Project Overview
This project aims to develop an autonomous multi-agent system that detects, analyzes, and mitigates cybersecurity threats in real-time. The system will use LLM-powered agents for threat intelligence gathering, automated reasoning, and adaptive response planning.

Key Innovation Areas
✅ Multi-Agent Collaboration: Agents communicate to share insights and dynamically respond to evolving threats.
✅ Memory & Context Management: Uses Vector DB (Qdrant/Milvus) and Knowledge Graphs (Neo4j) for long-term learning.
✅ Chain-of-Thought & Tool Use: The AI will reason through potential cyber threats and autonomously deploy countermeasures via API calls.
✅ LLM Workflow Integration: LangChain + FastAPI + Jinja2 to build the system with a user-friendly interface.
✅ Task Decomposition & Planning: AI decomposes security alerts into sub-tasks (e.g., log analysis, anomaly detection, action recommendation).

Technical Stack