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pentagi — Fully autonomous AI Agents system capable of performing complex penetration testing tasks | Kitploit
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GitHubvxcontrol/pentagi

pentagi

Fully autonomous AI Agents system capable of performing complex penetration testing tasks

21.8k2.9k14311 days agoReviewed by Kitploit
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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.

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vxcontrol%2Fpentagi | Trendshift vxcontrol%2Fpentagi | Trendshift

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Table of Contents

  • Overview
  • Features
  • Architecture
    • Agent Supervision
  • Quick Start
    • Agent Docker Access
    • Running Several Instances
  • How to Use PentAGI After Login
  • API Access
    • LLM Provider Configuration
      • Azure OpenAI
      • Ollama
      • OpenAI
      • Anthropic
      • Google AI (Gemini)
      • AWS Bedrock
      • DeepSeek
      • GLM
      • Kimi
      • Qwen
      • MiniMax
      • Mistral
      • xAI (Grok)
  • Advanced Setup
    • Langfuse Integration
    • Monitoring and Observability
    • Knowledge Graph (Graphiti)
    • OAuth Integration
    • Docker Image Configuration
  • Development
  • Testing LLM Agents
  • Embedding Configuration and Testing
  • Function Testing with ftester
  • Building
  • Credits
  • License

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: PentAGI Overview Video

Features

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