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Commit Graph

Author	SHA1	Message	Date
lintsinghua	6d98f29fa6	feat: 新增安全工具集成和漏洞知识库扩展 - 添加 Bandit 和 Safety 安全工具到依赖项 - 新增 CSRF、业务逻辑和开放重定向漏洞知识文档 - 实现安全工具一键安装脚本和文档 - 改进模式匹配工具支持直接文件扫描 - 增强遥测模块和 Agent 审计功能 - 修复验证节点中 findings 合并逻辑 - 优化前端 Agent 审计界面和状态展示	2025-12-13 12:35:03 +08:00
lintsinghua	f05c0073e1	feat(agent): implement comprehensive agent architecture with knowledge base and persistence layer - Add database migrations for agent checkpoints and tree node tracking - Implement core agent execution framework with executor, state management, and message handling - Create knowledge base system with framework-specific modules (Django, FastAPI, Flask, Express, React, Supabase) - Add vulnerability knowledge modules covering authentication, cryptography, injection, XSS, XXE, SSRF, path traversal, deserialization, and race conditions - Introduce new agent tools: thinking tool, reporting tool, and agent-specific utilities - Implement LLM memory compression and prompt caching for improved performance - Add agent registry and persistence layer for checkpoint management - Refactor agent implementations (analysis, recon, verification, orchestrator) with enhanced capabilities - Remove legacy agent implementations (analysis_v2, react_agent) - Update API endpoints for agent task creation and project management - Add frontend components for agent task creation and enhanced audit UI - Consolidate agent service architecture with improved separation of concerns - This refactoring provides a scalable foundation for multi-agent collaboration with knowledge-driven decision making and state persistence	2025-12-12 15:27:12 +08:00

Author

SHA1

Message

Date

lintsinghua

6d98f29fa6

feat: 新增安全工具集成和漏洞知识库扩展

- 添加 Bandit 和 Safety 安全工具到依赖项
- 新增 CSRF、业务逻辑和开放重定向漏洞知识文档
- 实现安全工具一键安装脚本和文档
- 改进模式匹配工具支持直接文件扫描
- 增强遥测模块和 Agent 审计功能
- 修复验证节点中 findings 合并逻辑
- 优化前端 Agent 审计界面和状态展示

2025-12-13 12:35:03 +08:00

lintsinghua

f05c0073e1

feat(agent): implement comprehensive agent architecture with knowledge base and persistence layer

- Add database migrations for agent checkpoints and tree node tracking
- Implement core agent execution framework with executor, state management, and message handling
- Create knowledge base system with framework-specific modules (Django, FastAPI, Flask, Express, React, Supabase)
- Add vulnerability knowledge modules covering authentication, cryptography, injection, XSS, XXE, SSRF, path traversal, deserialization, and race conditions
- Introduce new agent tools: thinking tool, reporting tool, and agent-specific utilities
- Implement LLM memory compression and prompt caching for improved performance
- Add agent registry and persistence layer for checkpoint management
- Refactor agent implementations (analysis, recon, verification, orchestrator) with enhanced capabilities
- Remove legacy agent implementations (analysis_v2, react_agent)
- Update API endpoints for agent task creation and project management
- Add frontend components for agent task creation and enhanced audit UI
- Consolidate agent service architecture with improved separation of concerns
- This refactoring provides a scalable foundation for multi-agent collaboration with knowledge-driven decision making and state persistence

2025-12-12 15:27:12 +08:00

2 Commits