pentagi
Fully autonomous AI Agents system capable of performing complex penetration testing tasks
- 32.1k stars
- 5k forks
- 51 open issues
- Language: Go
- License: MIT
- updated
Install
git clone https://github.com/vxcontrol/pentagi && cp pentagi/*.md ~/.claude/agents/- Clone the repository and copy the agent .md definitions into ~/.claude/agents (or .claude/agents inside a project).
- Start a new Claude Code session to load the agents.
- Delegate work to them with the Task/Agent tool or by name.
Editor's note
PentAGI is a self-hosted, multi-agent penetration testing system written in Go that autonomously plans and executes security assessments inside sandboxed Docker containers. Users submit a target and objective through a React web interface or via REST and GraphQL APIs, whereupon a supervisor agent breaks the work into subtasks delegated to specialist subagents for research, development, and infrastructure operations. Those agents invoke a built-in suite of over 20 security tools including nmap, Metasploit, and sqlmap, and can query external sources through Tavily, Sploitus, and Perplexity integrations. The system connects to Claude through the Anthropic API as one of ten supported LLM providers, configurable per agent role, and stores all command output in PostgreSQL with the pgvector extension to support long-term memory and a Graphiti-powered Neo4j knowledge graph. Grafana and Prometheus handle observability, and Langfuse can capture LLM traces. The standout architectural detail is smart container selection, where the supervisor automatically picks the appropriate Docker image based on the specific tooling a subtask requires. Security researchers and professional penetration testers conducting authorized assessments are the primary audience.
Subagents overview
PentAGI
Penetration testing Artificial General Intelligence
Join the Community! Connect with security researchers, AI enthusiasts, and fellow ethical hackers. Get support, share insights, and stay updated with the latest PentAGI developments.
Table of Contents
Overview
PentAGI is an open-source, self-hosted multi-agent system for autonomous penetration testing. You describe a target and a goal in plain language; a team of specialized AI agents plans the work, runs 20+ professional tools such as nmap, Metasploit and sqlmap inside an isolated Docker sandbox, remembers what it learned and hands you a report.
Who it is for. Security engineers, penetration testers, researchers and red teams who want an autonomous assistant on their own infrastructure, for authorized testing only.
What sets it apart. It runs on your own servers with the model of your choice: 10+ cloud LLM providers, your own OpenAI-compatible gateway, or local models through Ollama or vLLM. Results and successful approaches are kept in PostgreSQL with pgvector for later flows, an optional Neo4j knowledge graph tracks hosts, services and findings, execution monitoring and task planning help smaller open models, and REST and GraphQL APIs automate it. PentAGI Enterprise adds agent profiles, plugins and MCP servers, customer-ready reports and a real-time attack-chain view.
How to install. An interactive installer for Linux, macOS and Windows sets PentAGI up with Docker Compose — see Quick Start.
PentAGI is developed by VXControl, a security engineering company based in Dubai.
You can watch the video PentAGI overview:
Features
Secure & Isolated. All operations are performed in a sandboxed Docker environment with complete isolation.
Fully Autonomous. AI-powered agent that automatically determines and executes penetration testing steps with optional execution monitoring and intelligent task planning for enhanced reliability.
Professional Pentesting Tools. Built-in suite of 20+ professional security tools including nmap, metasploit, sqlmap, and more.
Smart Memory System. Long-term storage of research results and successful approaches for future use.
Optional Knowledge Graph Integration. Graphiti-powered knowledge graph using Neo4j for semantic relationship tracking and advanced context understanding.
Web Intelligence. Built-in browser via scraper for gathering latest information from web sources.
External Search Systems. Integration with advanced search APIs including Tavily, Firecrawl, Traversaal, Perplexity, DuckDuckGo, Google Custom Search, Sploitus Search and SearXNG for comprehensive information gathering.
Team of Specialists. Delegation system with specialized AI agents for research, development, and infrastructure tasks, enhanced with optional execution monitoring and intelligent task planning for optimal performance with smaller models.
Comprehensive Monitoring. Detailed logging and integration with Grafana/Prometheus for real-time system observation.
Detailed Reporting. Generation of thorough vulnerability reports with exploitation guides.
Smart Container Management. Automatic Docker image selection based on specific task requirements.
Modern Interface. Clean and intuitive web UI for system management and monitoring.
Comprehensive APIs. Full-featured REST and GraphQL APIs with Bearer token authentication for automation and integration.
Persistent Storage. All commands and outputs are stored in PostgreSQL with pgvector extension.
Scalable Architecture. Microservices-based design supporting horizontal scaling.
Self-Hosted Solution. Complete control over your deployment and data.
Flexible Authentication. Support for 10+ LLM providers (OpenAI, Anthropic, Google AI/Gemini, AWS Bedrock, Ollama, DeepSeek, GLM, Kimi, Qwen, MiniMax, Mistral, xAI, Custom for any OpenAI-compatible endpoint including Azure OpenAI) plus aggregators (OpenRouter, DeepInfra, Atlas Cloud, OpenCode Go plan). For production local deployments, see our vLLM + Qwen3.5-27B-FP8 guide.
API Token Authentication. Secure Bearer token system for programmatic access to REST and GraphQL APIs.
Quick Deployment. Easy setup through Docker Compose with comprehensive environment configuration.
Current Capability Boundaries
PentAGI today is an autonomous and assistant-guided penetration testing platform, not a CALDERA-style Breach and Attack Simulation (BAS) or adversary emulation product with predefined campaigns or attack plans.
BAS-like agent-authored attack scripts should be treated as conceptual or future work, not as a feature that is implemented today.
The current flow report UI supports web view, copy to clipboard, Markdown download, and PDF download. JSON flow-report export is not documented as a supported output format today.
Provider flexibility is available today through built-in providers and custom/OpenAI-compatible endpoints. See Custom LLM Provider Configuration and the vLLM + Qwen3.5-27B-FP8 guide.
What people ask about pentagi
What is vxcontrol/pentagi?
vxcontrol/pentagi is subagents for the Claude AI ecosystem. Fully autonomous AI Agents system capable of performing complex penetration testing tasks It has 32.1k GitHub stars and its last recorded update is dated 2026-10-22.
How do I install pentagi?
You can install pentagi by cloning the repository (https://github.com/vxcontrol/pentagi) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
Is vxcontrol/pentagi safe to use?
Our security agent has analyzed vxcontrol/pentagi and assigned a Trust Score of 100/100 (tier: Verified). See the full breakdown of passed checks and flags on this page.
Who maintains vxcontrol/pentagi?
vxcontrol/pentagi is maintained by vxcontrol. The last recorded GitHub activity is dated 2026-10-22, with 51 open issues.
Are there alternatives to pentagi?
Yes. On ClaudeWave you can browse similar subagents at /categories/agents, sorted by popularity or recent activity.
Maintain this repo? Show its Trust Score in your README
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