PentAGI

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 innovative tool for automated security testing that leverages cutting-edge artificial intelligence technologies. The project is designed for information security professionals, researchers, and enthusiasts who need a powerful and flexible solution for conducting penetration tests.

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.

Architecture

System Context

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    classDef system fill:#1168BD,stroke:#0B4884,color:#fff
    classDef external fill:#666666,stroke:#0B4884,color:#fff

    pentester["👤 Security Engineer
    (User of the system)"]