    """指纹管理基类 ViewSet，供 EHole/Goby/Wappalyzer 等子类继承
+    
+    提供的 API：
+    
+    标准 CRUD（继承自 ModelViewSet）：
+    - GET    /                  列表查询（分页 + 智能过滤）
+    - POST   /                  创建单条
+    - GET    /{id}/             获取详情
+    - PUT    /{id}/             更新
+    - DELETE /{id}/             删除
+    
+    批量操作（本类实现）：
+    - POST   /batch_create/     批量创建（JSON body）
+    - POST   /import_file/      文件导入（multipart/form-data，适合 10MB+ 大文件）
+    - POST   /bulk-delete/      批量删除
+    - POST   /delete-all/       删除所有
+    - GET    /export/           导出下载
+    
+    智能过滤语法（filter 参数）：
+    - field="value"      模糊匹配（包含）
+    - field=="value"     精确匹配
+    - 多条件空格分隔     AND 关系
+    - || 或 or           OR 关系
+    
+    子类必须实现：
+    - service_class      Service 类
+    - parse_import_data  解析导入数据格式
+    - get_export_filename 导出文件名
+    """
+    
+    pagination_class = BasePagination
+    filter_backends = [filters.OrderingFilter]
+    ordering = ['-created_at']
+    
+    # 子类必须指定
+    service_class = None  # Service 类
+    
+    # 智能过滤字段映射，子类必须覆盖
+    FILTER_FIELD_MAPPING = {}
+    
+    # JSON 数组字段列表（使用 __contains 查询），子类可覆盖
+    JSON_ARRAY_FIELDS = []
+    
+    def get_queryset(self):
+        """支持智能过滤语法"""
+        queryset = super().get_queryset()
+        filter_query = self.request.query_params.get('filter', None)
+        if filter_query:
+            queryset = apply_filters(
+                queryset, 
+                filter_query, 
+                self.FILTER_FIELD_MAPPING,
+                json_array_fields=getattr(self, 'JSON_ARRAY_FIELDS', [])
+            )
+        return queryset
+    
+    def get_service(self):
+        """获取 Service 实例"""
+        if self.service_class is None:
+            raise NotImplementedError("子类必须指定 service_class")
+        return self.service_class()
+    
+    def parse_import_data(self, json_data: dict) -> list:
+        """
+        解析导入数据，子类必须实现
+        
+        Args:
+            json_data: 解析后的 JSON 数据
+            
+        Returns:
+            list: 指纹数据列表
+        """
+        raise NotImplementedError("子类必须实现 parse_import_data 方法")
+    
+    def get_export_filename(self) -> str:
+        """
+        导出文件名，子类必须实现
+        
+        Returns:
+            str: 文件名
+        """
+        raise NotImplementedError("子类必须实现 get_export_filename 方法")
+
+    @action(detail=False, methods=['post'])
+    def batch_create(self, request):
+        """
+        批量创建指纹规则
+        POST /api/engine/fingerprints/{type}/batch_create/
+        
+        请求格式：
+        {
+            "fingerprints": [
+                {"cms": "WordPress", "method": "keyword", ...},
+                ...
+            ]
+        }
+        
+        返回：
+        {
+            "created": 2,
+            "failed": 0
+        }
+        """
+        fingerprints = request.data.get('fingerprints', [])
+        if not fingerprints:
+            raise ValidationError('fingerprints 不能为空')
+        if not isinstance(fingerprints, list):
+            raise ValidationError('fingerprints 必须是数组')
+        
+        result = self.get_service().batch_create_fingerprints(fingerprints)
+        return Response(result, status=status.HTTP_201_CREATED)
+    
+    @action(detail=False, methods=['post'])
+    def import_file(self, request):
+        """
+        文件导入（适合大文件，10MB+）
+        POST /api/engine/fingerprints/{type}/import_file/
+        
+        请求格式：multipart/form-data
+        - file: JSON 文件
+        
+        返回：同 batch_create
+        """
+        file = request.FILES.get('file')
+        if not file:
+            raise ValidationError('缺少文件')
+        
+        try:
+            json_data = json.load(file)
+        except json.JSONDecodeError as e:
+            raise ValidationError(f'无效的 JSON 格式: {e}')
+        
+        fingerprints = self.parse_import_data(json_data)
+        if not fingerprints:
+            raise ValidationError('文件中没有有效的指纹数据')
+        
+        result = self.get_service().batch_create_fingerprints(fingerprints)
+        return Response(result, status=status.HTTP_201_CREATED)
+    
+    @action(detail=False, methods=['post'], url_path='bulk-delete')
+    def bulk_delete(self, request):
+        """
+        批量删除
+        POST /api/engine/fingerprints/{type}/bulk-delete/
+        
+        请求格式：{"ids": [1, 2, 3]}
+        返回：{"deleted": 3}
+        """
+        ids = request.data.get('ids', [])
+        if not ids:
+            raise ValidationError('ids 不能为空')
+        if not isinstance(ids, list):
+            raise ValidationError('ids 必须是数组')
+        
+        deleted_count = self.queryset.model.objects.filter(id__in=ids).delete()[0]
+        return Response({'deleted': deleted_count})
+    
+    @action(detail=False, methods=['post'], url_path='delete-all')
+    def delete_all(self, request):
+        """
+        删除所有指纹
+        POST /api/engine/fingerprints/{type}/delete-all/
+        
+        返回：{"deleted": 1000}
+        """
+        deleted_count = self.queryset.model.objects.all().delete()[0]
+        return Response({'deleted': deleted_count})
+    
+    @action(detail=False, methods=['get'])
+    def export(self, request):
+        """
+        导出指纹（前端下载）
+        GET /api/engine/fingerprints/{type}/export/
+        
+        返回：JSON 文件下载
+        """
+        data = self.get_service().get_export_data()
+        content = json.dumps(data, ensure_ascii=False, indent=2)
+        response = HttpResponse(content, content_type='application/json')
+        response['Content-Disposition'] = f'attachment; filename="{self.get_export_filename()}"'
+        return response

backend/apps/engine/views/fingerprints/ehole.py

@@ -0,0 +1,67 @@
+"""EHole 指纹管理 ViewSet"""
+
+from apps.common.pagination import BasePagination
+from apps.engine.models import EholeFingerprint
+from apps.engine.serializers.fingerprints import EholeFingerprintSerializer
+from apps.engine.services.fingerprints import EholeFingerprintService
+
+from .base import BaseFingerprintViewSet
+
+
+class EholeFingerprintViewSet(BaseFingerprintViewSet):
+    """EHole 指纹管理 ViewSet
+    
+    继承自 BaseFingerprintViewSet，提供以下 API：
+    
+    标准 CRUD（ModelViewSet）：
+    - GET    /                  列表查询（分页）
+    - POST   /                  创建单条
+    - GET    /{id}/             获取详情
+    - PUT    /{id}/             更新
+    - DELETE /{id}/             删除
+    
+    批量操作（继承自基类）：
+    - POST   /batch_create/     批量创建（JSON body）
+    - POST   /import_file/      文件导入（multipart/form-data）
+    - POST   /bulk-delete/      批量删除
+    - POST   /delete-all/       删除所有
+    - GET    /export/           导出下载
+    
+    智能过滤语法（filter 参数）：
+    - cms="word"         模糊匹配 cms 字段
+    - cms=="WordPress"   精确匹配
+    - type="CMS"         按类型筛选
+    - method="keyword"   按匹配方式筛选
+    - location="body"    按匹配位置筛选
+    """
+    
+    queryset = EholeFingerprint.objects.all()
+    serializer_class = EholeFingerprintSerializer
+    pagination_class = BasePagination
+    service_class = EholeFingerprintService
+    
+    # 排序配置
+    ordering_fields = ['created_at', 'cms']
+    ordering = ['-created_at']
+    
+    # EHole 过滤字段映射
+    FILTER_FIELD_MAPPING = {
+        'cms': 'cms',
+        'method': 'method',
+        'location': 'location',
+        'type': 'type',
+        'isImportant': 'is_important',
+    }
+    
+    def parse_import_data(self, json_data: dict) -> list:
+        """
+        解析 EHole JSON 格式的导入数据
+        
+        输入格式：{"fingerprint": [...]}
+        返回：指纹列表
+        """
+        return json_data.get('fingerprint', [])
+    
+    def get_export_filename(self) -> str:
+        """导出文件名"""
+        return 'ehole.json'

backend/apps/engine/views/fingerprints/goby.py

@@ -0,0 +1,65 @@
+"""Goby 指纹管理 ViewSet"""
+
+from apps.common.pagination import BasePagination
+from apps.engine.models import GobyFingerprint
+from apps.engine.serializers.fingerprints import GobyFingerprintSerializer
+from apps.engine.services.fingerprints import GobyFingerprintService
+
+from .base import BaseFingerprintViewSet
+
+
+class GobyFingerprintViewSet(BaseFingerprintViewSet):
+    """Goby 指纹管理 ViewSet
+    
+    继承自 BaseFingerprintViewSet，提供以下 API：
+    
+    标准 CRUD（ModelViewSet）：
+    - GET    /                  列表查询（分页）
+    - POST   /                  创建单条
+    - GET    /{id}/             获取详情
+    - PUT    /{id}/             更新
+    - DELETE /{id}/             删除
+    
+    批量操作（继承自基类）：
+    - POST   /batch_create/     批量创建（JSON body）
+    - POST   /import_file/      文件导入（multipart/form-data）
+    - POST   /bulk-delete/      批量删除
+    - POST   /delete-all/       删除所有
+    - GET    /export/           导出下载
+    
+    智能过滤语法（filter 参数）：
+    - name="word"        模糊匹配 name 字段
+    - name=="ProductName" 精确匹配
+    """
+    
+    queryset = GobyFingerprint.objects.all()
+    serializer_class = GobyFingerprintSerializer
+    pagination_class = BasePagination
+    service_class = GobyFingerprintService
+    
+    # 排序配置
+    ordering_fields = ['created_at', 'name']
+    ordering = ['-created_at']
+    
+    # Goby 过滤字段映射
+    FILTER_FIELD_MAPPING = {
+        'name': 'name',
+        'logic': 'logic',
+    }
+    
+    def parse_import_data(self, json_data) -> list:
+        """
+        解析 Goby JSON 格式的导入数据
+        
+        Goby 格式是数组格式：[{...}, {...}, ...]
+        
+        输入格式：[{"name": "...", "logic": "...", "rule": [...]}, ...]
+        返回：指纹列表
+        """
+        if isinstance(json_data, list):
+            return json_data
+        return []
+    
+    def get_export_filename(self) -> str:
+        """导出文件名"""
+        return 'goby.json'

backend/apps/engine/views/fingerprints/wappalyzer.py

@@ -0,0 +1,75 @@
+"""Wappalyzer 指纹管理 ViewSet"""
+
+from apps.common.pagination import BasePagination
+from apps.engine.models import WappalyzerFingerprint
+from apps.engine.serializers.fingerprints import WappalyzerFingerprintSerializer
+from apps.engine.services.fingerprints import WappalyzerFingerprintService
+
+from .base import BaseFingerprintViewSet
+
+
+class WappalyzerFingerprintViewSet(BaseFingerprintViewSet):
+    """Wappalyzer 指纹管理 ViewSet
+    
+    继承自 BaseFingerprintViewSet，提供以下 API：
+    
+    标准 CRUD（ModelViewSet）：
+    - GET    /                  列表查询（分页）
+    - POST   /                  创建单条
+    - GET    /{id}/             获取详情
+    - PUT    /{id}/             更新
+    - DELETE /{id}/             删除
+    
+    批量操作（继承自基类）：
+    - POST   /batch_create/     批量创建（JSON body）
+    - POST   /import_file/      文件导入（multipart/form-data）
+    - POST   /bulk-delete/      批量删除
+    - POST   /delete-all/       删除所有
+    - GET    /export/           导出下载
+    
+    智能过滤语法（filter 参数）：
+    - name="word"        模糊匹配 name 字段
+    - name=="AppName"    精确匹配
+    """
+    
+    queryset = WappalyzerFingerprint.objects.all()
+    serializer_class = WappalyzerFingerprintSerializer
+    pagination_class = BasePagination
+    service_class = WappalyzerFingerprintService
+    
+    # 排序配置
+    ordering_fields = ['created_at', 'name']
+    ordering = ['-created_at']
+    
+    # Wappalyzer 过滤字段映射
+    # 注意：implies 是 JSON 数组字段，使用 __contains 查询
+    FILTER_FIELD_MAPPING = {
+        'name': 'name',
+        'description': 'description',
+        'website': 'website',
+        'cpe': 'cpe',
+        'implies': 'implies',  # JSON 数组字段
+    }
+    
+    # JSON 数组字段列表（使用 __contains 查询）
+    JSON_ARRAY_FIELDS = ['implies']
+    
+    def parse_import_data(self, json_data: dict) -> list:
+        """
+        解析 Wappalyzer JSON 格式的导入数据
+        
+        Wappalyzer 格式是 apps 对象格式：{"apps": {"AppName": {...}, ...}}
+        
+        输入格式：{"apps": {"1C-Bitrix": {"cats": [...], ...}, ...}}
+        返回：指纹列表（每个 app 转换为带 name 字段的 dict）
+        """
+        apps = json_data.get('apps', {})
+        fingerprints = []
+        for name, data in apps.items():
+            item = {'name': name, **data}
+            fingerprints.append(item)
+        return fingerprints
+    
+    def get_export_filename(self) -> str:
+        """导出文件名"""
+        return 'wappalyzer.json'

backend/apps/engine/views/worker_views.py

@@ -238,7 +238,7 @@ class WorkerNodeViewSet(viewsets.ModelViewSet):
                     docker run -d --pull=always \
                         --name xingrin-agent \
                         --restart always \
-                        -e HEARTBEAT_API_URL="https://{django_settings.PUBLIC_HOST}" \
+                        -e HEARTBEAT_API_URL="https://{django_settings.PUBLIC_HOST}:{getattr(django_settings, 'PUBLIC_PORT', '8083')}" \
                         -e WORKER_ID="{worker_id}" \
                         -e IMAGE_TAG="{target_version}" \
                         -v /proc:/host/proc:ro \
@@ -390,12 +390,14 @@ class WorkerNodeViewSet(viewsets.ModelViewSet):
             },
             'redisUrl': worker_redis_url,
             'paths': {
-                'results': getattr(settings, 'CONTAINER_RESULTS_MOUNT', '/app/backend/results'),
-                'logs': getattr(settings, 'CONTAINER_LOGS_MOUNT', '/app/backend/logs'),
+                'results': getattr(settings, 'CONTAINER_RESULTS_MOUNT', '/opt/xingrin/results'),
+                'logs': getattr(settings, 'CONTAINER_LOGS_MOUNT', '/opt/xingrin/logs'),
             },
             'logging': {
                 'level': os.getenv('LOG_LEVEL', 'INFO'),
                 'enableCommandLogging': os.getenv('ENABLE_COMMAND_LOGGING', 'true').lower() == 'true',
             },
-            'debug': settings.DEBUG
+            'debug': settings.DEBUG,
+            # Git 加速配置（用于 Git clone 加速，如 Nuclei 模板仓库）
+            'gitMirror': os.getenv('GIT_MIRROR', ''),
         })

backend/apps/scan/configs/command_templates.py

@@ -16,7 +16,7 @@ SUBDOMAIN_DISCOVERY_COMMANDS = {
         # 默认使用所有数据源（更全面，略慢），并始终开启递归
         # -all       使用所有数据源
         # -recursive 对支持递归的源启用递归枚举（默认开启）
-        'base': 'subfinder -d {domain} -all -recursive -o {output_file} -silent',
+        'base': "subfinder -d {domain} -all -recursive -o '{output_file}' -silent",
         'optional': {
             'threads': '-t {threads}',              # 控制并发 goroutine 数
         }
@@ -25,31 +25,31 @@ SUBDOMAIN_DISCOVERY_COMMANDS = {
     'amass_passive': {
         # 先执行被动枚举，将结果写入 amass 内部数据库，然后从数据库中导出纯域名（names）到 output_file
         # -silent 禁用进度条和其他输出
-        'base': 'amass enum -passive -silent -d {domain} && amass subs -names -d {domain} > {output_file}'
+        'base': "amass enum -passive -silent -d {domain} && amass subs -names -d {domain} > '{output_file}'"
     },
     
     'amass_active': {
         # 先执行主动枚举 + 爆破，将结果写入 amass 内部数据库，然后从数据库中导出纯域名（names）到 output_file
         # -silent 禁用进度条和其他输出
-        'base': 'amass enum -active -silent -d {domain} -brute && amass subs -names -d {domain} > {output_file}'
+        'base': "amass enum -active -silent -d {domain} -brute && amass subs -names -d {domain} > '{output_file}'"
     },
     
     'sublist3r': {
-        'base': 'python3 {scan_tools_base}/Sublist3r/sublist3r.py -d {domain} -o {output_file}',
+        'base': "python3 '{scan_tools_base}/Sublist3r/sublist3r.py' -d {domain} -o '{output_file}'",
         'optional': {
             'threads': '-t {threads}'
         }
     },
     
     'assetfinder': {
-        'base': 'assetfinder --subs-only {domain} > {output_file}',
+        'base': "assetfinder --subs-only {domain} > '{output_file}'",
     },
     
     # === 主动字典爆破 ===
     'subdomain_bruteforce': {
         # 使用字典对目标域名进行 DNS 爆破
         # -d 目标域名，-w 字典文件，-o 输出文件
-        'base': 'puredns bruteforce {wordlist} {domain} -r /app/backend/resources/resolvers.txt --write {output_file} --quiet',
+        'base': "puredns bruteforce '{wordlist}' {domain} -r /app/backend/resources/resolvers.txt --write '{output_file}' --quiet",
         'optional': {},
     },
     
@@ -57,7 +57,7 @@ SUBDOMAIN_DISCOVERY_COMMANDS = {
     'subdomain_resolve': {
         # 验证子域名是否能解析（存活验证）
         # 输入文件为候选子域列表，输出为存活子域列表
-        'base': 'puredns resolve {input_file} -r /app/backend/resources/resolvers.txt --write {output_file} --wildcard-tests 50 --wildcard-batch 1000000 --quiet',
+        'base': "puredns resolve '{input_file}' -r /app/backend/resources/resolvers.txt --write '{output_file}' --wildcard-tests 50 --wildcard-batch 1000000 --quiet",
         'optional': {},
     },
     
@@ -65,7 +65,7 @@ SUBDOMAIN_DISCOVERY_COMMANDS = {
     'subdomain_permutation_resolve': {
         # 流式管道：dnsgen 生成变异域名 | puredns resolve 验证存活
         # 不落盘中间文件，避免内存爆炸；不做通配符过滤
-        'base': 'cat {input_file} | dnsgen - | puredns resolve -r /app/backend/resources/resolvers.txt --write {output_file} --wildcard-tests 50 --wildcard-batch 1000000 --quiet',
+        'base': "cat '{input_file}' | dnsgen - | puredns resolve -r /app/backend/resources/resolvers.txt --write '{output_file}' --wildcard-tests 50 --wildcard-batch 1000000 --quiet",
         'optional': {},
     },
 }
@@ -75,7 +75,7 @@ SUBDOMAIN_DISCOVERY_COMMANDS = {
 
