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
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"""
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漏洞类型知识模块
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包含各种漏洞类型的专业知识
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"""
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from .injection import SQL_INJECTION, NOSQL_INJECTION, COMMAND_INJECTION, CODE_INJECTION
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from .xss import XSS_REFLECTED, XSS_STORED, XSS_DOM
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from .auth import AUTH_BYPASS, IDOR, BROKEN_ACCESS_CONTROL
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from .crypto import WEAK_CRYPTO, HARDCODED_SECRETS
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from .ssrf import SSRF
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from .deserialization import INSECURE_DESERIALIZATION
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from .path_traversal import PATH_TRAVERSAL
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from .xxe import XXE
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from .race_condition import RACE_CONDITION
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from .csrf import CSRF
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from .business_logic import BUSINESS_LOGIC, RATE_LIMITING
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from .open_redirect import OPEN_REDIRECT
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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
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# 所有漏洞知识文档
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ALL_VULNERABILITY_DOCS = [
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# 注入类
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SQL_INJECTION,
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NOSQL_INJECTION,
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COMMAND_INJECTION,
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CODE_INJECTION,
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# XSS类
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XSS_REFLECTED,
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XSS_STORED,
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XSS_DOM,
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# 认证授权类
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AUTH_BYPASS,
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IDOR,
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BROKEN_ACCESS_CONTROL,
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# 加密类
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WEAK_CRYPTO,
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HARDCODED_SECRETS,
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2025-12-13 12:35:03 +08:00
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# 请求伪造
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CSRF,
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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
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SSRF,
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2025-12-13 12:35:03 +08:00
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# 其他
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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
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INSECURE_DESERIALIZATION,
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PATH_TRAVERSAL,
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XXE,
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RACE_CONDITION,
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2025-12-13 12:35:03 +08:00
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BUSINESS_LOGIC,
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RATE_LIMITING,
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OPEN_REDIRECT,
|
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
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]
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__all__ = [
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"ALL_VULNERABILITY_DOCS",
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2025-12-13 12:35:03 +08:00
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# 注入类
|
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
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"SQL_INJECTION",
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"NOSQL_INJECTION",
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"COMMAND_INJECTION",
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"CODE_INJECTION",
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2025-12-13 12:35:03 +08:00
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# XSS类
|
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
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"XSS_REFLECTED",
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"XSS_STORED",
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"XSS_DOM",
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2025-12-13 12:35:03 +08:00
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# 认证授权类
|
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
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"AUTH_BYPASS",
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"IDOR",
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"BROKEN_ACCESS_CONTROL",
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2025-12-13 12:35:03 +08:00
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# 加密类
|
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
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"WEAK_CRYPTO",
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"HARDCODED_SECRETS",
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2025-12-13 12:35:03 +08:00
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# 请求伪造
|
|
|
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"CSRF",
|
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
|
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"SSRF",
|
2025-12-13 12:35:03 +08:00
|
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|
# 其他
|
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
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"INSECURE_DESERIALIZATION",
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"PATH_TRAVERSAL",
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"XXE",
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"RACE_CONDITION",
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2025-12-13 12:35:03 +08:00
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"BUSINESS_LOGIC",
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"RATE_LIMITING",
|
|
|
|
|
"OPEN_REDIRECT",
|
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
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]
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2025-12-13 12:35:03 +08:00
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