33rd of 3 in Security
pentagi
Autonomous multi-agent penetration testing system with sandboxed security tools
- Stars
- 25.3k
- License
- MIT
- Last commit
- Oct 2026
- Last release
- Oct 2026
- Language
- Go
Missed the latest GitHub check; these facts may be older.
Overview
PentAGI takes a target and goal in plain language, then uses a team of specialized agents (orchestrator, researcher, developer, executor) to plan and run 20+ tools such as nmap, Metasploit and sqlmap inside an isolated Docker sandbox. Findings are stored in PostgreSQL with pgvector, with an optional Neo4j/Graphiti knowledge graph, and it produces vulnerability reports. It works with 10+ LLM providers, any OpenAI-compatible endpoint, or local models via Ollama or vLLM.
Who it is for: Security engineers, pentesters and red teams doing authorized testing
Strengths
- Runs 20+ pentest tools (nmap, Metasploit, sqlmap) in an isolated Docker sandbox
- Supports 10+ LLM providers, custom OpenAI-compatible endpoints, and local Ollama or vLLM
- Persistent memory in PostgreSQL with pgvector, optional Neo4j knowledge graph via Graphiti
- REST and GraphQL APIs with Bearer tokens; Langfuse, Grafana and Prometheus integrations
Weaknesses
- Full stack spans many containers (Postgres, Neo4j, Langfuse, ClickHouse, Grafana), heavy to self-host
- Agent profiles, plugins, MCP servers and attack-chain view are Enterprise-only
- Not a BAS or adversary emulation tool; no predefined campaigns
- Report export limited to web, Markdown and PDF; no JSON export
What it needs
- GPU optional
- Docker + Compose
- Needs Docker, Docker Compose, PostgreSQL with pgvector, Neo4j (optional), Langfuse (optional), Grafana/Prometheus (optional)
- Models: OpenAI, Anthropic, Google Gemini, AWS Bedrock, Ollama