 PORT_SCAN_COMMANDS = {
     'naabu_active': {
-        'base': 'naabu -exclude-cdn -warm-up-time 5 -verify -list {domains_file} -json -silent',
+        'base': "naabu -exclude-cdn -warm-up-time 5 -verify -list '{domains_file}' -json -silent",
         'optional': {
             'threads': '-c {threads}',
             'ports': '-p {ports}',
@@ -85,7 +85,7 @@ PORT_SCAN_COMMANDS = {
     },
     
     'naabu_passive': {
-        'base': 'naabu -list {domains_file} -passive -json -silent'
+        'base': "naabu -list '{domains_file}' -passive -json -silent"
     },
 }
 
@@ -95,7 +95,7 @@ PORT_SCAN_COMMANDS = {
 SITE_SCAN_COMMANDS = {
     'httpx': {
         'base': (
-            'httpx -l {url_file} '
+            "'{scan_tools_base}/httpx' -l '{url_file}' "
             '-status-code -content-type -content-length '
             '-location -title -server -body-preview '
             '-tech-detect -cdn -vhost '
@@ -115,7 +115,7 @@ SITE_SCAN_COMMANDS = {
 
 DIRECTORY_SCAN_COMMANDS = {
     'ffuf': {
-        'base': 'ffuf -u {url}/FUZZ -se -ac -sf -json -w {wordlist}',  
+        'base': "ffuf -u '{url}FUZZ' -se -ac -sf -json -w '{wordlist}'",  
         'optional': {
             'delay': '-p {delay}',
             'threads': '-t {threads}',
@@ -131,13 +131,13 @@ DIRECTORY_SCAN_COMMANDS = {
 
 URL_FETCH_COMMANDS = {
     'waymore': {
-        'base': 'waymore -i {domain_name} -mode U -oU {output_file}',
+        'base': "waymore -i {domain_name} -mode U -oU '{output_file}'",
         'input_type': 'domain_name'
     },
     
     'katana': {
         'base': (
-            'katana -list {sites_file} -o {output_file} '
+            "katana -list '{sites_file}' -o '{output_file}' "
             '-jc '                   # 开启 JavaScript 爬取 + 自动解析 .js 文件里的所有端点（最重要）
             '-xhr '                  # 额外从 JS 中提取 XHR/Fetch 请求的 API 路径（再多挖 10-20% 隐藏接口）
             '-kf all '               # 在每个目录下自动 fuzz 所有已知敏感文件（.env、.git、backup、config、ds_store 等 5000+ 条）
@@ -157,7 +157,7 @@ URL_FETCH_COMMANDS = {
     },
     
     'uro': {
-        'base': 'uro -i {input_file} -o {output_file}',
+        'base': "uro -i '{input_file}' -o '{output_file}'",
         'optional': {
             'whitelist': '-w {whitelist}',      # 只保留指定扩展名的 URL（空格分隔）
             'blacklist': '-b {blacklist}',      # 排除指定扩展名的 URL（空格分隔）
@@ -167,7 +167,7 @@ URL_FETCH_COMMANDS = {
     
     'httpx': {
         'base': (
-            'httpx -l {url_file} '
+            "'{scan_tools_base}/httpx' -l '{url_file}' "
             '-status-code -content-type -content-length '
             '-location -title -server -body-preview '
             '-tech-detect -cdn -vhost '
@@ -187,7 +187,7 @@ VULN_SCAN_COMMANDS = {
         'base': (
             'dalfox --silence --no-color --no-spinner '
             '--skip-bav '
-            'file {endpoints_file} '
+            "file '{endpoints_file}' "
             '--waf-evasion '
             '--format json'
         ),
@@ -205,11 +205,11 @@ VULN_SCAN_COMMANDS = {
     },
     'nuclei': {
         # nuclei 漏洞扫描
-        # -j: JSON 输出
+        # -j: JSON 输出（每行一条完整 JSON）
         # -silent: 静默模式
         # -l: 输入 URL 列表文件
         # -t: 模板目录路径（支持多个仓库，多次 -t 由 template_args 直接拼接）
-        'base': 'nuclei -j -silent -l {endpoints_file} {template_args}',
+        'base': "nuclei -j -silent -l '{endpoints_file}' {template_args}",
         'optional': {
             'concurrency': '-c {concurrency}',           # 并发数（默认 25）
             'rate_limit': '-rl {rate_limit}',            # 每秒请求数限制
@@ -225,12 +225,32 @@ VULN_SCAN_COMMANDS = {
 }
 
 
+# ==================== 指纹识别 ====================
+
+FINGERPRINT_DETECT_COMMANDS = {
+    'xingfinger': {
+        # 流式输出模式（不使用 -o，输出到 stdout）
+        # -l: URL 列表文件输入
+        # -s: 静默模式，只输出命中结果
+        # --json: JSON 格式输出（每行一条）
+        'base': "xingfinger -l '{urls_file}' -s --json",
+        'optional': {
+            # 自定义指纹库路径
+            'ehole': '--ehole {ehole}',
+            'goby': '--goby {goby}',
+            'wappalyzer': '--wappalyzer {wappalyzer}',
+        }
+    },
+}
+
+
 # ==================== 工具映射 ====================
 
 COMMAND_TEMPLATES = {
     'subdomain_discovery': SUBDOMAIN_DISCOVERY_COMMANDS,
     'port_scan': PORT_SCAN_COMMANDS,
     'site_scan': SITE_SCAN_COMMANDS,
+    'fingerprint_detect': FINGERPRINT_DETECT_COMMANDS,
     'directory_scan': DIRECTORY_SCAN_COMMANDS,
     'url_fetch': URL_FETCH_COMMANDS,
     'vuln_scan': VULN_SCAN_COMMANDS,
@@ -242,7 +262,7 @@ COMMAND_TEMPLATES = {
 EXECUTION_STAGES = [
     {
         'mode': 'sequential',
-        'flows': ['subdomain_discovery', 'port_scan', 'site_scan']
+        'flows': ['subdomain_discovery', 'port_scan', 'site_scan', 'fingerprint_detect']
     },
     {
         'mode': 'parallel',

backend/apps/scan/configs/engine_config_example.yaml

@@ -1,7 +1,8 @@
 # 引擎配置
 #
 # 参数命名：统一用中划线（如 rate-limit），系统自动转换为下划线
-# 必需参数：enabled（是否启用）、timeout（超时秒数，auto 表示自动计算）
+# 必需参数：enabled（是否启用）
+# 可选参数：timeout（超时秒数，默认 auto 自动计算）
 
 # ==================== 子域名发现 ====================
 # 
@@ -15,31 +16,31 @@ subdomain_discovery:
   passive_tools:
     subfinder:
       enabled: true
-      timeout: 7200      # 2小时
+      timeout: 3600      # 1小时
       # threads: 10      # 并发 goroutine 数
       
     amass_passive:
       enabled: true
-      timeout: 7200
+      timeout: 3600
       
     amass_active:
       enabled: true      # 主动枚举 + 爆破
-      timeout: 7200
+      timeout: 3600
       
     sublist3r:
       enabled: true
-      timeout: 7200
+      timeout: 3600
       # threads: 50      # 线程数
     
     assetfinder:
       enabled: true
-      timeout: 7200
+      timeout: 3600
 
   # === Stage 2: 主动字典爆破（可选）===
   bruteforce:
     enabled: false
     subdomain_bruteforce:
-      timeout: auto                      # 自动根据字典行数计算
+      # timeout: auto                    # 自动根据字典行数计算
       wordlist-name: subdomains-top1million-110000.txt    # 对应「字典管理」中的 Wordlist.name
 
   # === Stage 3: 变异生成 + 存活验证（可选）===
@@ -52,14 +53,14 @@ subdomain_discovery:
   resolve:
     enabled: true
     subdomain_resolve:
-      timeout: auto      # 自动根据候选子域数量计算
+      # timeout: auto    # 自动根据候选子域数量计算
 
 # ==================== 端口扫描 ====================
 port_scan:
   tools:
     naabu_active:
       enabled: true
-      timeout: auto      # 自动计算（目标数 × 端口数 × 0.5秒），范围 60秒 ~ 2天
+      # timeout: auto    # 自动计算（目标数 × 端口数 × 0.5秒），范围 60秒 ~ 2天
       threads: 200       # 并发连接数（默认 5）
       # ports: 1-65535   # 扫描端口范围（默认 1-65535）
       top-ports: 100     # 扫描 nmap top 100 端口
@@ -67,25 +68,34 @@ port_scan:
       
     naabu_passive:
       enabled: true
-      timeout: auto      # 被动扫描通常较快
+      # timeout: auto    # 被动扫描通常较快
 
 # ==================== 站点扫描 ====================
 site_scan:
   tools:
     httpx:
       enabled: true
-      timeout: auto          # 自动计算（每个 URL 约 1 秒）
+      # timeout: auto        # 自动计算（每个 URL 约 1 秒）
       # threads: 50          # 并发线程数（默认 50）
       # rate-limit: 150      # 每秒请求数（默认 150）
       # request-timeout: 10  # 单个请求超时秒数（默认 10）
       # retries: 2           # 请求失败重试次数
 
+# ==================== 指纹识别 ====================
+# 在 site_scan 后串行执行，识别 WebSite 的技术栈
+fingerprint_detect:
+  tools:
+    xingfinger:
+      enabled: true
+      fingerprint-libs: [ehole, goby, wappalyzer]  # 启用的指纹库：ehole, goby, wappalyzer, fingers, fingerprinthub
+
 # ==================== 目录扫描 ====================
 directory_scan:
   tools:
     ffuf:
       enabled: true
-      timeout: auto                       # 自动计算（字典行数 × 0.02秒），范围 60秒 ~ 2小时
+      # timeout: auto                     # 自动计算（字典行数 × 0.02秒），范围 60秒 ~ 2小时
+      max-workers: 5                      # 并发扫描站点数（默认 5）
       wordlist-name: dir_default.txt      # 对应「字典管理」中的 Wordlist.name
       delay: 0.1-2.0                      # 请求间隔，支持范围随机（如 "0.1-2.0"）
       threads: 10                         # 并发线程数（默认 40）
@@ -102,7 +112,7 @@ url_fetch:
     
     katana:
       enabled: true
-      timeout: auto      # 自动计算（根据站点数量）
+      # timeout: auto    # 自动计算（根据站点数量）
       depth: 5           # 爬取最大深度（默认 3）
       threads: 10        # 全局并发数
       rate-limit: 30     # 每秒最多请求数
@@ -112,7 +122,7 @@ url_fetch:
     
     uro:
       enabled: true
-      timeout: auto      # 自动计算（每 100 个 URL 约 1 秒），范围 30 ~ 300 秒
+      # timeout: auto    # 自动计算（每 100 个 URL 约 1 秒），范围 30 ~ 300 秒
       # whitelist:       # 只保留指定扩展名
       #   - php
       #   - asp
@@ -126,7 +136,7 @@ url_fetch:
     
     httpx:
       enabled: true
-      timeout: auto          # 自动计算（每个 URL 约 1 秒）
+      # timeout: auto        # 自动计算（每个 URL 约 1 秒）
       # threads: 50          # 并发线程数（默认 50）
       # rate-limit: 150      # 每秒请求数（默认 150）
       # request-timeout: 10  # 单个请求超时秒数（默认 10）
@@ -137,18 +147,18 @@ vuln_scan:
   tools:
     dalfox_xss:
       enabled: true
-      timeout: auto          # 自动计算（endpoints 行数 × 100 秒）
-      request-timeout: 10    # 单个请求超时秒数
+      # timeout: auto        # 自动计算（endpoints 行数 × 100 秒）
+      request-timeout: 10  # 单个请求超时秒数
       only-poc: r            # 只输出 POC 结果（r: 反射型）
       ignore-return: "302,404,403"  # 忽略的返回码
-      delay: 100             # 扫描内部延迟
-      worker: 10             # worker 数量
+      delay: 50            # 请求间隔（毫秒）
+      worker: 30             # worker 数量
       user-agent: "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36"
       # blind-xss-server: xxx  # 盲打 XSS 回连服务地址
 
     nuclei:
       enabled: true
-      timeout: auto          # 自动计算（根据 endpoints 行数）
+      # timeout: auto        # 自动计算（根据 endpoints 行数）
       template-repo-names:   # 模板仓库列表，对应「Nuclei 模板」中的仓库名
         - nuclei-templates
         # - nuclei-custom    # 可追加自定义仓库

backend/apps/scan/flows/__init__.py

@@ -5,8 +5,10 @@
 
 from .initiate_scan_flow import initiate_scan_flow
 from .subdomain_discovery_flow import subdomain_discovery_flow
+from .fingerprint_detect_flow import fingerprint_detect_flow
 
 __all__ = [
     'initiate_scan_flow',
     'subdomain_discovery_flow',
+    'fingerprint_detect_flow',
 ]

backend/apps/scan/flows/directory_scan_flow.py

@@ -5,7 +5,7 @@
 
 架构：
 - Flow 负责编排多个原子 Task
-- 支持串行执行扫描工具（流式处理）
+- 支持并发执行扫描工具（使用 ThreadPoolTaskRunner）
 - 每个 Task 可独立重试
 - 配置由 YAML 解析
 """
@@ -14,11 +14,15 @@
 from apps.common.prefect_django_setup import setup_django_for_prefect
 
 from prefect import flow
+from prefect.task_runners import ThreadPoolTaskRunner
 
+import hashlib
 import logging
 import os
 import subprocess
+from datetime import datetime
 from pathlib import Path
+from typing import List, Tuple
 
 from apps.scan.tasks.directory_scan import (
     export_sites_task,
@@ -33,6 +37,9 @@ from apps.scan.utils import config_parser, build_scan_command, ensure_wordlist_l
 
 logger = logging.getLogger(__name__)
 
+# 默认最大并发数
+DEFAULT_MAX_WORKERS = 5
+
 
 def calculate_directory_scan_timeout(
     tool_config: dict,
@@ -112,36 +119,37 @@ def calculate_directory_scan_timeout(
         return min_timeout
 
 
-def _setup_directory_scan_directory(scan_workspace_dir: str) -> Path:
+def _get_max_workers(tool_config: dict, default: int = DEFAULT_MAX_WORKERS) -> int:
     """
-    创建并验证目录扫描工作目录
+    从单个工具配置中获取 max_workers 参数
     
     Args:
-        scan_workspace_dir: 扫描工作空间目录
+        tool_config: 单个工具的配置字典，如 {'max_workers': 10, 'threads': 5, ...}
+        default: 默认值，默认为 5
         
     Returns:
-        Path: 目录扫描目录路径
-        
-    Raises:
-        RuntimeError: 目录创建或验证失败
+        int: max_workers 值
     """
-    directory_scan_dir = Path(scan_workspace_dir) / 'directory_scan'
-    directory_scan_dir.mkdir(parents=True, exist_ok=True)
+    if not isinstance(tool_config, dict):
+        return default
     
-    if not directory_scan_dir.is_dir():
-        raise RuntimeError(f"目录扫描目录创建失败: {directory_scan_dir}")
-    if not os.access(directory_scan_dir, os.W_OK):
-        raise RuntimeError(f"目录扫描目录不可写: {directory_scan_dir}")
-    
-    return directory_scan_dir
+    # 支持 max_workers 和 max-workers（YAML 中划线会被转换）
+    max_workers = tool_config.get('max_workers') or tool_config.get('max-workers')
+    if max_workers is not None and isinstance(max_workers, int) and max_workers > 0:
+        return max_workers
+    return default
 
 
-def _export_site_urls(target_id: int, directory_scan_dir: Path) -> tuple[str, int]:
+
+
+
+def _export_site_urls(target_id: int, target_name: str, directory_scan_dir: Path) -> tuple[str, int]:
     """
-    导出目标下的所有站点 URL 到文件
+    导出目标下的所有站点 URL 到文件（支持懒加载）
     
     Args:
         target_id: 目标 ID
+        target_name: 目标名称（用于懒加载创建默认站点）
         directory_scan_dir: 目录扫描目录
         
     Returns:
@@ -185,7 +193,7 @@ def _run_scans_sequentially(
     target_name: str
 ) -> tuple[int, int, list]:
     """
-    串行执行目录扫描任务（支持多工具）
+    串行执行目录扫描任务（支持多工具）- 已废弃，保留用于兼容
     
     Args:
         enabled_tools: 启用的工具配置字典
@@ -333,6 +341,198 @@ def _run_scans_sequentially(
     return total_directories, processed_count, failed_sites
 
