TBHM is a comprehensive bug bounty and penetration testing platform that combines automated reconnaissance, vulnerability scanning, and AI-powered analysis following Jason Haddix's methodology. The application leverages private AI models to provide intelligent insights and decision-making throughout the security assessment process.
- Private AI Integration: Local LLM deployment for secure, offline analysis
- Comprehensive Reconnaissance: Asset discovery, subdomain enumeration, and attack surface mapping
- Advanced Scanning: Technology profiling, content discovery, and vulnerability automation
- AI-Driven Insights: Intelligent heat mapping and vulnerability prioritization
- Scalable Architecture: Kubernetes orchestration for high-concurrency operations
- Interactive Dashboard: Real-time monitoring and AI-assisted analysis
- Backend: Python FastAPI with Celery task queuing
- Performance Layer: Go wrappers for high-performance scanning
- Databases: PostgreSQL (data), Neo4j (relationships), Redis (caching)
- AI Engine: Ollama/vLLM with LangChain/CrewAI agents
- Orchestration: Docker containers with Kubernetes scaling
See TODO.md for the detailed development plan organized by phases.
Coming soon - Infrastructure setup and deployment guides
Coming soon - Development guidelines and contribution process
To be determined