 
+def _generate_log_filename(tool_name: str, site_url: str, directory_scan_dir: Path) -> Path:
+    """
+    生成唯一的日志文件名
+    
+    使用 URL 的 hash 确保并发时不会冲突
+    
+    Args:
+        tool_name: 工具名称
+        site_url: 站点 URL
+        directory_scan_dir: 目录扫描目录
+        
+    Returns:
+        Path: 日志文件路径
+    """
+    url_hash = hashlib.md5(site_url.encode()).hexdigest()[:8]
+    timestamp = datetime.now().strftime('%Y%m%d_%H%M%S_%f')
+    return directory_scan_dir / f"{tool_name}_{url_hash}_{timestamp}.log"
+
+
+def _run_scans_concurrently(
+    enabled_tools: dict,
+    sites_file: str,
+    directory_scan_dir: Path,
+    scan_id: int,
+    target_id: int,
+    site_count: int,
+    target_name: str
+) -> Tuple[int, int, List[str]]:
+    """
+    并发执行目录扫描任务（使用 ThreadPoolTaskRunner）
+    
+    Args:
+        enabled_tools: 启用的工具配置字典
+        sites_file: 站点文件路径
+        directory_scan_dir: 目录扫描目录
+        scan_id: 扫描任务 ID
+        target_id: 目标 ID
+        site_count: 站点数量
+        target_name: 目标名称（用于错误日志）
+        
+    Returns:
+        tuple: (total_directories, processed_sites, failed_sites)
+    """
+    # 读取站点列表
+    sites: List[str] = []
+    with open(sites_file, 'r', encoding='utf-8') as f:
+        for line in f:
+            site_url = line.strip()
+            if site_url:
+                sites.append(site_url)
+    
+    if not sites:
+        logger.warning("站点列表为空")
+        return 0, 0, []
+    
+    logger.info(
+        "准备并发扫描 %d 个站点，使用工具: %s",
+        len(sites), ', '.join(enabled_tools.keys())
+    )
+    
+    total_directories = 0
+    processed_sites_count = 0
+    failed_sites: List[str] = []
+    
+    # 遍历每个工具
+    for tool_name, tool_config in enabled_tools.items():
+        # 每个工具独立获取 max_workers 配置
+        max_workers = _get_max_workers(tool_config)
+        
+        logger.info("="*60)
+        logger.info("使用工具: %s (并发模式, max_workers=%d)", tool_name, max_workers)
+        logger.info("="*60)
+
+        # 如果配置了 wordlist_name，则先确保本地存在对应的字典文件（含 hash 校验）
+        wordlist_name = tool_config.get('wordlist_name')
+        if wordlist_name:
+            try:
+                local_wordlist_path = ensure_wordlist_local(wordlist_name)
+                tool_config['wordlist'] = local_wordlist_path
+            except Exception as exc:
+                logger.error("为工具 %s 准备字典失败: %s", tool_name, exc)
+                # 当前工具无法执行，将所有站点视为失败，继续下一个工具
+                failed_sites.extend(sites)
+                continue
+        
+        # 计算超时时间（所有站点共用）
+        site_timeout = tool_config.get('timeout', 300)
+        if site_timeout == 'auto':
+            site_timeout = calculate_directory_scan_timeout(tool_config)
+            logger.info(f"✓ 工具 {tool_name} 动态计算 timeout: {site_timeout}秒")
+        
+        # 准备所有站点的扫描参数
+        scan_params_list = []
+        for idx, site_url in enumerate(sites, 1):
+            try:
+                command = build_scan_command(
+                    tool_name=tool_name,
+                    scan_type='directory_scan',
+                    command_params={'url': site_url},
+                    tool_config=tool_config
+                )
+                log_file = _generate_log_filename(tool_name, site_url, directory_scan_dir)
+                scan_params_list.append({
+                    'idx': idx,
+                    'site_url': site_url,
+                    'command': command,
+                    'log_file': str(log_file),
+                    'timeout': site_timeout
+                })
+            except Exception as e:
+                logger.error(
+                    "✗ [%d/%d] 构建 %s 命令失败: %s - 站点: %s",
+                    idx, len(sites), tool_name, e, site_url
+                )
+                failed_sites.append(site_url)
+        
+        if not scan_params_list:
+            logger.warning("没有有效的扫描任务")
+            continue
+        
+        # ============================================================
+        # 分批执行策略：控制实际并发的 ffuf 进程数
+        # ============================================================
+        total_tasks = len(scan_params_list)
+        logger.info("开始分批执行 %d 个扫描任务（每批 %d 个）...", total_tasks, max_workers)
+        
+        batch_num = 0
+        for batch_start in range(0, total_tasks, max_workers):
+            batch_end = min(batch_start + max_workers, total_tasks)
+            batch_params = scan_params_list[batch_start:batch_end]
+            batch_num += 1
+            
+            logger.info("执行第 %d 批任务（%d-%d/%d）...", batch_num, batch_start + 1, batch_end, total_tasks)
+            
+            # 提交当前批次的任务（非阻塞，立即返回 future）
+            futures = []
+            for params in batch_params:
+                future = run_and_stream_save_directories_task.submit(
+                    cmd=params['command'],
+                    tool_name=tool_name,
+                    scan_id=scan_id,
+                    target_id=target_id,
+                    site_url=params['site_url'],
+                    cwd=str(directory_scan_dir),
+                    shell=True,
+                    batch_size=1000,
+                    timeout=params['timeout'],
+                    log_file=params['log_file']
+                )
+                futures.append((params['idx'], params['site_url'], future))
+            
+            # 等待当前批次所有任务完成（阻塞，确保本批完成后再启动下一批）
+            for idx, site_url, future in futures:
+                try:
+                    result = future.result()  # 阻塞等待单个任务完成
+                    directories_found = result.get('created_directories', 0)
+                    total_directories += directories_found
+                    processed_sites_count += 1
+                    
+                    logger.info(
+                        "✓ [%d/%d] 站点扫描完成: %s - 发现 %d 个目录",
+                        idx, len(sites), site_url, directories_found
+                    )
+                    
+                except Exception as exc:
+                    failed_sites.append(site_url)
+                    if 'timeout' in str(exc).lower() or isinstance(exc, subprocess.TimeoutExpired):
+                        logger.warning(
+                            "⚠️ [%d/%d] 站点扫描超时: %s - 错误: %s",
+                            idx, len(sites), site_url, exc
+                        )
+                    else:
+                        logger.error(
+                            "✗ [%d/%d] 站点扫描失败: %s - 错误: %s",
+                            idx, len(sites), site_url, exc
+                        )
+    
+    # 输出汇总信息
+    if failed_sites:
+        logger.warning(
+            "部分站点扫描失败: %d/%d",
+            len(failed_sites), len(sites)
+        )
+    
+    logger.info(
+        "✓ 并发目录扫描执行完成 - 成功: %d/%d, 失败: %d, 总目录数: %d",
+        processed_sites_count, len(sites), len(failed_sites), total_directories
+    )
+    
+    return total_directories, processed_sites_count, failed_sites
+
+
 @flow(
     name="directory_scan", 
     log_prints=True,
@@ -359,7 +559,7 @@ def directory_scan_flow(
         Step 0: 创建工作目录
         Step 1: 导出站点 URL 列表到文件（供扫描工具使用）
         Step 2: 验证工具配置
-        Step 3: 串行执行扫描工具并实时保存结果
+        Step 3: 并发执行扫描工具并实时保存结果（使用 ThreadPoolTaskRunner）
     
     ffuf 输出字段：
         - url: 发现的目录/文件 URL
@@ -418,10 +618,11 @@ def directory_scan_flow(
             raise ValueError("enabled_tools 不能为空")
         
         # Step 0: 创建工作目录
-        directory_scan_dir = _setup_directory_scan_directory(scan_workspace_dir)
+        from apps.scan.utils import setup_scan_directory
+        directory_scan_dir = setup_scan_directory(scan_workspace_dir, 'directory_scan')
         
-        # Step 1: 导出站点 URL
-        sites_file, site_count = _export_site_urls(target_id, directory_scan_dir)
+        # Step 1: 导出站点 URL（支持懒加载）
+        sites_file, site_count = _export_site_urls(target_id, target_name, directory_scan_dir)
         
         if site_count == 0:
             logger.warning("目标下没有站点，跳过目录扫描")
@@ -440,14 +641,15 @@ def directory_scan_flow(
         
         # Step 2: 工具配置信息
         logger.info("Step 2: 工具配置信息")
-        logger.info(
-            "✓ 启用工具: %s",
-            ', '.join(enabled_tools.keys())
-        )
+        tool_info = []
+        for tool_name, tool_config in enabled_tools.items():
+            mw = _get_max_workers(tool_config)
+            tool_info.append(f"{tool_name}(max_workers={mw})")
+        logger.info("✓ 启用工具: %s", ', '.join(tool_info))
         
-        # Step 3: 串行执行扫描工具并实时保存结果
-        logger.info("Step 3: 串行执行扫描工具并实时保存结果")
-        total_directories, processed_sites, failed_sites = _run_scans_sequentially(
+        # Step 3: 并发执行扫描工具并实时保存结果
+        logger.info("Step 3: 并发执行扫描工具并实时保存结果")
+        total_directories, processed_sites, failed_sites = _run_scans_concurrently(
             enabled_tools=enabled_tools,
             sites_file=sites_file,
             directory_scan_dir=directory_scan_dir,

backend/apps/scan/flows/fingerprint_detect_flow.py

@@ -0,0 +1,380 @@
+"""
+指纹识别 Flow
+
+负责编排指纹识别的完整流程
+
+架构：
+- Flow 负责编排多个原子 Task
+- 在 site_scan 后串行执行
+- 使用 xingfinger 工具识别技术栈
+- 流式处理输出，批量更新数据库
+"""
+
+# Django 环境初始化（导入即生效）
+from apps.common.prefect_django_setup import setup_django_for_prefect
+
+import logging
+import os
+from datetime import datetime
+from pathlib import Path
+
+from prefect import flow
+
+from apps.scan.handlers.scan_flow_handlers import (
+    on_scan_flow_running,
+    on_scan_flow_completed,
+    on_scan_flow_failed,
+)
+from apps.scan.tasks.fingerprint_detect import (
+    export_urls_for_fingerprint_task,
+    run_xingfinger_and_stream_update_tech_task,
+)
+from apps.scan.utils import build_scan_command
+from apps.scan.utils.fingerprint_helpers import get_fingerprint_paths
+
+logger = logging.getLogger(__name__)
+
+
+def calculate_fingerprint_detect_timeout(
+    url_count: int,
+    base_per_url: float = 3.0,
+    min_timeout: int = 60
+) -> int:
+    """
+    根据 URL 数量计算超时时间
+    
+    公式：超时时间 = URL 数量 × 每 URL 基础时间
+    最小值：60秒
+    无上限
+    
+    Args:
+        url_count: URL 数量
+        base_per_url: 每 URL 基础时间（秒），默认 3秒
+        min_timeout: 最小超时时间（秒），默认 60秒
+        
+    Returns:
+        int: 计算出的超时时间（秒）
+        
+    示例：
+        100 URL × 3秒 = 300秒
+        1000 URL × 3秒 = 3000秒（50分钟）
+        10000 URL × 3秒 = 30000秒（8.3小时）
+    """
+    timeout = int(url_count * base_per_url)
+    return max(min_timeout, timeout)
+
+
+
+
+
+def _export_urls(
+    target_id: int,
+    fingerprint_dir: Path,
+    source: str = 'website'
+) -> tuple[str, int]:
+    """
+    导出 URL 到文件
+    
+    Args:
+        target_id: 目标 ID
+        fingerprint_dir: 指纹识别目录
+        source: 数据源类型
+        
+    Returns:
+        tuple: (urls_file, total_count)
+    """
+    logger.info("Step 1: 导出 URL 列表 (source=%s)", source)
+    
+    urls_file = str(fingerprint_dir / 'urls.txt')
+    export_result = export_urls_for_fingerprint_task(
+        target_id=target_id,
+        output_file=urls_file,
+        source=source,
+        batch_size=1000
+    )
+    
+    total_count = export_result['total_count']
+    
+    logger.info(
+        "✓ URL 导出完成 - 文件: %s, 数量: %d",
+        export_result['output_file'],
+        total_count
+    )
+    
+    return export_result['output_file'], total_count
+
+
+def _run_fingerprint_detect(
+    enabled_tools: dict,
+    urls_file: str,
+    url_count: int,
+    fingerprint_dir: Path,
+    scan_id: int,
+    target_id: int,
+    source: str
+) -> tuple[dict, list]:
+    """
+    执行指纹识别任务
+    
+    Args:
+        enabled_tools: 已启用的工具配置字典
+        urls_file: URL 文件路径
+        url_count: URL 总数
+        fingerprint_dir: 指纹识别目录
+        scan_id: 扫描任务 ID
+        target_id: 目标 ID
+        source: 数据源类型
+        
+    Returns:
+        tuple: (tool_stats, failed_tools)
+    """
+    tool_stats = {}
+    failed_tools = []
+    
+    for tool_name, tool_config in enabled_tools.items():
+        # 1. 获取指纹库路径
+        lib_names = tool_config.get('fingerprint_libs', ['ehole'])
+        fingerprint_paths = get_fingerprint_paths(lib_names)
+        
+        if not fingerprint_paths:
+            reason = f"没有可用的指纹库: {lib_names}"
+            logger.warning(reason)
+            failed_tools.append({'tool': tool_name, 'reason': reason})
+            continue
+        
+        # 2. 将指纹库路径合并到 tool_config（用于命令构建）
+        tool_config_with_paths = {**tool_config, **fingerprint_paths}
+        
+        # 3. 构建命令
+        try:
+            command = build_scan_command(
+                tool_name=tool_name,
+                scan_type='fingerprint_detect',
+                command_params={
+                    'urls_file': urls_file
+                },
+                tool_config=tool_config_with_paths
+            )
+        except Exception as e:
+            reason = f"命令构建失败: {str(e)}"
+            logger.error("构建 %s 命令失败: %s", tool_name, e)
+            failed_tools.append({'tool': tool_name, 'reason': reason})
+            continue
+        
+        # 4. 计算超时时间
+        timeout = calculate_fingerprint_detect_timeout(url_count)
+        
+        # 5. 生成日志文件路径
+        timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
+        log_file = fingerprint_dir / f"{tool_name}_{timestamp}.log"
+        
+        logger.info(
+            "开始执行 %s 指纹识别 - URL数: %d, 超时: %ds, 指纹库: %s",
+            tool_name, url_count, timeout, list(fingerprint_paths.keys())
+        )
+        
+        # 6. 执行扫描任务
+        try:
+            result = run_xingfinger_and_stream_update_tech_task(
+                cmd=command,
+                tool_name=tool_name,
+                scan_id=scan_id,
+                target_id=target_id,
+                source=source,
+                cwd=str(fingerprint_dir),
+                timeout=timeout,
+                log_file=str(log_file),
+                batch_size=100
+            )
+            
+            tool_stats[tool_name] = {
+                'command': command,
+                'result': result,
+                'timeout': timeout,
+                'fingerprint_libs': list(fingerprint_paths.keys())
+            }
+            
+            logger.info(
+                "✓ 工具 %s 执行完成 - 处理记录: %d, 更新: %d, 未找到: %d",
+                tool_name,
+                result.get('processed_records', 0),
+                result.get('updated_count', 0),
+                result.get('not_found_count', 0)
+            )
+            
+        except Exception as exc:
+            failed_tools.append({'tool': tool_name, 'reason': str(exc)})
+            logger.error("工具 %s 执行失败: %s", tool_name, exc, exc_info=True)
+    
+    if failed_tools:
+        logger.warning(
+            "以下指纹识别工具执行失败: %s",
+            ', '.join([f['tool'] for f in failed_tools])
+        )
+    
+    return tool_stats, failed_tools
+
+
+@flow(
+    name="fingerprint_detect",
+    log_prints=True,
+    on_running=[on_scan_flow_running],
+    on_completion=[on_scan_flow_completed],
+    on_failure=[on_scan_flow_failed],
+)
+def fingerprint_detect_flow(
+    scan_id: int,
+    target_name: str,
+    target_id: int,
+    scan_workspace_dir: str,
+    enabled_tools: dict
+) -> dict:
+    """
+    指纹识别 Flow
+    
+    主要功能：
+        1. 从数据库导出目标下所有 WebSite URL 到文件
+        2. 使用 xingfinger 进行技术栈识别
+        3. 解析结果并更新 WebSite.tech 字段（合并去重）
+    
+    工作流程：
+        Step 0: 创建工作目录
+        Step 1: 导出 URL 列表
+        Step 2: 解析配置，获取启用的工具
+        Step 3: 执行 xingfinger 并解析结果
+    
+    Args:
+        scan_id: 扫描任务 ID
+        target_name: 目标名称
+        target_id: 目标 ID
+        scan_workspace_dir: 扫描工作空间目录
+        enabled_tools: 启用的工具配置（xingfinger）
+        
+    Returns:
+        dict: {
+            'success': bool,
+            'scan_id': int,
+            'target': str,
+            'scan_workspace_dir': str,
+            'urls_file': str,
+            'url_count': int,
+            'processed_records': int,
+            'updated_count': int,
+            'not_found_count': int,
+            'executed_tasks': list,
+            'tool_stats': dict
+        }
+    """
+    try:
+        logger.info(
+            "="*60 + "\n" +
+            "开始指纹识别\n" +
+            f"  Scan ID: {scan_id}\n" +
+            f"  Target: {target_name}\n" +
+            f"  Workspace: {scan_workspace_dir}\n" +
+            "="*60
+        )
+        
+        # 参数验证
+        if scan_id is None:
+            raise ValueError("scan_id 不能为空")
+        if not target_name:
+            raise ValueError("target_name 不能为空")
+        if target_id is None:
+            raise ValueError("target_id 不能为空")
+        if not scan_workspace_dir:
+            raise ValueError("scan_workspace_dir 不能为空")
+        
+        # 数据源类型（当前只支持 website）
+        source = 'website'
+        
+        # Step 0: 创建工作目录
+        from apps.scan.utils import setup_scan_directory
+        fingerprint_dir = setup_scan_directory(scan_workspace_dir, 'fingerprint_detect')
+        
+        # Step 1: 导出 URL（支持懒加载）
+        urls_file, url_count = _export_urls(target_id, fingerprint_dir, source)
+        
+        if url_count == 0:
+            logger.warning("目标下没有可用的 URL，跳过指纹识别")
+            return {
+                'success': True,
+                'scan_id': scan_id,
+                'target': target_name,
+                'scan_workspace_dir': scan_workspace_dir,
+                'urls_file': urls_file,
+                'url_count': 0,
+                'processed_records': 0,
+                'updated_count': 0,
+                'created_count': 0,
+                'executed_tasks': ['export_urls_for_fingerprint'],
+                'tool_stats': {
+                    'total': 0,
+                    'successful': 0,
+                    'failed': 0,
+                    'successful_tools': [],
+                    'failed_tools': [],
+                    'details': {}
+                }
+            }
+        
+        # Step 2: 工具配置信息
+        logger.info("Step 2: 工具配置信息")
+        logger.info("✓ 启用工具: %s", ', '.join(enabled_tools.keys()))
+        
+        # Step 3: 执行指纹识别
+        logger.info("Step 3: 执行指纹识别")
+        tool_stats, failed_tools = _run_fingerprint_detect(
+            enabled_tools=enabled_tools,
+            urls_file=urls_file,
+            url_count=url_count,
+            fingerprint_dir=fingerprint_dir,
+            scan_id=scan_id,
+            target_id=target_id,
+            source=source
+        )
+        
+        logger.info("="*60 + "\n✓ 指纹识别完成\n" + "="*60)
+        
+        # 动态生成已执行的任务列表
+        executed_tasks = ['export_urls_for_fingerprint']
+        executed_tasks.extend([f'run_xingfinger ({tool})' for tool in tool_stats.keys()])
+        
+        # 汇总所有工具的结果
+        total_processed = sum(stats['result'].get('processed_records', 0) for stats in tool_stats.values())
+        total_updated = sum(stats['result'].get('updated_count', 0) for stats in tool_stats.values())
+        total_created = sum(stats['result'].get('created_count', 0) for stats in tool_stats.values())
+        
+        successful_tools = [name for name in enabled_tools.keys() 
+                           if name not in [f['tool'] for f in failed_tools]]
+        
+        return {
+            'success': True,
+            'scan_id': scan_id,
+            'target': target_name,
+            'scan_workspace_dir': scan_workspace_dir,
+            'urls_file': urls_file,
+            'url_count': url_count,
+            'processed_records': total_processed,
+            'updated_count': total_updated,
+            'created_count': total_created,
+            'executed_tasks': executed_tasks,
+            'tool_stats': {
+                'total': len(enabled_tools),
+                'successful': len(successful_tools),
+                'failed': len(failed_tools),
+                'successful_tools': successful_tools,
+                'failed_tools': failed_tools,
+                'details': tool_stats
+            }
+        }
+        
+    except ValueError as e:
+        logger.error("配置错误: %s", e)
+        raise
+    except RuntimeError as e:
+        logger.error("运行时错误: %s", e)
+        raise
+    except Exception as e:
+        logger.exception("指纹识别失败: %s", e)
+        raise

backend/apps/scan/flows/initiate_scan_flow.py

@@ -30,7 +30,7 @@ from apps.scan.handlers import (
     on_initiate_scan_flow_failed,
 )
 from prefect.futures import wait
-from apps.scan.tasks.workspace_tasks import create_scan_workspace_task
+from apps.scan.utils import setup_scan_workspace
 from apps.scan.orchestrators import FlowOrchestrator
 
 logger = logging.getLogger(__name__)
@@ -110,7 +110,7 @@ def initiate_scan_flow(
         )
         
         # ==================== Task 1: 创建 Scan 工作空间 ====================
-        scan_workspace_path = create_scan_workspace_task(scan_workspace_dir)
+        scan_workspace_path = setup_scan_workspace(scan_workspace_dir)
         
         # ==================== Task 2: 获取引擎配置 ====================
         from apps.scan.models import Scan

backend/apps/scan/flows/port_scan_flow.py

@@ -154,28 +154,7 @@ def _parse_port_count(tool_config: dict) -> int:
     return 100
 
 
-def _setup_port_scan_directory(scan_workspace_dir: str) -> Path:
-    """
-    创建并验证端口扫描工作目录
-    
-    Args:
-        scan_workspace_dir: 扫描工作空间目录
-        
-    Returns:
-        Path: 端口扫描目录路径
-        
-    Raises:
-        RuntimeError: 目录创建或验证失败
-    """
-    port_scan_dir = Path(scan_workspace_dir) / 'port_scan'
-    port_scan_dir.mkdir(parents=True, exist_ok=True)
-    
-    if not port_scan_dir.is_dir():
-        raise RuntimeError(f"端口扫描目录创建失败: {port_scan_dir}")
-    if not os.access(port_scan_dir, os.W_OK):
-        raise RuntimeError(f"端口扫描目录不可写: {port_scan_dir}")
-    
-    return port_scan_dir
+
 
 
 def _export_scan_targets(target_id: int, port_scan_dir: Path) -> tuple[str, int, str]:
@@ -442,7 +421,8 @@ def port_scan_flow(
         )
         
         # Step 0: 创建工作目录
-        port_scan_dir = _setup_port_scan_directory(scan_workspace_dir)
+        from apps.scan.utils import setup_scan_directory
+        port_scan_dir = setup_scan_directory(scan_workspace_dir, 'port_scan')
         
         # Step 1: 导出扫描目标列表到文件（根据 Target 类型自动决定内容）
         targets_file, target_count, target_type = _export_scan_targets(target_id, port_scan_dir)

backend/apps/scan/flows/site_scan_flow.py

@@ -34,7 +34,8 @@ logger = logging.getLogger(__name__)
 def calculate_timeout_by_line_count(
     tool_config: dict,
     file_path: str, 
-    base_per_time: int = 1
+    base_per_time: int = 1,
+    min_timeout: int = 60
 ) -> int:
     """
     根据文件行数计算 timeout
@@ -45,9 +46,10 @@ def calculate_timeout_by_line_count(
         tool_config: 工具配置字典（此函数未使用，但保持接口一致性）
         file_path: 要统计行数的文件路径
         base_per_time: 每行的基础时间（秒），默认1秒
+        min_timeout: 最小超时时间（秒），默认60秒
     
     Returns:
-        int: 计算出的超时时间（秒）
+        int: 计算出的超时时间（秒），不低于 min_timeout
     
     Example:
         timeout = calculate_timeout_by_line_count(
@@ -67,53 +69,33 @@ def calculate_timeout_by_line_count(
         # wc -l 输出格式：行数 + 空格 + 文件名
         line_count = int(result.stdout.strip().split()[0])
         
-        # 计算 timeout：行数 × 每行基础时间
-        timeout = line_count * base_per_time
+        # 计算 timeout：行数 × 每行基础时间，不低于最小值
+        timeout = max(line_count * base_per_time, min_timeout)
         
         logger.info(
             f"timeout 自动计算: 文件={file_path}, "
-            f"行数={line_count}, 每行时间={base_per_time}秒, timeout={timeout}秒"
+            f"行数={line_count}, 每行时间={base_per_time}秒, 最小值={min_timeout}秒, timeout={timeout}秒"
         )
         
         return timeout
         
     except Exception as e:
         # 如果 wc -l 失败，使用默认值
-        logger.warning(f"wc -l 计算行数失败: {e}，使用默认 timeout: 600秒")
-        return 600
+        logger.warning(f"wc -l 计算行数失败: {e}，使用默认 timeout: {min_timeout}秒")
+        return min_timeout
 
 
-def _setup_site_scan_directory(scan_workspace_dir: str) -> Path:
-    """
-    创建并验证站点扫描工作目录
-    
-    Args:
-        scan_workspace_dir: 扫描工作空间目录
-        
-    Returns:
-        Path: 站点扫描目录路径
-        
-    Raises:
-        RuntimeError: 目录创建或验证失败
-    """
-    site_scan_dir = Path(scan_workspace_dir) / 'site_scan'
-    site_scan_dir.mkdir(parents=True, exist_ok=True)
-    
-    if not site_scan_dir.is_dir():
-        raise RuntimeError(f"站点扫描目录创建失败: {site_scan_dir}")
-    if not os.access(site_scan_dir, os.W_OK):
-        raise RuntimeError(f"站点扫描目录不可写: {site_scan_dir}")
-    
-    return site_scan_dir
 
 
-def _export_site_urls(target_id: int, site_scan_dir: Path) -> tuple[str, int, int]:
+
+def _export_site_urls(target_id: int, site_scan_dir: Path, target_name: str = None) -> tuple[str, int, int]:
     """
     导出站点 URL 到文件
     
     Args:
         target_id: 目标 ID
         site_scan_dir: 站点扫描目录
+        target_name: 目标名称（用于懒加载时写入默认值）
         
     Returns:
         tuple: (urls_file, total_urls, association_count)
@@ -399,11 +381,12 @@ def site_scan_flow(
             raise ValueError("scan_workspace_dir 不能为空")
         
         # Step 0: 创建工作目录
-        site_scan_dir = _setup_site_scan_directory(scan_workspace_dir)
+        from apps.scan.utils import setup_scan_directory
+        site_scan_dir = setup_scan_directory(scan_workspace_dir, 'site_scan')
         
         # Step 1: 导出站点 URL
         urls_file, total_urls, association_count = _export_site_urls(
-            target_id, site_scan_dir
+            target_id, site_scan_dir, target_name
         )
         
         if total_urls == 0:

backend/apps/scan/flows/subdomain_discovery_flow.py

@@ -41,28 +41,7 @@ import subprocess
 logger = logging.getLogger(__name__)
 
 
-def _setup_subdomain_directory(scan_workspace_dir: str) -> Path:
-    """
-    创建并验证子域名扫描工作目录
-    
-    Args:
-        scan_workspace_dir: 扫描工作空间目录
-        
-    Returns:
-        Path: 子域名扫描目录路径
-        
-    Raises:
-        RuntimeError: 目录创建或验证失败
-    """
-    result_dir = Path(scan_workspace_dir) / 'subdomain_discovery'
-    result_dir.mkdir(parents=True, exist_ok=True)
-    
-    if not result_dir.is_dir():
-        raise RuntimeError(f"子域名扫描目录创建失败: {result_dir}")
-    if not os.access(result_dir, os.W_OK):
-        raise RuntimeError(f"子域名扫描目录不可写: {result_dir}")
-    
-    return result_dir
+
 
 
 def _validate_and_normalize_target(target_name: str) -> str:
@@ -119,12 +98,7 @@ def _run_scans_parallel(
     
     # 生成时间戳（所有工具共用）
     timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
-    
-    # TODO: 接入代理池管理系统
-    # from apps.proxy.services import proxy_pool
-    # proxy_stats = proxy_pool.get_stats()
-    # logger.info(f"代理池状态: {proxy_stats['healthy']}/{proxy_stats['total']} 可用")
-    
+
     failures = []  # 记录命令构建失败的工具
     futures = {}
     
@@ -352,6 +326,10 @@ def subdomain_discovery_flow(
         Stage 4: DNS 存活验证（可选） - 通用存活验证
         Final: 保存到数据库
     
+    注意：
+        - 子域名发现只对 DOMAIN 类型目标有意义
+        - IP 和 CIDR 类型目标会自动跳过
+    
     Args:
         scan_id: 扫描任务 ID
         target_name: 目标名称（域名）
@@ -390,6 +368,21 @@ def subdomain_discovery_flow(
             logger.warning("未提供目标域名，跳过子域名发现扫描")
             return _empty_result(scan_id, '', scan_workspace_dir)
         
+        # ==================== 检查 Target 类型 ====================
+        # 子域名发现只对 DOMAIN 类型有意义，IP 和 CIDR 类型跳过
+        from apps.targets.services import TargetService
+        from apps.targets.models import Target
+        
+        target_service = TargetService()
+        target = target_service.get_target(target_id)
+        
+        if target and target.type != Target.TargetType.DOMAIN:
+            logger.info(
+                "跳过子域名发现扫描: Target 类型为 %s (ID=%d, Name=%s)，子域名发现仅适用于域名类型",
+                target.type, target_id, target_name
+            )
+            return _empty_result(scan_id, target_name, scan_workspace_dir)
+        
         # 导入任务函数
         from apps.scan.tasks.subdomain_discovery import (
             run_subdomain_discovery_task,
@@ -398,7 +391,8 @@ def subdomain_discovery_flow(
         )
         
         # Step 0: 准备工作
-        result_dir = _setup_subdomain_directory(scan_workspace_dir)
+        from apps.scan.utils import setup_scan_directory
+        result_dir = setup_scan_directory(scan_workspace_dir, 'subdomain_discovery')
         
         # 验证并规范化目标域名
         try:

backend/apps/scan/flows/url_fetch/__init__.py

@@ -4,18 +4,15 @@ URL Fetch Flow 模块
 提供 URL 获取相关的 Flow：
 - url_fetch_flow: 主 Flow（按输入类型编排 + 统一后处理）
 - domain_name_url_fetch_flow: 基于 domain_name（来自 target_name）输入的 URL 获取子 Flow（如 waymore）
-- domains_url_fetch_flow: 基于 domains_file 输入的 URL 获取子 Flow（如 gau、waybackurls）
 - sites_url_fetch_flow: 基于 sites_file 输入的 URL 获取子 Flow（如 katana 等爬虫）
 """
 
 from .main_flow import url_fetch_flow
 from .domain_name_url_fetch_flow import domain_name_url_fetch_flow
-from .domains_url_fetch_flow import domains_url_fetch_flow
 from .sites_url_fetch_flow import sites_url_fetch_flow
 
 __all__ = [
     'url_fetch_flow',
     'domain_name_url_fetch_flow',
-    'domains_url_fetch_flow',
     'sites_url_fetch_flow',
 ]

backend/apps/scan/flows/url_fetch/domain_name_url_fetch_flow.py

@@ -1,9 +1,14 @@
 """
-基于 domain_name（域名）的 URL 获取 Flow
+基于 Target 根域名的 URL 被动收集 Flow
 
-主要用于像 waymore 这种按域名输入（input_type = 'domain_name'）的工具：
-- 直接对目标域名（target_name/domain_name）执行 URL 被动收集
-- 不再依赖 domains_file（子域名列表文件）
+用于 waymore 等被动收集工具：
+- 输入：Target 的根域名（target_name，如 example.com）
+- 工具会自动从第三方源（Wayback Machine、Common Crawl 等）查询该域名及其子域名的历史 URL
+- 不需要遍历子域名列表，工具内部会处理 *.example.com
+
+注意：
+- 此 Flow 只对 DOMAIN 类型 Target 有效
+- IP 和 CIDR 类型会自动跳过（被动收集工具不支持）
 """
 
 # Django 环境初始化
@@ -34,18 +39,49 @@ def domain_name_url_fetch_flow(
     domain_name_tools: Dict[str, dict],
 ) -> dict:
     """
-    基于 target_name/domain_name 域名执行 URL 获取子 Flow（当前主要用于 waymore）。
+    基于 Target 根域名执行 URL 被动收集（当前主要用于 waymore）
 
     执行流程：
-    1. 校验 target_name 是否为域名
-    2. 使用传入的 domain_name_tools 工具列表
-    3. 为每个工具构建命令并并行执行
+    1. 校验 Target 类型（IP/CIDR 类型跳过）
+    2. 使用传入的工具列表对根域名执行被动收集
+    3. 工具内部会自动查询该域名及其子域名的历史 URL
     4. 汇总结果文件列表
+    
+    Args:
+        scan_id: 扫描 ID
+        target_id: 目标 ID
+        target_name: Target 根域名（如 example.com），不是子域名列表
+        output_dir: 输出目录
+        domain_name_tools: 被动收集工具配置（如 waymore）
+    
+    注意：
+    - 此 Flow 只对 DOMAIN 类型 Target 有效
+    - IP 和 CIDR 类型会自动跳过（waymore 等工具不支持）
+    - 工具会自动收集 *.target_name 的所有历史 URL，无需遍历子域名
     """
     try:
         output_path = Path(output_dir)
         output_path.mkdir(parents=True, exist_ok=True)
 
+        # 检查 Target 类型，IP/CIDR 类型跳过
+        from apps.targets.services import TargetService
+        from apps.targets.models import Target
+        
+        target_service = TargetService()
+        target = target_service.get_target(target_id)
+        
+        if target and target.type != Target.TargetType.DOMAIN:
+            logger.info(
+                "跳过 domain_name URL 获取: Target 类型为 %s (ID=%d, Name=%s)，waymore 等工具仅适用于域名类型",
+                target.type, target_id, target_name
+            )
+            return {
+                "success": True,
+                "result_files": [],
+                "failed_tools": [],
+                "successful_tools": [],
+            }
+
         # 复用公共域名校验逻辑，确保 target_name 是合法域名
         validate_domain(target_name)
 

backend/apps/scan/flows/url_fetch/domains_url_fetch_flow.py

@@ -1,139 +0,0 @@
-"""
-URL 被动收集 Flow
-
-从历史归档、搜索引擎等被动来源收集 URL
-工具：waymore, gau, waybackurls 等
-输入：domains_file（子域名列表）
-"""
-
-# Django 环境初始化
-from apps.common.prefect_django_setup import setup_django_for_prefect
-
-import logging
-from pathlib import Path
-
-from prefect import flow
-
-from .utils import run_tools_parallel
-
-logger = logging.getLogger(__name__)
-
-
-def _export_domains_file(target_id: int, scan_id: int, output_dir: Path) -> tuple[str, int]:
-    """
-    导出子域名列表到文件
-    
-    Args:
-        target_id: 目标 ID
-        scan_id: 扫描 ID
-        output_dir: 输出目录
-        
-    Returns:
-        tuple: (file_path, count)
-    """
-    from apps.scan.tasks.url_fetch import export_target_assets_task
-    
-    output_file = str(output_dir / "domains.txt")
-    result = export_target_assets_task(
-        output_file=output_file,
-        target_id=target_id,
-        scan_id=scan_id,
-        input_type="domains_file"
-    )
-    
-    count = result['asset_count']
-    if count == 0:
-        logger.warning("子域名列表为空，被动收集可能无法正常工作")
-    else:
-        logger.info("✓ 子域名列表导出完成 - 数量: %d", count)
-    
-    return output_file, count
-
-
-@flow(name="domains_url_fetch_flow", log_prints=True)
-def domains_url_fetch_flow(
-    scan_id: int,
-    target_id: int,
-    target_name: str,
-    output_dir: str,
-    enabled_tools: dict
-) -> dict:
-    """
-    URL 被动收集子 Flow
-    
-    执行流程：
-    1. 导出子域名列表（domains_file）
-    2. 并行执行被动收集工具
-    3. 返回结果文件列表
-    
-    Args:
-        scan_id: 扫描 ID
-        target_id: 目标 ID
-        target_name: 目标名称
-        output_dir: 输出目录
-        enabled_tools: 启用的被动收集工具配置
-        
-    Returns:
-        dict: {
-            'success': bool,
-            'result_files': list,
-            'failed_tools': list,
-            'successful_tools': list,
-            'domains_count': int
-        }
-    """
-    try:
-        output_path = Path(output_dir)
-        
-        logger.info(
-            "开始 URL 被动收集 - Target: %s, Tools: %s",
-            target_name, ', '.join(enabled_tools.keys())
-        )
-        
-        # Step 1: 导出子域名列表
-        domains_file, domains_count = _export_domains_file(
-            target_id=target_id,
-            scan_id=scan_id,
-            output_dir=output_path
-        )
-        
-        if domains_count == 0:
-            logger.warning("没有可用的子域名，跳过被动收集")
-            return {
-                'success': True,
-                'result_files': [],
-                'failed_tools': [],
-                'successful_tools': [],
-                'domains_count': 0
-            }
-        
-        # Step 2: 并行执行被动收集工具
-        result_files, failed_tools, successful_tools = run_tools_parallel(
-            tools=enabled_tools,
-            input_file=domains_file,
-            input_type="domains_file",
-            output_dir=output_path
-        )
-        
-        logger.info(
-            "✓ 被动收集完成 - 成功: %d/%d, 结果文件: %d",
-            len(successful_tools), len(enabled_tools), len(result_files)
-        )
-        
-        return {
-            'success': True,
-            'result_files': result_files,
-            'failed_tools': failed_tools,
-            'successful_tools': successful_tools,
-            'domains_count': domains_count
-        }
-        
-    except Exception as e:
-        logger.error("URL 被动收集失败: %s", e, exc_info=True)
-        return {
-            'success': False,
-            'result_files': [],
-            'failed_tools': [{'tool': 'domains_url_fetch_flow', 'reason': str(e)}],
-            'successful_tools': [],
-            'domains_count': 0
-        }

backend/apps/scan/flows/url_fetch/main_flow.py

@@ -1,10 +1,10 @@
 """
 URL Fetch 主 Flow
 
-负责编排不同输入类型的 URL 获取子 Flow（domain_name / domains_file / sites_file），以及统一的后处理（uro 去重、httpx 验证）
+负责编排不同输入类型的 URL 获取子 Flow（domain_name / sites_file），以及统一的后处理（uro 去重、httpx 验证）
 
 架构：
-- 调用 domain_name_url_fetch_flow（domain_name 输入）、domains_url_fetch_flow（domains_file 输入）和 sites_url_fetch_flow（sites_file 输入）
+- 调用 domain_name_url_fetch_flow（domain_name 输入）和 sites_url_fetch_flow（sites_file 输入）
 - 合并多个子 Flow 的结果
 - 统一进行 uro 去重（如果启用）
 - 统一进行 httpx 验证（如果启用）
@@ -27,7 +27,6 @@ from apps.scan.handlers.scan_flow_handlers import (
 )
 
 from .domain_name_url_fetch_flow import domain_name_url_fetch_flow
-from .domains_url_fetch_flow import domains_url_fetch_flow
 from .sites_url_fetch_flow import sites_url_fetch_flow
 from .utils import calculate_timeout_by_line_count
 
@@ -37,36 +36,23 @@ logger = logging.getLogger(__name__)
 # ==================== 工具分类配置 ====================
 # 使用 target_name (domain_name) 作为输入的 URL 获取工具
 DOMAIN_NAME_TOOLS = {'waymore'}
-# 使用 domains_file 作为输入的 URL 获取工具
-DOMAINS_FILE_TOOLS = {'gau', 'waybackurls'}
 # 使用 sites_file 作为输入的 URL 获取工具
-SITES_FILE_TOOLS = {'katana', 'gospider', 'hakrawler'}
+SITES_FILE_TOOLS = {'katana'}
 # 后处理工具：不参与获取，用于清理和验证
 POST_PROCESS_TOOLS = {'uro', 'httpx'}
 
 
-def _setup_url_fetch_directory(scan_workspace_dir: str) -> Path:
-    """创建并验证 URL 获取工作目录"""
-    url_fetch_dir = Path(scan_workspace_dir) / 'url_fetch'
-    url_fetch_dir.mkdir(parents=True, exist_ok=True)
-    
-    if not url_fetch_dir.is_dir():
-        raise RuntimeError(f"URL 获取目录创建失败: {url_fetch_dir}")
-    if not os.access(url_fetch_dir, os.W_OK):
-        raise RuntimeError(f"URL 获取目录不可写: {url_fetch_dir}")
-    
-    return url_fetch_dir
 
 
-def _classify_tools(enabled_tools: dict) -> tuple[dict, dict, dict, dict, dict]:
+
+def _classify_tools(enabled_tools: dict) -> tuple[dict, dict, dict, dict]:
     """
     将启用的工具按输入类型分类
     
     Returns:
-        tuple: (domain_name_tools, domains_file_tools, sites_file_tools, uro_config, httpx_config)
+        tuple: (domain_name_tools, sites_file_tools, uro_config, httpx_config)
     """
     domain_name_tools: dict = {}
-    domains_file_tools: dict = {}
     sites_file_tools: dict = {}
     uro_config = None
     httpx_config = None
@@ -74,8 +60,6 @@ def _classify_tools(enabled_tools: dict) -> tuple[dict, dict, dict, dict, dict]:
     for tool_name, tool_config in enabled_tools.items():
         if tool_name in DOMAIN_NAME_TOOLS:
             domain_name_tools[tool_name] = tool_config
-        elif tool_name in DOMAINS_FILE_TOOLS:
-            domains_file_tools[tool_name] = tool_config
         elif tool_name in SITES_FILE_TOOLS:
             sites_file_tools[tool_name] = tool_config
         elif tool_name == 'uro':
@@ -83,10 +67,9 @@ def _classify_tools(enabled_tools: dict) -> tuple[dict, dict, dict, dict, dict]:
         elif tool_name == 'httpx':
             httpx_config = tool_config
         else:
-            logger.warning("未知工具类型: %s，将尝试作为 domains_file 输入的被动收集工具", tool_name)
-            domains_file_tools[tool_name] = tool_config
+            logger.warning("未知工具类型: %s，跳过", tool_name)
 
-    return domain_name_tools, domains_file_tools, sites_file_tools, uro_config, httpx_config
+    return domain_name_tools, sites_file_tools, uro_config, httpx_config
 
 
 def _merge_and_deduplicate_urls(result_files: list, url_fetch_dir: Path) -> tuple[str, int]:
@@ -131,9 +114,9 @@ def _clean_urls_with_uro(
             tool_config=uro_config,
             file_path=merged_file,
             base_per_time=1,
+            min_timeout=60,
         )
-        timeout = max(30, timeout)
-        logger.info("uro 自动计算超时时间(按行数，每行 1 秒): %d 秒", timeout)
+        logger.info("uro 自动计算超时时间(按行数，每行 1 秒，最小 60 秒): %d 秒", timeout)
     else:
         try:
             timeout = int(raw_timeout)
@@ -202,11 +185,10 @@ def _validate_and_stream_save_urls(
     raw_timeout = httpx_config.get('timeout', 'auto')
     timeout = 3600
     if isinstance(raw_timeout, str) and raw_timeout == 'auto':
-        # 按 URL 行数计算超时时间：每行 3 秒，不设上限
-        timeout = url_count * 3
-        timeout = max(600, timeout)
+        # 按 URL 行数计算超时时间：每行 3 秒，最小 60 秒
+        timeout = max(60, url_count * 3)
         logger.info(
-            "自动计算 httpx 超时时间(按行数，每行 3 秒): url_count=%d, timeout=%d 秒",
+            "自动计算 httpx 超时时间(按行数，每行 3 秒，最小 60 秒): url_count=%d, timeout=%d 秒",
             url_count,
             timeout,
         )
@@ -282,10 +264,9 @@ def url_fetch_flow(
     
     执行流程：
     1. 准备工作目录
-    2. 按输入类型分类工具（domain_name / domains_file / sites_file / 后处理）
+    2. 按输入类型分类工具（domain_name / sites_file / 后处理）
     3. 并行执行子 Flow
        - domain_name_url_fetch_flow: 基于 domain_name（来自 target_name）执行 URL 获取（如 waymore）
-       - domains_url_fetch_flow: 基于 domains_file 执行 URL 获取（如 gau、waybackurls）
        - sites_url_fetch_flow: 基于 sites_file 执行爬虫（如 katana 等）
     4. 合并所有子 Flow 的结果并去重
     5. uro 去重（如果启用）
@@ -313,23 +294,23 @@ def url_fetch_flow(
         
         # Step 1: 准备工作目录
         logger.info("Step 1: 准备工作目录")
-        url_fetch_dir = _setup_url_fetch_directory(scan_workspace_dir)
+        from apps.scan.utils import setup_scan_directory
+        url_fetch_dir = setup_scan_directory(scan_workspace_dir, 'url_fetch')
         
         # Step 2: 分类工具（按输入类型）
         logger.info("Step 2: 分类工具")
-        domain_name_tools, domains_file_tools, sites_file_tools, uro_config, httpx_config = _classify_tools(enabled_tools)
+        domain_name_tools, sites_file_tools, uro_config, httpx_config = _classify_tools(enabled_tools)
 
         logger.info(
-            "工具分类 - domain_name: %s, domains_file: %s, sites_file: %s, uro: %s, httpx: %s",
+            "工具分类 - domain_name: %s, sites_file: %s, uro: %s, httpx: %s",
             list(domain_name_tools.keys()) or '无',
-            list(domains_file_tools.keys()) or '无',
             list(sites_file_tools.keys()) or '无',
             '启用' if uro_config else '未启用',
             '启用' if httpx_config else '未启用'
         )
 
         # 检查是否有获取工具
-        if not domain_name_tools and not domains_file_tools and not sites_file_tools:
+        if not domain_name_tools and not sites_file_tools:
             raise ValueError(
                 "URL Fetch 流程需要至少启用一个 URL 获取工具（如 waymore, katana）。"
                 "httpx 和 uro 仅用于后处理，不能单独使用。"
@@ -353,24 +334,10 @@ def url_fetch_flow(
             all_result_files.extend(tn_result.get('result_files', []))
             all_failed_tools.extend(tn_result.get('failed_tools', []))
             all_successful_tools.extend(tn_result.get('successful_tools', []))
-
-        # 3b: 基于 domains_file 的 URL 被动收集
-        if domains_file_tools:
-            logger.info("Step 3b: 执行基于 domains_file 的 URL 被动收集子 Flow")
-            passive_result = domains_url_fetch_flow(
-                scan_id=scan_id,
-                target_id=target_id,
-                target_name=target_name,
-                output_dir=str(url_fetch_dir),
-                enabled_tools=domains_file_tools,
-            )
-            all_result_files.extend(passive_result.get('result_files', []))
-            all_failed_tools.extend(passive_result.get('failed_tools', []))
-            all_successful_tools.extend(passive_result.get('successful_tools', []))
         
-        # 3c: 爬虫（以 sites_file 为输入）
+        # 3b: 爬虫（以 sites_file 为输入）
         if sites_file_tools:
-            logger.info("Step 3c: 执行爬虫子 Flow")
+            logger.info("Step 3b: 执行爬虫子 Flow")
             crawl_result = sites_url_fetch_flow(
                 scan_id=scan_id,
                 target_id=target_id,
@@ -443,8 +410,6 @@ def url_fetch_flow(
         executed_tasks = ['setup_directory', 'classify_tools']
         if domain_name_tools:
             executed_tasks.append('domain_name_url_fetch_flow')
-        if domains_file_tools:
-            executed_tasks.append('domains_url_fetch_flow')
         if sites_file_tools:
             executed_tasks.append('sites_url_fetch_flow')
         executed_tasks.append('merge_and_deduplicate')
@@ -463,7 +428,7 @@ def url_fetch_flow(
             'total': saved_count,
             'executed_tasks': executed_tasks,
             'tool_stats': {
-                'total': len(domain_name_tools) + len(domains_file_tools) + len(sites_file_tools),
+                'total': len(domain_name_tools) + len(sites_file_tools),
                 'successful': len(all_successful_tools),
                 'failed': len(all_failed_tools),
                 'successful_tools': all_successful_tools,

backend/apps/scan/flows/url_fetch/sites_url_fetch_flow.py

@@ -19,33 +19,35 @@ from .utils import run_tools_parallel
 logger = logging.getLogger(__name__)
 
 
-def _export_sites_file(target_id: int, scan_id: int, output_dir: Path) -> tuple[str, int]:
+def _export_sites_file(target_id: int, scan_id: int, target_name: str, output_dir: Path) -> tuple[str, int]:
     """
     导出站点 URL 列表到文件
     
+    懒加载模式：如果 WebSite 表为空，根据 Target 类型生成默认 URL
+    
     Args:
         target_id: 目标 ID
         scan_id: 扫描 ID
+        target_name: 目标名称（用于懒加载）
         output_dir: 输出目录
         
     Returns:
         tuple: (file_path, count)
     """
-    from apps.scan.tasks.url_fetch import export_target_assets_task
+    from apps.scan.tasks.url_fetch import export_sites_task
     
     output_file = str(output_dir / "sites.txt")
-    result = export_target_assets_task(
+    result = export_sites_task(
         output_file=output_file,
         target_id=target_id,
-        scan_id=scan_id,
-        input_type="sites_file"
+        scan_id=scan_id
     )
     
     count = result['asset_count']
-    if count == 0:
-        logger.warning("站点列表为空，爬虫可能无法正常工作")
-    else:
+    if count > 0:
         logger.info("✓ 站点列表导出完成 - 数量: %d", count)
+    else:
+        logger.warning("站点列表为空，爬虫可能无法正常工作")
     
     return output_file, count
 
@@ -94,9 +96,11 @@ def sites_url_fetch_flow(
         sites_file, sites_count = _export_sites_file(
             target_id=target_id,
             scan_id=scan_id,
+            target_name=target_name,
             output_dir=output_path
         )
         
+        # 默认值模式下，即使原本没有站点，也会有默认 URL 作为输入
         if sites_count == 0:
             logger.warning("没有可用的站点，跳过爬虫")
             return {

backend/apps/scan/flows/url_fetch/utils.py

@@ -17,6 +17,7 @@ def calculate_timeout_by_line_count(
     tool_config: dict,
     file_path: str,
     base_per_time: int = 1,
+    min_timeout: int = 60,
 ) -> int:
     """
     根据文件行数自动计算超时时间
@@ -25,9 +26,10 @@ def calculate_timeout_by_line_count(
         tool_config: 工具配置（保留参数，未来可能用于更复杂的计算）
         file_path: 输入文件路径
         base_per_time: 每行的基础时间（秒）
+        min_timeout: 最小超时时间（秒），默认60秒
         
     Returns:
-        int: 计算出的超时时间（秒）
+        int: 计算出的超时时间（秒），不低于 min_timeout
     """
     try:
         result = subprocess.run(
@@ -37,18 +39,19 @@ def calculate_timeout_by_line_count(
             check=True,
         )
         line_count = int(result.stdout.strip().split()[0])
-        timeout = line_count * base_per_time
+        timeout = max(line_count * base_per_time, min_timeout)
         logger.info(
-            "timeout 自动计算: 文件=%s, 行数=%d, 每行时间=%d秒, timeout=%d秒",
+            "timeout 自动计算: 文件=%s, 行数=%d, 每行时间=%d秒, 最小值=%d秒, timeout=%d秒",
             file_path,
             line_count,
             base_per_time,
+            min_timeout,
             timeout,
         )
         return timeout
     except Exception as e:
-        logger.warning("wc -l 计算行数失败: %s，将使用默认 timeout: 600秒", e)
-        return 600
+        logger.warning("wc -l 计算行数失败: %s，将使用默认 timeout: %d秒", e, min_timeout)
+        return min_timeout
 
 
 def prepare_tool_execution(

backend/apps/scan/flows/vuln_scan/endpoints_vuln_scan_flow.py

@@ -25,10 +25,7 @@ from .utils import calculate_timeout_by_line_count
 logger = logging.getLogger(__name__)
 
 
-def _setup_vuln_scan_directory(scan_workspace_dir: str) -> Path:
-    vuln_scan_dir = Path(scan_workspace_dir) / "vuln_scan"
-    vuln_scan_dir.mkdir(parents=True, exist_ok=True)
-    return vuln_scan_dir
+
 
 
 @flow(
@@ -55,7 +52,8 @@ def endpoints_vuln_scan_flow(
         if not enabled_tools:
             raise ValueError("enabled_tools 不能为空")
 
-        vuln_scan_dir = _setup_vuln_scan_directory(scan_workspace_dir)
+        from apps.scan.utils import setup_scan_directory
+        vuln_scan_dir = setup_scan_directory(scan_workspace_dir, 'vuln_scan')
         endpoints_file = vuln_scan_dir / "input_endpoints.txt"
 
         # Step 1: 导出 Endpoint URL
@@ -119,7 +117,6 @@ def endpoints_vuln_scan_flow(
             )
 
             raw_timeout = tool_config.get("timeout", 600)
-            timeout = 600
 
             if isinstance(raw_timeout, str) and raw_timeout == "auto":
                 # timeout=auto 时，根据 endpoints_file 行数自动计算超时时间
@@ -134,7 +131,6 @@ def endpoints_vuln_scan_flow(
                 try:
                     timeout = int(raw_timeout)
                 except (TypeError, ValueError) as e:
-                    # 配置错误应当直接暴露，避免默默使用默认值导致排查困难
                     raise ValueError(
                         f"工具 {tool_name} 的 timeout 配置无效: {raw_timeout!r}"
                     ) from e
@@ -174,7 +170,7 @@ def endpoints_vuln_scan_flow(
                     target_id=target_id,
                     cwd=str(vuln_scan_dir),
                     shell=True,
-                    batch_size=10,
+                    batch_size=1,
                     timeout=timeout,
                     log_file=str(log_file),
                 )

backend/apps/scan/flows/vuln_scan/utils.py

@@ -12,6 +12,7 @@ def calculate_timeout_by_line_count(
     tool_config: dict,
     file_path: str,
     base_per_time: int = 1,
+    min_timeout: int = 600,
 ) -> int:
     """
     根据文件行数自动计算超时时间
@@ -20,9 +21,10 @@ def calculate_timeout_by_line_count(
         tool_config: 工具配置（保留参数，未来可能用于更复杂的计算）
         file_path: 输入文件路径
         base_per_time: 每行的基础时间（秒）
+        min_timeout: 最小超时时间（秒），默认600秒（10分钟）
 
     Returns:
-        int: 计算出的超时时间（秒）
+        int: 计算出的超时时间（秒），不低于 min_timeout
     """
     try:
         result = subprocess.run(
@@ -32,15 +34,16 @@ def calculate_timeout_by_line_count(
             check=True,
         )
         line_count = int(result.stdout.strip().split()[0])
-        timeout = line_count * base_per_time
+        timeout = max(line_count * base_per_time, min_timeout)
         logger.info(
-            "timeout 自动计算: 文件=%s, 行数=%d, 每行时间=%d秒, timeout=%d秒",
+            "timeout 自动计算: 文件=%s, 行数=%d, 每行时间=%d秒, 最小值=%d秒, timeout=%d秒",
             file_path,
             line_count,
             base_per_time,
+            min_timeout,
             timeout,
         )
         return timeout
     except Exception as e:
-        logger.error("wc -l 计算行数失败: %s", e)
-        raise RuntimeError(f"自动计算超时时间失败: {e}") from e
+        logger.warning("wc -l 计算行数失败: %s，使用最小超时: %d秒", e, min_timeout)
+        return min_timeout

backend/apps/scan/management/commands/generate_test_data.py

@@ -1,567 +0,0 @@
-"""
-生成测试数据的管理命令
-
-用法：
-    python manage.py generate_test_data --target test.com --count 100000
-    
-性能测试：
-    python manage.py generate_test_data --target test.com --count 10000 --batch-size 500 --benchmark
-"""
-
-import random
-import string
-import time
-from django.core.management.base import BaseCommand
-from django.db import transaction, connection
-from django.utils import timezone
-from apps.targets.models import Target
-from apps.scan.models import Scan
-from apps.asset.models.asset_models import Subdomain, IPAddress, Port, WebSite, Directory
-
-
-class Command(BaseCommand):
-    help = '为指定目标生成大量测试数据'
-
-    def add_arguments(self, parser):
-        parser.add_argument(
-            '--target',
-            type=str,
-            required=True,
-            help='目标域名（如 test.com）'
-        )
-        parser.add_argument(
-            '--count',
-            type=int,
-            default=100000,
-            help='每个表生成的记录数（默认 100000）'
-        )
-        parser.add_argument(
-            '--batch-size',
-            type=int,
-            default=1000,
-            help='批量插入的批次大小（默认 1000）'
-        )
-        parser.add_argument(
-            '--benchmark',
-            action='store_true',
-            help='启用性能基准测试模式（显示详细的性能指标）'
-        )
-        parser.add_argument(
-            '--test-batch-sizes',
-            action='store_true',
-            help='测试不同批次大小的性能（100, 500, 1000, 2000, 5000）'
-        )
-
-    def handle(self, *args, **options):
-        target_name = options['target']
-        count = options['count']
-        batch_size = options['batch_size']
-        benchmark = options['benchmark']
-        test_batch_sizes = options['test_batch_sizes']
-
-        # 如果是测试批次大小模式
-        if test_batch_sizes:
-            self._test_batch_sizes(target_name, count)
-            return
-
-        self.stdout.write(f'\n{"="*60}')
-        self.stdout.write(f'  开始生成测试数据')
-        self.stdout.write(f'{"="*60}\n')
-        self.stdout.write(f'目标: {target_name}')
-        self.stdout.write(f'每表记录数: {count:,}')
-        self.stdout.write(f'批次大小: {batch_size:,}')
-        if benchmark:
-            self.stdout.write('模式: 性能基准测试 ⚡')
-            self._print_db_info()
-        self.stdout.write('')
-        
-        # 记录总开始时间
-        total_start_time = time.time()
-
-        # 1. 获取或创建目标
-        try:
-            target = Target.objects.get(name=target_name)
-            self.stdout.write(self.style.SUCCESS(f'✓ 找到目标: {target.name} (ID: {target.id})'))
-        except Target.DoesNotExist:
-            self.stdout.write(self.style.ERROR(f'✗ 目标不存在: {target_name}'))
-            return
-
-        # 2. 创建新的测试扫描任务
-        from apps.engine.models import ScanEngine
-        engine = ScanEngine.objects.first()
-        if not engine:
-            self.stdout.write(self.style.ERROR('✗ 没有可用的扫描引擎'))
-            return
-        
-        scan = Scan.objects.create(
-            target=target,
-            engine=engine,
-            status='completed',
-            results_dir=f'/tmp/test_{target_name}_{int(time.time())}'
-        )
-        self.stdout.write(self.style.SUCCESS(f'✓ 创建新测试扫描任务 (ID: {scan.id})'))
-
-        # 3. 生成子域名
-        self.stdout.write(f'\n[1/5] 生成 {count:,} 个子域名...')
-        subdomains, stats1 = self._generate_subdomains(target, scan, count, batch_size, benchmark)
-        
-        # 4. 生成 IP 地址
-        self.stdout.write(f'\n[2/5] 生成 {count:,} 个 IP 地址...')
-        ips, stats2 = self._generate_ips(target, scan, subdomains, count, batch_size, benchmark)
-        
-        # 5. 生成端口
-        self.stdout.write(f'\n[3/5] 生成 {count:,} 个端口...')
-        stats3 = self._generate_ports(scan, ips, subdomains, count, batch_size, benchmark)
-        
-        # 6. 生成网站
-        self.stdout.write(f'\n[4/5] 生成 {count:,} 个网站...')
-        websites, stats4 = self._generate_websites(target, scan, subdomains, count, batch_size, benchmark)
-        
-        # 7. 生成目录
-        self.stdout.write(f'\n[5/5] 生成 {count:,} 个目录...')
-        stats5 = self._generate_directories(target, scan, websites, count, batch_size, benchmark)
-
-        # 计算总耗时
-        total_time = time.time() - total_start_time
-        
-        self.stdout.write(f'\n{"="*60}')
-        self.stdout.write(self.style.SUCCESS('  ✓ 测试数据生成完成！'))
-        self.stdout.write(f'{"="*60}')
-        self.stdout.write(f'总耗时: {total_time:.2f} 秒 ({total_time/60:.2f} 分钟)\n')
-        
-        if benchmark:
-            self._print_performance_summary([stats1, stats2, stats3, stats4, stats5])
-
-    def _generate_subdomains(self, target, scan, count, batch_size, benchmark=False):
-        """生成子域名"""
-        subdomains = []
-        created_subdomains = []
-        start_time = time.time()
-        batch_times = []
-        
-        for i in range(count):
-            # 生成唯一的子域名
-            subdomain_name = f'test-{i:07d}.{target.name}'
-            
-            subdomains.append(Subdomain(
-                target=target,
-                scan=scan,
-                name=subdomain_name,
-                cname=[],
-                is_cdn=random.choice([True, False]),
-                cdn_name=random.choice(['', 'cloudflare', 'akamai', 'fastly'])
-            ))
-            
-            # 批量插入
-            if len(subdomains) >= batch_size:
-                batch_start = time.time()
-                with transaction.atomic():
-                    created = Subdomain.objects.bulk_create(subdomains, ignore_conflicts=True)
-                    created_subdomains.extend(created)
-                batch_time = time.time() - batch_start
-                batch_times.append(batch_time)
-                
-                if benchmark:
-                    speed = len(subdomains) / batch_time
-                    self.stdout.write(f'  插入 {len(subdomains):,} 个 | 耗时: {batch_time:.2f}s | 速度: {speed:.0f} 条/秒')
-                else:
-                    self.stdout.write(f'  插入 {len(subdomains):,} 个子域名... (进度: {i+1:,}/{count:,})')
-                subdomains = []
-        
-        # 插入剩余的
-        if subdomains:
-            with transaction.atomic():
-                created = Subdomain.objects.bulk_create(subdomains, ignore_conflicts=True)
-                created_subdomains.extend(created)
-            self.stdout.write(f'  插入 {len(subdomains):,} 个子域名... (进度: {count:,}/{count:,})')
-        
-        total_time = time.time() - start_time
-        avg_batch_time = sum(batch_times) / len(batch_times) if batch_times else 0
-        total_speed = len(created_subdomains) / total_time if total_time > 0 else 0
-        
-        self.stdout.write(self.style.SUCCESS(
-            f'  ✓ 完成！共创建 {len(created_subdomains):,} 个 | '
-            f'总耗时: {total_time:.2f}s | '
-            f'平均速度: {total_speed:.0f} 条/秒'
-        ))
-        
-        return created_subdomains, {
-            'name': '子域名',
-            'count': len(created_subdomains),
-            'time': total_time,
-            'speed': total_speed,
-            'avg_batch_time': avg_batch_time
-        }
-
-    def _generate_ips(self, target, scan, subdomains, count, batch_size, benchmark=False):
-        """生成 IP 地址"""
-        # 重新从数据库查询 subdomain，确保有 ID
-        subdomain_list = list(Subdomain.objects.filter(scan=scan).values_list('id', flat=True))
-        
-        ips = []
-        created_ips = []
-        start_time = time.time()
-        batch_times = []
-        
-        for i in range(count):
-            # 生成随机 IP
-            ip_addr = f'192.168.{random.randint(0, 255)}.{random.randint(1, 254)}'
-            subdomain_id = random.choice(subdomain_list) if subdomain_list else None
-            
-            if subdomain_id:
-                ips.append(IPAddress(
-                    target=target,
-                    scan=scan,
-                    subdomain_id=subdomain_id,
-                    ip=f'{ip_addr}-{i}',  # 加后缀确保唯一
-                    protocol_version='IPv4',
-                    is_private=True
-                ))
-            
-            # 批量插入
-            if len(ips) >= batch_size:
-                batch_start = time.time()
-                with transaction.atomic():
-                    created = IPAddress.objects.bulk_create(ips, ignore_conflicts=True)
-                    created_ips.extend(created)
-                batch_time = time.time() - batch_start
-                batch_times.append(batch_time)
-                
-                if benchmark:
-                    speed = len(ips) / batch_time
-                    self.stdout.write(f'  插入 {len(ips):,} 个 | 耗时: {batch_time:.2f}s | 速度: {speed:.0f} 条/秒')
-                else:
-                    self.stdout.write(f'  插入 {len(ips):,} 个 IP 地址... (进度: {i+1:,}/{count:,})')
-                ips = []
-        
-        # 插入剩余的
-        if ips:
-            with transaction.atomic():
-                created = IPAddress.objects.bulk_create(ips, ignore_conflicts=True)
-                created_ips.extend(created)
-            self.stdout.write(f'  插入 {len(ips):,} 个 IP 地址... (进度: {count:,}/{count:,})')
-        
-        total_time = time.time() - start_time
-        avg_batch_time = sum(batch_times) / len(batch_times) if batch_times else 0
-        total_speed = len(created_ips) / total_time if total_time > 0 else 0
-        
-        self.stdout.write(self.style.SUCCESS(
-            f'  ✓ 完成！共创建 {len(created_ips):,} 个 | '
-            f'总耗时: {total_time:.2f}s | '
-            f'平均速度: {total_speed:.0f} 条/秒'
-        ))
-        
-        return created_ips, {
-            'name': 'IP地址',
-            'count': len(created_ips),
-            'time': total_time,
-            'speed': total_speed,
-            'avg_batch_time': avg_batch_time
-        }
-
-    def _generate_ports(self, scan, ips, subdomains, count, batch_size, benchmark=False):
-        """生成端口"""
-        # 重新查询 IP 和 subdomain 的 ID
-        ip_list = list(IPAddress.objects.filter(scan=scan).values_list('id', flat=True))
-        subdomain_list = list(Subdomain.objects.filter(scan=scan).values_list('id', flat=True))
-        
-        ports = []
-        total_created = 0
-        start_time = time.time()
-        batch_times = []
-        
-        for i in range(count):
-            ip_id = random.choice(ip_list) if ip_list else None
-            subdomain_id = random.choice(subdomain_list) if subdomain_list else None
-            
-            if ip_id:
-                ports.append(Port(
-                    ip_address_id=ip_id,
-                    subdomain_id=subdomain_id,
-                    number=random.randint(1, 65535),
-                    service_name=random.choice(['http', 'https', 'ssh', 'ftp', 'mysql']),
-                    is_uncommon=random.choice([True, False])
-                ))
-            
-            # 批量插入
-            if len(ports) >= batch_size:
-                batch_start = time.time()
-                with transaction.atomic():
-                    Port.objects.bulk_create(ports, ignore_conflicts=True)
-                total_created += len(ports)
-                batch_time = time.time() - batch_start
-                batch_times.append(batch_time)
-                
-                if benchmark:
-                    speed = len(ports) / batch_time
-                    self.stdout.write(f'  插入 {len(ports):,} 个 | 耗时: {batch_time:.2f}s | 速度: {speed:.0f} 条/秒')
-                else:
-                    self.stdout.write(f'  插入 {len(ports):,} 个端口... (进度: {i+1:,}/{count:,})')
-                ports = []
-        
-        # 插入剩余的
-        if ports:
-            with transaction.atomic():
-                Port.objects.bulk_create(ports, ignore_conflicts=True)
-            total_created += len(ports)
-            self.stdout.write(f'  插入 {len(ports):,} 个端口... (进度: {count:,}/{count:,})')
-        
-        total_time = time.time() - start_time
-        avg_batch_time = sum(batch_times) / len(batch_times) if batch_times else 0
-        total_speed = total_created / total_time if total_time > 0 else 0
-        
-        self.stdout.write(self.style.SUCCESS(
-            f'  ✓ 完成！共创建 {total_created:,} 个 | '
-            f'总耗时: {total_time:.2f}s | '
-            f'平均速度: {total_speed:.0f} 条/秒'
-        ))
-        
-        return {
-            'name': '端口',
-            'count': total_created,
-            'time': total_time,
-            'speed': total_speed,
-            'avg_batch_time': avg_batch_time
-        }
-
-    def _generate_websites(self, target, scan, subdomains, count, batch_size, benchmark=False):
-        """生成网站"""
-        # 重新查询 subdomain 信息
-        subdomain_data = list(Subdomain.objects.filter(scan=scan).values('id', 'name'))
-        
-        websites = []
-        created_websites = []
-        start_time = time.time()
-        batch_times = []
-        
-        for i in range(count):
-            subdomain = random.choice(subdomain_data) if subdomain_data else None
-            
-            if subdomain:
-                protocol = random.choice(['http', 'https'])
-                url = f'{protocol}://{subdomain["name"]}'
-                
-                websites.append(WebSite(
-                    target=target,
-                    scan=scan,
-                    subdomain_id=subdomain['id'],
-                    url=f'{url}?id={i}',  # 加参数确保唯一
-                    title=f'Test Website {i}',
-                    status_code=random.choice([200, 301, 302, 404, 500]),
-                    content_length=random.randint(1000, 100000),
-                    webserver=random.choice(['nginx', 'apache', 'IIS']),
-                    content_type='text/html',
-                    tech=['Python', 'Django'] if i % 2 == 0 else ['Node.js', 'React'],
-                    vhost=random.choice([True, False, None])
-                ))
-            
-            # 批量插入
-            if len(websites) >= batch_size:
-                batch_start = time.time()
-                with transaction.atomic():
-                    created = WebSite.objects.bulk_create(websites, ignore_conflicts=True)
-                    created_websites.extend(created)
-                batch_time = time.time() - batch_start
-                batch_times.append(batch_time)
-                
-                if benchmark:
-                    speed = len(websites) / batch_time
-                    self.stdout.write(f'  插入 {len(websites):,} 个 | 耗时: {batch_time:.2f}s | 速度: {speed:.0f} 条/秒')
-                else:
-                    self.stdout.write(f'  插入 {len(websites):,} 个网站... (进度: {i+1:,}/{count:,})')
-                websites = []
-        
-        # 插入剩余的
-        if websites:
-            with transaction.atomic():
-                created = WebSite.objects.bulk_create(websites, ignore_conflicts=True)
-                created_websites.extend(created)
-            self.stdout.write(f'  插入 {len(websites):,} 个网站... (进度: {count:,}/{count:,})')
-        
-        total_time = time.time() - start_time
-        avg_batch_time = sum(batch_times) / len(batch_times) if batch_times else 0
-        total_speed = len(created_websites) / total_time if total_time > 0 else 0
-        
-        self.stdout.write(self.style.SUCCESS(
-            f'  ✓ 完成！共创建 {len(created_websites):,} 个 | '
-            f'总耗时: {total_time:.2f}s | '
-            f'平均速度: {total_speed:.0f} 条/秒'
-        ))
-        
-        return created_websites, {
-            'name': '网站',
-            'count': len(created_websites),
-            'time': total_time,
-            'speed': total_speed,
-            'avg_batch_time': avg_batch_time
-        }
-
-    def _generate_directories(self, target, scan, websites, count, batch_size, benchmark=False):
-        """生成目录"""
-        # 重新查询 website 信息
-        website_data = list(WebSite.objects.filter(scan=scan).values('id', 'url'))
-        
-        directories = []
-        total_created = 0
-        start_time = time.time()
-        batch_times = []
-        
-        for i in range(count):
-            website = random.choice(website_data) if website_data else None
-            
-            if website:
-                path = ''.join(random.choices(string.ascii_lowercase, k=10))
-                
-                directories.append(Directory(
-                    target=target,
-                    scan=scan,
-                    website_id=website['id'],
-                    url=f'{website["url"]}/dir/{path}/{i}',  # 加后缀确保唯一
-                    status=random.choice([200, 301, 403, 404]),
-                    length=random.randint(1000, 50000),
-                    words=random.randint(100, 5000),
-                    lines=random.randint(50, 1000),
-                    content_type='text/html'
-                ))
-            
-            # 批量插入
-            if len(directories) >= batch_size:
-                batch_start = time.time()
-                with transaction.atomic():
-                    Directory.objects.bulk_create(directories, ignore_conflicts=True)
-                total_created += len(directories)
-                batch_time = time.time() - batch_start
-                batch_times.append(batch_time)
-                
-                if benchmark:
-                    speed = len(directories) / batch_time
-                    self.stdout.write(f'  插入 {len(directories):,} 个 | 耗时: {batch_time:.2f}s | 速度: {speed:.0f} 条/秒')
-                else:
-                    self.stdout.write(f'  插入 {len(directories):,} 个目录... (进度: {i+1:,}/{count:,})')
-                directories = []
-        
-        # 插入剩余的
-        if directories:
-            with transaction.atomic():
-                Directory.objects.bulk_create(directories, ignore_conflicts=True)
-            total_created += len(directories)
-            self.stdout.write(f'  插入 {len(directories):,} 个目录... (进度: {count:,}/{count:,})')
-        
-        total_time = time.time() - start_time
-        avg_batch_time = sum(batch_times) / len(batch_times) if batch_times else 0
-        total_speed = total_created / total_time if total_time > 0 else 0
-        
-        self.stdout.write(self.style.SUCCESS(
-            f'  ✓ 完成！共创建 {total_created:,} 个 | '
-            f'总耗时: {total_time:.2f}s | '
-            f'平均速度: {total_speed:.0f} 条/秒'
-        ))
-        
-        return {
-            'name': '目录',
-            'count': total_created,
-            'time': total_time,
-            'speed': total_speed,
-            'avg_batch_time': avg_batch_time
-        }
-    
-    def _print_db_info(self):
-        """打印数据库连接信息"""
-        db_settings = connection.settings_dict
-        self.stdout.write(f'\n数据库信息:')
-        self.stdout.write(f'  主机: {db_settings["HOST"]}')
-        self.stdout.write(f'  端口: {db_settings["PORT"]}')
-        self.stdout.write(f'  数据库: {db_settings["NAME"]}')
-        self.stdout.write(f'  引擎: {db_settings["ENGINE"].split(".")[-1]}')
-    
-    def _print_performance_summary(self, stats_list):
-        """打印性能总结"""
-        self.stdout.write(f'\n{"="*60}')
-        self.stdout.write('  性能测试报告')
-        self.stdout.write(f'{"="*60}\n')
-        
-        total_records = sum(s['count'] for s in stats_list)
-        total_time = sum(s['time'] for s in stats_list)
-        overall_speed = total_records / total_time if total_time > 0 else 0
-        
-        self.stdout.write(f'{"表名":<12} {"记录数":<12} {"耗时(秒)":<12} {"速度(条/秒)":<15} {"平均批次时间(秒)"}')
-        self.stdout.write('-' * 65)
-        
-        for stats in stats_list:
-            self.stdout.write(
-                f'{stats["name"]:<12} '
-                f'{stats["count"]:<12,} '
-                f'{stats["time"]:<12.2f} '
-                f'{stats["speed"]:<15.0f} '
-                f'{stats.get("avg_batch_time", 0):<.3f}'
-            )
-        
-        self.stdout.write('-' * 65)
-        self.stdout.write(
-            f'{"总计":<12} '
-            f'{total_records:<12,} '
-            f'{total_time:<12.2f} '
-            f'{overall_speed:<15.0f}'
-        )
-        self.stdout.write('')
-    
-    def _test_batch_sizes(self, target_name, count):
-        """测试不同批次大小的性能"""
-        batch_sizes = [100, 500, 1000, 2000, 5000]
-        test_count = min(count, 10000)  # 限制测试数据量
-        
-        self.stdout.write(f'\n{"="*60}')
-        self.stdout.write(f'  批次大小性能测试')
-        self.stdout.write(f'{"="*60}\n')
-        self.stdout.write(f'测试数据量: {test_count:,} 条')
-        self.stdout.write(f'测试批次: {batch_sizes}\n')
-        
-        results = []
-        
-        for batch_size in batch_sizes:
-            self.stdout.write(f'\n测试批次大小: {batch_size}')
-            self.stdout.write('-' * 40)
-            
-            # 这里只测试子域名的插入性能
-            try:
-                target = Target.objects.get(name=target_name)
-            except Target.DoesNotExist:
-                self.stdout.write(self.style.ERROR(f'目标不存在: {target_name}'))
-                return
-            
-            scan = Scan.objects.filter(target=target).first()
-            if not scan:
-                from apps.engine.models import ScanEngine
-                engine = ScanEngine.objects.first()
-                scan = Scan.objects.create(
-                    target=target,
-                    engine=engine,
-                    status='completed',
-                    results_dir=f'/tmp/test_{target_name}'
-                )
-            
-            _, stats = self._generate_subdomains(target, scan, test_count, batch_size, benchmark=True)
-            results.append((batch_size, stats))
-            
-            # 清理测试数据
-            Subdomain.objects.filter(scan=scan, name__startswith=f'test-').delete()
-        
-        # 打印对比结果
-        self.stdout.write(f'\n{"="*60}')
-        self.stdout.write('  批次大小对比结果')
-        self.stdout.write(f'{"="*60}\n')
-        self.stdout.write(f'{"批次大小":<12} {"总耗时(秒)":<15} {"速度(条/秒)":<15} {"平均批次时间(秒)"}')
-        self.stdout.write('-' * 60)
-        
-        for batch_size, stats in results:
-            self.stdout.write(
-                f'{batch_size:<12} '
-                f'{stats["time"]:<15.2f} '
-                f'{stats["speed"]:<15.0f} '
-                f'{stats["avg_batch_time"]:<.3f}'
-            )
-        
-        # 找出最快的批次大小
-        fastest = min(results, key=lambda x: x[1]['time'])
-        self.stdout.write(f'\n推荐批次大小: {fastest[0]} (最快: {fastest[1]["time"]:.2f}秒)')
-        self.stdout.write('')

backend/apps/scan/notifications/receivers.py

@@ -87,8 +87,8 @@ def on_all_workers_high_load(sender, worker_name, cpu, mem, **kwargs):
     """所有 Worker 高负载时的通知处理"""
     create_notification(
         title="系统负载较高",
-        message=f"所有节点负载较高，已选择负载最低的节点 {worker_name}（CPU: {cpu:.1f}%, 内存: {mem:.1f}%）执行任务，扫描速度可能受影响",
+        message=f"所有节点负载较高（最低负载节点 CPU: {cpu:.1f}%, 内存: {mem:.1f}%），系统将等待最多 10 分钟后分发任务，扫描速度可能受影响",
         level=NotificationLevel.MEDIUM,
         category=NotificationCategory.SYSTEM
     )
-    logger.warning("高负载通知已发送 - worker=%s, cpu=%.1f%%, mem=%.1f%%", worker_name, cpu, mem)
+    logger.warning("高负载通知已发送 - cpu=%.1f%%, mem=%.1f%%", cpu, mem)

backend/apps/scan/orchestrators/flow_orchestrator.py

@@ -206,6 +206,10 @@ class FlowOrchestrator:
             from apps.scan.flows.site_scan_flow import site_scan_flow
             return site_scan_flow
         
+        elif scan_type == 'fingerprint_detect':
+            from apps.scan.flows.fingerprint_detect_flow import fingerprint_detect_flow
+            return fingerprint_detect_flow
+        
         elif scan_type == 'directory_scan':
             from apps.scan.flows.directory_scan_flow import directory_scan_flow
             return directory_scan_flow

backend/apps/scan/scripts/run_cleanup.py

@@ -83,7 +83,7 @@ def cleanup_results(results_dir: str, retention_days: int) -> dict:
 
 def main():
     parser = argparse.ArgumentParser(description="清理任务")
-    parser.add_argument("--results_dir", type=str, default="/app/backend/results", help="扫描结果目录")
+    parser.add_argument("--results_dir", type=str, default="/opt/xingrin/results", help="扫描结果目录")
     parser.add_argument("--retention_days", type=int, default=7, help="保留天数")
     
     args = parser.parse_args()

backend/apps/scan/services/__init__.py

@@ -17,6 +17,8 @@ from .scan_state_service import ScanStateService
 from .scan_control_service import ScanControlService
 from .scan_stats_service import ScanStatsService
 from .scheduled_scan_service import ScheduledScanService
+from .blacklist_service import BlacklistService
+from .target_export_service import TargetExportService
 
 __all__ = [
     'ScanService',           # 主入口（向后兼容）
@@ -25,5 +27,7 @@ __all__ = [
     'ScanControlService',
     'ScanStatsService',
     'ScheduledScanService',
+    'BlacklistService',      # 黑名单过滤服务
+    'TargetExportService',   # 目标导出服务
 ]
 

backend/apps/scan/services/blacklist_service.py

@@ -0,0 +1,85 @@
+"""
+黑名单过滤服务
+
+过滤敏感域名（如 .gov、.edu、.mil 等）
+
+当前版本使用默认规则，后续将支持从前端配置加载。
+"""
+
+from typing import List, Optional
+from django.db.models import QuerySet
+import re
+import logging
+
+logger = logging.getLogger(__name__)
+
+
+class BlacklistService:
+    """
+    黑名单过滤服务 - 过滤敏感域名
+    
+    TODO: 后续版本支持从前端配置加载黑名单规则
+    - 用户在开始扫描时配置黑名单 URL、域名、IP
+    - 黑名单规则存储在数据库中，与 Scan 或 Engine 关联
+    """
+    
+    # 默认黑名单正则规则
+    DEFAULT_PATTERNS = [
+        r'\.gov$',           # .gov 结尾
+        r'\.gov\.[a-z]{2}$', # .gov.cn, .gov.uk 等
+        r'\.edu$',           # .edu 结尾
+        r'\.edu\.[a-z]{2}$', # .edu.cn 等
+        r'\.mil$',           # .mil 结尾
+    ]
+    
+    def __init__(self, patterns: Optional[List[str]] = None):
+        """
+        初始化黑名单服务
+        
+        Args:
+            patterns: 正则表达式列表，None 使用默认规则
+        """
+        self.patterns = patterns or self.DEFAULT_PATTERNS
+        self._compiled_patterns = [re.compile(p) for p in self.patterns]
+    
+    def filter_queryset(
+        self,
+        queryset: QuerySet,
+        url_field: str = 'url'
+    ) -> QuerySet:
+        """
+        数据库层面过滤 queryset
+        
+        使用 PostgreSQL 正则表达式排除黑名单 URL
+        
+        Args:
+            queryset: 原始 queryset
+            url_field: URL 字段名
+            
+        Returns:
+            QuerySet: 过滤后的 queryset
+        """
+        for pattern in self.patterns:
+            queryset = queryset.exclude(**{f'{url_field}__regex': pattern})
+        return queryset
+    
+    def filter_url(self, url: str) -> bool:
+        """
+        检查单个 URL 是否通过黑名单过滤
+        
+        Args:
+            url: 要检查的 URL
+            
+        Returns:
+            bool: True 表示通过（不在黑名单），False 表示被过滤
+        """
+        for pattern in self._compiled_patterns:
+            if pattern.search(url):
+                return False
+        return True
+    
+    # TODO: 后续版本实现
+    # @classmethod
+    # def from_scan(cls, scan_id: int) -> 'BlacklistService':
+    #     """从数据库加载扫描配置的黑名单规则"""
+    #     pass

backend/apps/scan/services/quick_scan_service.py

@@ -0,0 +1,295 @@
+"""
+快速扫描服务
+
+负责解析用户输入（URL、域名、IP、CIDR）并创建对应的资产数据
+"""
+
+import logging
+from dataclasses import dataclass
+from typing import Optional, Literal, List, Dict, Any
+from urllib.parse import urlparse
+
+from django.db import transaction
+
+from apps.common.validators import validate_url, detect_input_type, validate_domain, validate_ip, validate_cidr, is_valid_ip
+from apps.targets.services.target_service import TargetService
+from apps.targets.models import Target
+from apps.asset.dtos import WebSiteDTO
+from apps.asset.dtos.asset import EndpointDTO
+from apps.asset.repositories.asset.website_repository import DjangoWebSiteRepository
+from apps.asset.repositories.asset.endpoint_repository import DjangoEndpointRepository
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class ParsedInputDTO:
+    """
+    解析输入 DTO
+    
+    只在快速扫描流程中使用
+    """
+    original_input: str
+    input_type: Literal['url', 'domain', 'ip', 'cidr']
+    target_name: str                              # host/domain/ip/cidr
+    target_type: Literal['domain', 'ip', 'cidr']
+    website_url: Optional[str] = None             # 根 URL（scheme://host[:port]）
+    endpoint_url: Optional[str] = None            # 完整 URL（含路径）
+    is_valid: bool = True
+    error: Optional[str] = None
+    line_number: Optional[int] = None
+
+
+class QuickScanService:
+    """快速扫描服务 - 解析输入并创建资产"""
+    
+    def __init__(self):
+        self.target_service = TargetService()
+        self.website_repo = DjangoWebSiteRepository()
+        self.endpoint_repo = DjangoEndpointRepository()
+    
+    def parse_inputs(self, inputs: List[str]) -> List[ParsedInputDTO]:
+        """
+        解析多行输入
+        
+        Args:
+            inputs: 输入字符串列表（每行一个）
+            
+        Returns:
+            解析结果列表（跳过空行）
+        """
+        results = []
+        for line_number, input_str in enumerate(inputs, start=1):
+            input_str = input_str.strip()
+            
+            # 空行跳过
+            if not input_str:
+                continue
+            
+            try:
+                # 检测输入类型
+                input_type = detect_input_type(input_str)
+                
+                if input_type == 'url':
+                    dto = self._parse_url_input(input_str, line_number)
+                else:
+                    dto = self._parse_target_input(input_str, input_type, line_number)
+                
+                results.append(dto)
+            except ValueError as e:
+                # 解析失败，记录错误
+                results.append(ParsedInputDTO(
+                    original_input=input_str,
+                    input_type='domain',  # 默认类型
+                    target_name=input_str,
+                    target_type='domain',
+                    is_valid=False,
+                    error=str(e),
+                    line_number=line_number
+                ))
+        
+        return results
+    
+    def _parse_url_input(self, url_str: str, line_number: int) -> ParsedInputDTO:
+        """
+        解析 URL 输入
+        
+        Args:
+            url_str: URL 字符串
+            line_number: 行号
+            
+        Returns:
+            ParsedInputDTO
+        """
+        # 验证 URL 格式
+        validate_url(url_str)
+        
+        # 使用标准库解析
+        parsed = urlparse(url_str)
+        
+        host = parsed.hostname  # 不含端口
+        has_path = parsed.path and parsed.path != '/'
+        
+        # 构建 root_url: scheme://host[:port]
+        root_url = f"{parsed.scheme}://{parsed.netloc}"
+        
+        # 检测 host 类型（domain 或 ip）
+        target_type = 'ip' if is_valid_ip(host) else 'domain'
+        
+        return ParsedInputDTO(
+            original_input=url_str,
+            input_type='url',
+            target_name=host,
+            target_type=target_type,
+            website_url=root_url,
+            endpoint_url=url_str if has_path else None,
+            line_number=line_number
+        )
+    
+    def _parse_target_input(
+        self, 
+        input_str: str, 
+        input_type: str, 
+        line_number: int
+    ) -> ParsedInputDTO:
+        """
+        解析非 URL 输入（domain/ip/cidr）
+        
+        Args:
+            input_str: 输入字符串
+            input_type: 输入类型
+            line_number: 行号
+            
+        Returns:
+            ParsedInputDTO
+        """
+        # 验证格式
+        if input_type == 'domain':
+            validate_domain(input_str)
+            target_type = 'domain'
+        elif input_type == 'ip':
+            validate_ip(input_str)
+            target_type = 'ip'
+        elif input_type == 'cidr':
+            validate_cidr(input_str)
+            target_type = 'cidr'
+        else:
+            raise ValueError(f"未知的输入类型: {input_type}")
+        
+        return ParsedInputDTO(
+            original_input=input_str,
+            input_type=input_type,
+            target_name=input_str,
+            target_type=target_type,
+            website_url=None,
+            endpoint_url=None,
+            line_number=line_number
+        )
+    
+    @transaction.atomic
+    def process_quick_scan(
+        self, 
+        inputs: List[str],
+        engine_id: int
+    ) -> Dict[str, Any]:
+        """
+        处理快速扫描请求
+        
+        Args:
+            inputs: 输入字符串列表
+            engine_id: 扫描引擎 ID
+            
+        Returns:
+            处理结果字典
+        """
+        # 1. 解析输入
+        parsed_inputs = self.parse_inputs(inputs)
+        
+        # 分离有效和无效输入
+        valid_inputs = [p for p in parsed_inputs if p.is_valid]
+        invalid_inputs = [p for p in parsed_inputs if not p.is_valid]
+        
+        if not valid_inputs:
+            return {
+                'targets': [],
+                'target_stats': {'created': 0, 'reused': 0, 'failed': len(invalid_inputs)},
+                'asset_stats': {'websites_created': 0, 'endpoints_created': 0},
+                'errors': [
+                    {'line_number': p.line_number, 'input': p.original_input, 'error': p.error}
+                    for p in invalid_inputs
+                ]
+            }
+        
+        # 2. 创建资产
+        asset_result = self.create_assets_from_parsed_inputs(valid_inputs)
+        
+        # 3. 返回结果
+        return {
+            'targets': asset_result['targets'],
+            'target_stats': asset_result['target_stats'],
+            'asset_stats': asset_result['asset_stats'],
+            'errors': [
+                {'line_number': p.line_number, 'input': p.original_input, 'error': p.error}
+                for p in invalid_inputs
+            ]
+        }
+    
+    def create_assets_from_parsed_inputs(
+        self, 
+        parsed_inputs: List[ParsedInputDTO]
+    ) -> Dict[str, Any]:
+        """
+        从解析结果创建资产
+        
+        Args:
+            parsed_inputs: 解析结果列表（只包含有效输入）
+            
+        Returns:
+            创建结果字典
+        """
+        # 1. 收集所有 target 数据（内存操作，去重）
+        targets_data = {}
+        for dto in parsed_inputs:
+            if dto.target_name not in targets_data:
+                targets_data[dto.target_name] = {'name': dto.target_name, 'type': dto.target_type}
+        
+        targets_list = list(targets_data.values())
+        
+        # 2. 批量创建 Target（复用现有方法）
+        target_result = self.target_service.batch_create_targets(targets_list)
+        
+        # 3. 查询刚创建的 Target，建立 name → id 映射
+        target_names = [d['name'] for d in targets_list]
+        targets = Target.objects.filter(name__in=target_names)
+        target_id_map = {t.name: t.id for t in targets}
+        
+        # 4. 收集 Website DTO（内存操作，去重）
+        website_dtos = []
+        seen_websites = set()
+        for dto in parsed_inputs:
+            if dto.website_url and dto.website_url not in seen_websites:
+                seen_websites.add(dto.website_url)
+                target_id = target_id_map.get(dto.target_name)
+                if target_id:
+                    website_dtos.append(WebSiteDTO(
+                        target_id=target_id,
+                        url=dto.website_url,
+                        host=dto.target_name
+                    ))
+        
+        # 5. 批量创建 Website（存在即跳过）
+        websites_created = 0
+        if website_dtos:
+            websites_created = self.website_repo.bulk_create_ignore_conflicts(website_dtos)
+        
+        # 6. 收集 Endpoint DTO（内存操作，去重）
+        endpoint_dtos = []
+        seen_endpoints = set()
+        for dto in parsed_inputs:
+            if dto.endpoint_url and dto.endpoint_url not in seen_endpoints:
+                seen_endpoints.add(dto.endpoint_url)
+                target_id = target_id_map.get(dto.target_name)
+                if target_id:
+                    endpoint_dtos.append(EndpointDTO(
+                        target_id=target_id,
+                        url=dto.endpoint_url,
+                        host=dto.target_name
+                    ))
+        
+        # 7. 批量创建 Endpoint（存在即跳过）
+        endpoints_created = 0
+        if endpoint_dtos:
+            endpoints_created = self.endpoint_repo.bulk_create_ignore_conflicts(endpoint_dtos)
+        
+        return {
+            'targets': list(targets),
+            'target_stats': {
+                'created': target_result['created_count'],
+                'reused': 0,  # bulk_create 无法区分新建和复用
+                'failed': target_result['failed_count']
+            },
+            'asset_stats': {
+                'websites_created': websites_created,
+                'endpoints_created': endpoints_created
+            }
+        }

backend/apps/scan/services/target_export_service.py

@@ -0,0 +1,364 @@
+"""
+目标导出服务
+
+提供统一的目标提取和文件导出功能，支持：
+- URL 导出（流式写入 + 默认值回退）
+- 域名/IP 导出（用于端口扫描）
+- 黑名单过滤集成
+"""
+
+import ipaddress
+import logging
+from pathlib import Path
+from typing import Dict, Any, Optional, Iterator
+
+from django.db.models import QuerySet
+
+from .blacklist_service import BlacklistService
+
+logger = logging.getLogger(__name__)
+
+
+class TargetExportService:
+    """
+    目标导出服务 - 提供统一的目标提取和文件导出功能
+    
+    使用方式：
+        # Task 层决定数据源
+        queryset = WebSite.objects.filter(target_id=target_id).values_list('url', flat=True)
+        
+        # 使用导出服务
+        blacklist_service = BlacklistService()
+        export_service = TargetExportService(blacklist_service=blacklist_service)
+        result = export_service.export_urls(target_id, output_path, queryset)
+    """
+    
+    def __init__(self, blacklist_service: Optional[BlacklistService] = None):
+        """
+        初始化导出服务
+        
+        Args:
+            blacklist_service: 黑名单过滤服务，None 表示禁用过滤
+        """
+        self.blacklist_service = blacklist_service
+    
+    def export_urls(
+        self,
+        target_id: int,
+        output_path: str,
+        queryset: QuerySet,
+        url_field: str = 'url',
+        batch_size: int = 1000
+    ) -> Dict[str, Any]:
+        """
+        统一 URL 导出函数
+        
+        自动判断数据库有无数据：
+        - 有数据：流式写入数据库数据到文件
+        - 无数据：调用默认值生成器生成 URL
+        
+        Args:
+            target_id: 目标 ID
+            output_path: 输出文件路径
+            queryset: 数据源 queryset（由 Task 层构建，应为 values_list flat=True）
+            url_field: URL 字段名（用于黑名单过滤）
+            batch_size: 批次大小
+            
+        Returns:
+            dict: {
+                'success': bool,
+                'output_file': str,
+                'total_count': int
+            }
+            
+        Raises:
+            IOError: 文件写入失败
+        """
+        output_file = Path(output_path)
+        output_file.parent.mkdir(parents=True, exist_ok=True)
+        
+        logger.info("开始导出 URL - target_id=%s, output=%s", target_id, output_path)
+        
+        # 应用黑名单过滤（数据库层面）
+        if self.blacklist_service:
+            # 注意：queryset 应该是原始 queryset，不是 values_list
+            # 这里假设 Task 层传入的是 values_list，需要在 Task 层处理过滤
+            pass
+        
+        total_count = 0
+        try:
+            with open(output_file, 'w', encoding='utf-8', buffering=8192) as f:
+                for url in queryset.iterator(chunk_size=batch_size):
+                    if url:
+                        # Python 层面黑名单过滤
+                        if self.blacklist_service and not self.blacklist_service.filter_url(url):
+                            continue
+                        f.write(f"{url}\n")
+                        total_count += 1
+                        
+                        if total_count % 10000 == 0:
+                            logger.info("已导出 %d 个 URL...", total_count)
+        except IOError as e:
+            logger.error("文件写入失败: %s - %s", output_path, e)
+            raise
+        
+        # 默认值回退模式
+        if total_count == 0:
+            total_count = self._generate_default_urls(target_id, output_file)
+        
+        logger.info("✓ URL 导出完成 - 数量: %d, 文件: %s", total_count, output_path)
+        
+        return {
+            'success': True,
+            'output_file': str(output_file),
+            'total_count': total_count
+        }
+
+    def _generate_default_urls(
+        self,
+        target_id: int,
+        output_path: Path
+    ) -> int:
+        """
+        默认值生成器（内部函数）
+        
+        根据 Target 类型生成默认 URL：
+        - DOMAIN: http(s)://domain
+        - IP: http(s)://ip
+        - CIDR: 展开为所有 IP 的 http(s)://ip
+        - URL: 直接使用目标 URL
+        
+        Args:
+            target_id: 目标 ID
+            output_path: 输出文件路径
+            
+        Returns:
+            int: 写入的 URL 总数
+        """
+        from apps.targets.services import TargetService
+        from apps.targets.models import Target
+        
+        target_service = TargetService()
+        target = target_service.get_target(target_id)
+        
+        if not target:
+            logger.warning("Target ID %d 不存在，无法生成默认 URL", target_id)
+            return 0
+        
+        target_name = target.name
+        target_type = target.type
+        
+        logger.info("懒加载模式：Target 类型=%s, 名称=%s", target_type, target_name)
+        
+        total_urls = 0
+        
+        with open(output_path, 'w', encoding='utf-8', buffering=8192) as f:
+            if target_type == Target.TargetType.DOMAIN:
+                urls = [f"http://{target_name}", f"https://{target_name}"]
+                for url in urls:
+                    if self._should_write_url(url):
+                        f.write(f"{url}\n")
+                        total_urls += 1
+                        
+            elif target_type == Target.TargetType.IP:
+                urls = [f"http://{target_name}", f"https://{target_name}"]
+                for url in urls:
+                    if self._should_write_url(url):
+                        f.write(f"{url}\n")
+                        total_urls += 1
+                        
+            elif target_type == Target.TargetType.CIDR:
+                try:
+                    network = ipaddress.ip_network(target_name, strict=False)
+                    
+                    for ip in network.hosts():
+                        urls = [f"http://{ip}", f"https://{ip}"]
+                        for url in urls:
+                            if self._should_write_url(url):
+                                f.write(f"{url}\n")
+                                total_urls += 1
+                        
+                        if total_urls % 10000 == 0:
+                            logger.info("已生成 %d 个 URL...", total_urls)
+                    
+                    # /32 或 /128 特殊处理
+                    if total_urls == 0:
+                        ip = str(network.network_address)
+                        urls = [f"http://{ip}", f"https://{ip}"]
+                        for url in urls:
+                            if self._should_write_url(url):
+                                f.write(f"{url}\n")
+                                total_urls += 1
+                                
+                except ValueError as e:
+                    logger.error("CIDR 解析失败: %s - %s", target_name, e)
+                    raise ValueError(f"无效的 CIDR: {target_name}") from e
+                    
+            elif target_type == Target.TargetType.URL:
+                if self._should_write_url(target_name):
+                    f.write(f"{target_name}\n")
+                    total_urls = 1
+            else:
+                logger.warning("不支持的 Target 类型: %s", target_type)
+        
+        logger.info("✓ 懒加载生成默认 URL - 数量: %d", total_urls)
+        return total_urls
+    
+    def _should_write_url(self, url: str) -> bool:
+        """检查 URL 是否应该写入（通过黑名单过滤）"""
+        if self.blacklist_service:
+            return self.blacklist_service.filter_url(url)
+        return True
+
+    def export_targets(
+        self,
+        target_id: int,
+        output_path: str,
+        batch_size: int = 1000
+    ) -> Dict[str, Any]:
+        """
+        域名/IP 导出函数（用于端口扫描）
+        
+        根据 Target 类型选择导出逻辑：
+        - DOMAIN: 从 Subdomain 表流式导出子域名
+        - IP: 直接写入 IP 地址
+        - CIDR: 展开为所有主机 IP
+        
+        Args:
+            target_id: 目标 ID
+            output_path: 输出文件路径
+            batch_size: 批次大小
+            
+        Returns:
+            dict: {
+                'success': bool,
+                'output_file': str,
+                'total_count': int,
+                'target_type': str
+            }
+        """
+        from apps.targets.services import TargetService
+        from apps.targets.models import Target
+        from apps.asset.services.asset.subdomain_service import SubdomainService
+        
+        output_file = Path(output_path)
+        output_file.parent.mkdir(parents=True, exist_ok=True)
+        
+        # 获取 Target 信息
+        target_service = TargetService()
+        target = target_service.get_target(target_id)
+        
+        if not target:
+            raise ValueError(f"Target ID {target_id} 不存在")
+        
+        target_type = target.type
+        target_name = target.name
+        
+        logger.info(
+            "开始导出扫描目标 - Target ID: %d, Name: %s, Type: %s, 输出文件: %s",
+            target_id, target_name, target_type, output_path
+        )
+        
+        total_count = 0
+        
+        if target_type == Target.TargetType.DOMAIN:
+            total_count = self._export_domains(target_id, target_name, output_file, batch_size)
+            type_desc = "域名"
+            
+        elif target_type == Target.TargetType.IP:
+            total_count = self._export_ip(target_name, output_file)
+            type_desc = "IP"
+            
+        elif target_type == Target.TargetType.CIDR:
+            total_count = self._export_cidr(target_name, output_file)
+            type_desc = "CIDR IP"
+            
+        else:
+            raise ValueError(f"不支持的目标类型: {target_type}")
+        
+        logger.info(
+            "✓ 扫描目标导出完成 - 类型: %s, 总数: %d, 文件: %s",
+            type_desc, total_count, output_path
+        )
+        
+        return {
+            'success': True,
+            'output_file': str(output_file),
+            'total_count': total_count,
+            'target_type': target_type
+        }
+    
+    def _export_domains(
+        self,
+        target_id: int,
+        target_name: str,
+        output_path: Path,
+        batch_size: int
+    ) -> int:
+        """导出域名类型目标的子域名"""
+        from apps.asset.services.asset.subdomain_service import SubdomainService
+        
+        subdomain_service = SubdomainService()
+        domain_iterator = subdomain_service.iter_subdomain_names_by_target(
+            target_id=target_id,
+            chunk_size=batch_size
+        )
+        
+        total_count = 0
+        with open(output_path, 'w', encoding='utf-8', buffering=8192) as f:
+            for domain_name in domain_iterator:
+                if self._should_write_target(domain_name):
+                    f.write(f"{domain_name}\n")
+                    total_count += 1
+                    
+                    if total_count % 10000 == 0:
+                        logger.info("已导出 %d 个域名...", total_count)
+        
+        # 默认值模式：如果没有子域名，使用根域名
+        if total_count == 0:
+            logger.info("采用默认域名：%s (target_id=%d)", target_name, target_id)
+            if self._should_write_target(target_name):
+                with open(output_path, 'w', encoding='utf-8') as f:
+                    f.write(f"{target_name}\n")
+                total_count = 1
+        
+        return total_count
+    
+    def _export_ip(self, target_name: str, output_path: Path) -> int:
+        """导出 IP 类型目标"""
+        if self._should_write_target(target_name):
+            with open(output_path, 'w', encoding='utf-8') as f:
+                f.write(f"{target_name}\n")
+            return 1
+        return 0
+    
+    def _export_cidr(self, target_name: str, output_path: Path) -> int:
+        """导出 CIDR 类型目标，展开为每个 IP"""
+        network = ipaddress.ip_network(target_name, strict=False)
+        total_count = 0
+        
+        with open(output_path, 'w', encoding='utf-8', buffering=8192) as f:
+            for ip in network.hosts():
+                ip_str = str(ip)
+                if self._should_write_target(ip_str):
+                    f.write(f"{ip_str}\n")
+                    total_count += 1
+                    
+                    if total_count % 10000 == 0:
+                        logger.info("已导出 %d 个 IP...", total_count)
+        
+        # /32 或 /128 特殊处理
+        if total_count == 0:
+            ip_str = str(network.network_address)
+            if self._should_write_target(ip_str):
+                with open(output_path, 'w', encoding='utf-8') as f:
+                    f.write(f"{ip_str}\n")
+                total_count = 1
+        
+        return total_count
+    
+    def _should_write_target(self, target: str) -> bool:
+        """检查目标是否应该写入（通过黑名单过滤）"""
+        if self.blacklist_service:
+            return self.blacklist_service.filter_url(target)
+        return True

backend/apps/scan/tasks/__init__.py

@@ -9,9 +9,6 @@
 - Tasks 负责具体操作，Flow 负责编排
 """
 
-# Prefect Tasks
-from .workspace_tasks import create_scan_workspace_task
-
 # 子域名发现任务（已重构为多个子任务）
 from .subdomain_discovery import (
     run_subdomain_discovery_task,
@@ -19,17 +16,25 @@ from .subdomain_discovery import (
     save_domains_task,
 )
 
+# 指纹识别任务
+from .fingerprint_detect import (
+    export_urls_for_fingerprint_task,
+    run_xingfinger_and_stream_update_tech_task,
+)
+
 # 注意：
 # - subdomain_discovery_task 已重构为多个子任务（subdomain_discovery/）
 # - finalize_scan_task 已废弃（Handler 统一管理状态）
 # - initiate_scan_task 已迁移到 flows/initiate_scan_flow.py
 # - cleanup_old_scans_task 已迁移到 flows（cleanup_old_scans_flow）
+# - create_scan_workspace_task 已删除，直接使用 setup_scan_workspace()
 
 __all__ = [
-    # Prefect Tasks
-    'create_scan_workspace_task',
     # 子域名发现任务
     'run_subdomain_discovery_task',
     'merge_and_validate_task',
     'save_domains_task',
+    # 指纹识别任务
+    'export_urls_for_fingerprint_task',
+    'run_xingfinger_and_stream_update_tech_task',
 ]

backend/apps/scan/tasks/directory_scan/export_sites_task.py

@@ -1,13 +1,14 @@
 """
 导出站点 URL 到 TXT 文件的 Task
 
-使用流式处理，避免大量站点导致内存溢出
+使用 TargetExportService 统一处理导出逻辑和默认值回退
+数据源: WebSite.url
 """
 import logging
-from pathlib import Path
 from prefect import task
 
-from apps.asset.repositories import DjangoWebSiteRepository
+from apps.asset.models import WebSite
+from apps.scan.services import TargetExportService, BlacklistService
 
 logger = logging.getLogger(__name__)
 
@@ -16,12 +17,18 @@ logger = logging.getLogger(__name__)
 def export_sites_task(
     target_id: int,
     output_file: str,
-    batch_size: int = 1000
+    batch_size: int = 1000,
 ) -> dict:
     """
     导出目标下的所有站点 URL 到 TXT 文件
 
-    使用流式处理，支持大规模数据导出（10万+站点）
+    数据源: WebSite.url
+    
+    懒加载模式：
+    - 如果数据库为空，根据 Target 类型生成默认 URL
+    - DOMAIN: http(s)://domain
+    - IP: http(s)://ip
+    - CIDR: 展开为所有 IP 的 URL
 
     Args:
         target_id: 目标 ID
@@ -39,56 +46,26 @@ def export_sites_task(
         ValueError: 参数错误
         IOError: 文件写入失败
     """
-    try:
-        # 初始化 Repository
-        repository = DjangoWebSiteRepository()
-
-        logger.info("开始导出站点 URL - Target ID: %d, 输出文件: %s", target_id, output_file)
-
-        # 确保输出目录存在
-        output_path = Path(output_file)
-        output_path.parent.mkdir(parents=True, exist_ok=True)
-
-        # 使用 Repository 流式查询站点 URL
-        url_iterator = repository.get_urls_for_export(
-            target_id=target_id,
-            batch_size=batch_size
-        )
-
-        # 流式写入文件
-        total_count = 0
-        with open(output_path, 'w', encoding='utf-8', buffering=8192) as f:
-            for url in url_iterator:
-                # 每次只处理一个 URL，边读边写
-                f.write(f"{url}\n")
-                total_count += 1
-
-                # 每写入 10000 条记录打印一次进度
-                if total_count % 10000 == 0:
-                    logger.info("已导出 %d 个站点 URL...", total_count)
-
-        logger.info(
-            "✓ 站点 URL 导出完成 - 总数: %d, 文件: %s (%.2f KB)",
-            total_count,
-            str(output_path),  # 使用绝对路径
-            output_path.stat().st_size / 1024
-        )
-
-        return {
-            'success': True,
-            'output_file': str(output_path),
-            'total_count': total_count
-        }
-
-    except FileNotFoundError as e:
-        logger.error("输出目录不存在: %s", e)
-        raise
-    except PermissionError as e:
-        logger.error("文件写入权限不足: %s", e)
-        raise
-    except Exception as e:
-        logger.exception("导出站点 URL 失败: %s", e)
-        raise
+    # 构建数据源 queryset（Task 层决定数据源）
+    queryset = WebSite.objects.filter(target_id=target_id).values_list('url', flat=True)
+    
+    # 使用 TargetExportService 处理导出
+    blacklist_service = BlacklistService()
+    export_service = TargetExportService(blacklist_service=blacklist_service)
+    
+    result = export_service.export_urls(
+        target_id=target_id,
+        output_path=output_file,
+        queryset=queryset,
+        batch_size=batch_size
+    )
+    
+    # 保持返回值格式不变（向后兼容）
+    return {
+        'success': result['success'],
+        'output_file': result['output_file'],
+        'total_count': result['total_count']
+    }
 
 
 

backend/apps/scan/tasks/directory_scan/run_and_stream_save_directories_task.py

@@ -30,7 +30,6 @@ from django.db import IntegrityError, OperationalError, DatabaseError
 from psycopg2 import InterfaceError
 from dataclasses import dataclass
 
-from apps.asset.services import WebSiteService
 from apps.asset.dtos.snapshot import DirectorySnapshotDTO
 from apps.scan.utils import execute_stream
 
@@ -48,7 +47,6 @@ class ServiceSet:
     
     提供目录扫描所需的 Service 实例，便于测试时注入 Mock 对象
     """
-    website: WebSiteService
     snapshot: "DirectorySnapshotsService"
     
     @classmethod
@@ -56,7 +54,6 @@ class ServiceSet:
         """创建默认的 Service 集合"""
         from apps.asset.services.snapshot import DirectorySnapshotsService
         return cls(
-            website=WebSiteService(),
             snapshot=DirectorySnapshotsService()
         )
 
@@ -79,19 +76,19 @@ def _parse_and_validate_line(line: str) -> Optional[dict]:
     try:
         # 步骤 1: 解析 JSON
         try:
-            line_data = json.loads(line)
+            line_data = json.loads(line, strict=False)
         except json.JSONDecodeError:
-            # logger.debug("跳过非 JSON 格式的行: %s", line[:100])
+            # logger.debug("跳过非 JSON 行: %s", line)
             return None
         
         # 步骤 2: 验证数据类型
         if not isinstance(line_data, dict):
-            logger.warning("解析后的数据不是字典类型，跳过: %s", str(line_data)[:100])
+            logger.debug("跳过非字典数据")
             return None
         
         # 步骤 3: 验证必要字段
         if not line_data.get('url'):
-            logger.debug("URL 为空，跳过")
+            logger.info("URL 为空，跳过 - 数据: %s", str(line_data)[:200])
             return None
         
         # 返回有效记录
@@ -105,8 +102,8 @@ def _parse_and_validate_line(line: str) -> Optional[dict]:
             'duration': line_data.get('duration')
         }
     
-    except Exception as e:
-        logger.error("解析行数据异常: %s - 数据: %s", e, line[:100])
+    except Exception:
+        logger.info("跳过无法解析的行: %s", line[:100])
         return None
 
 
@@ -176,7 +173,6 @@ def _parse_ffuf_stream_output(
 
 def _save_batch_with_retry(
     batch: list,
-    website_id: int,
     scan_id: int,
     target_id: int,
     batch_num: int,
@@ -188,7 +184,6 @@ def _save_batch_with_retry(
     
     Args:
         batch: 数据批次
-        website_id: 站点 ID
         scan_id: 扫描任务ID
         target_id: 目标ID
         batch_num: 批次编号
@@ -203,7 +198,7 @@ def _save_batch_with_retry(
     """
     for attempt in range(max_retries):
         try:
-            count = _save_batch(batch, website_id, scan_id, target_id, batch_num, services)
+            count = _save_batch(batch, scan_id, target_id, batch_num, services)
             return {
                 'success': True,
                 'created_directories': count
@@ -257,7 +252,6 @@ def _save_batch_with_retry(
 
 def _save_batch(
     batch: list,
-    website_id: int,
     scan_id: int,
     target_id: int,
     batch_num: int,
@@ -267,7 +261,7 @@ def _save_batch(
     保存一个批次的数据到数据库（使用快照 Service）
     
     数据关系链：
-        WebSite (已存在) → DirectorySnapshot (待创建) → Directory (自动同步)
+        Target → DirectorySnapshot (待创建) → Directory (自动同步)
     
     处理流程：
         1. 构建 DirectorySnapshotDTO：包含 scan_id 和 target_id
@@ -275,7 +269,6 @@ def _save_batch(
     
     Args:
         batch: 数据批次，list of dict
-        website_id: 站点 ID
         scan_id: 扫描任务 ID
         target_id: 目标 ID
         batch_num: 批次编号（用于日志）
@@ -289,14 +282,11 @@ def _save_batch(
         return 0
     
     # ========== Step 1: 准备 DirectorySnapshot 数据（内存操作，无需事务）==========
-    snapshot_items = []
-    
-    for record in batch:
-        # 创建 DirectorySnapshot DTO
-        snapshot_dto = DirectorySnapshotDTO(
+    # 使用列表推导式构建 DTO 列表
+    snapshot_items = [
+        DirectorySnapshotDTO(
             scan_id=scan_id,
-            website_id=website_id,
-            target_id=target_id,  # 冗余字段，用于同步到资产表
+            target_id=target_id,
             url=record['url'],
             status=record.get('status'),
             content_length=record.get('length'),
@@ -305,8 +295,8 @@ def _save_batch(
             content_type=record.get('content_type', ''),
             duration=record.get('duration')
         )
-        
-        snapshot_items.append(snapshot_dto)
+        for record in batch
+    ]
     
     # ========== Step 2: 保存快照并同步到资产表（通过快照 Service）==========
     if snapshot_items:
@@ -373,19 +363,10 @@ def run_and_stream_save_directories_task(
         # 1. 初始化服务
         services = ServiceSet.create_default()
         
-        # 2. 查找站点（使用 Service）
-        website_id = services.website.get_by_url(url=site_url, target_id=target_id)
-        
-        if website_id is None:
-            logger.error("站点不存在: %s", site_url)
-            raise ValueError(f"站点不存在: {site_url}")
-        
-        logger.info("找到站点: %s (ID: %d)", site_url, website_id)
-        
-        # 3. 初始化资源
+        # 2. 初始化资源（不再需要查找 WebSite，Directory 直接关联 Target）
         data_generator = _parse_ffuf_stream_output(cmd=cmd, tool_name=tool_name, cwd=cwd, shell=shell, timeout=timeout, log_file=log_file)
         
-        # 4. 流式处理记录并分批保存
+        # 3. 流式处理记录并分批保存
         total_records = 0
         batch_num = 0
         failed_batches = []
@@ -400,7 +381,7 @@ def run_and_stream_save_directories_task(
             if len(batch) >= batch_size:
                 batch_num += 1
                 result = _save_batch_with_retry(
-                    batch, website_id, scan_id, target_id, batch_num, services
+                    batch, scan_id, target_id, batch_num, services
                 )
                 
                 total_created += result.get('created_directories', 0)
@@ -421,7 +402,7 @@ def run_and_stream_save_directories_task(
         if batch:
             batch_num += 1
             result = _save_batch_with_retry(
-                batch, website_id, scan_id, target_id, batch_num, services
+                batch, scan_id, target_id, batch_num, services
             )
             total_created += result.get('created_directories', 0)