PentAGI

<div align="center" style="font-size: 1.5em; margin: 20px 0;"> <strong>P</strong>enetration testing <strong>A</strong>rtificial <strong>G</strong>eneral <strong>I</strong>ntelligence </div> <br> <div align="center">

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.

⠀

<a href="https://trendshift.io/repositories/15161" target="_blank"><img src="https://trendshift.io/api/badge/repositories/15161" alt="vxcontrol%2Fpentagi | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>

</div>

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
    • Ollama
    • OpenAI
    • Anthropic
    • Google AI (Gemini)
    • AWS Bedrock
    • DeepSeek
    • GLM
    • Kimi
    • Qwen
    • MiniMax
• 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, Custom) 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

flowchart TB
    classDef person fill:#08427B,stroke:#073B6F,color:#fff
    classDef system fill:#1168BD,stroke:#0B4884,color:#fff
    classDef external fill:#666666,stroke:#0B4884,color:#fff

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

    pentagi["✨ PentAGI
    (Autonomous penetration testing system)"]

    target["🎯 target-system
    (System under test)"]
    llm["🧠 llm-provider
    (OpenAI/Anthropic/Ollama/Bedrock/Gemini/Custom)"]
    search["🔍 search-systems
    (Google/DuckDuckGo/Tavily/Firecrawl/Traversaal/Perplexity/Sploitus/Searxng)"]
    langfuse["📊 langfuse-ui
    (LLM Observability Dashboard)"]
    grafana["📈 grafana
    (System Monitoring Dashboard)"]

    pentester --> |Uses HTTPS| pentagi
    pentester --> |Monitors AI HTTPS| langfuse
    pentester --> |Monitors System HTTPS| grafana
    pentagi --> |Tests Various protocols| target
    pentagi --> |Queries HTTPS| llm
    pentagi --> |Searches HTTPS| search
    pentagi --> |Reports HTTPS| langfuse
    pentagi --> |Reports HTTPS| grafana

    class pentester person
    class pentagi system
    class target,llm,search,langfuse,grafana external

    linkStyle default stroke:#ffffff,color:#ffffff

<details> <summary><b>Container Architecture</b> (click to expand)</summary>

graph TB
    subgraph Core Services
        UI[Frontend UI<br/>React + TypeScript]
        API[Backend API<br/>Go + GraphQL]
        DB[(Vector Store<br/>PostgreSQL + pgvector)]
        MQ[Task Queue<br/>Async Processing]
        Agent[AI Agents<br/>Multi-Agent System]
    end

    subgraph Knowledge Graph
        Graphiti[Graphiti<br/>Knowledge Graph API]
        Neo4j[(Neo4j<br/>Graph Database)]
    end

    subgraph Monitoring
        Grafana[Grafana<br/>Dashboards]
        VictoriaMetrics[VictoriaMetrics<br/>Time-series DB]
        Jaeger[Jaeger<br/>Distributed Tracing]
        Loki[Loki<br/>Log Aggregation]
        OTEL[OpenTelemetry<br/>Data Collection]
    end

    subgraph Analytics
        Langfuse[Langfuse<br/>LLM Analytics]
        ClickHouse[ClickHouse<br/>Analytics DB]
        Redis[Redis<br/>Cache + Rate Limiter]
        MinIO[MinIO<br/>S3 Storage]
    end

    subgraph Security Tools
        Scraper[Web Scraper<br/>Isolated Browser]
        PenTest[Security Tools<br/>20+ Pro Tools<br/>Sandboxed Execution]
    end

    UI --> |HTTP/WS| API
    API --> |SQL| DB
    API --> |Events| MQ
    MQ --> |Tasks| Agent
    Agent --> |Commands| PenTest
    Agent --> |Queries| DB
    Agent --> |Knowledge| Graphiti
    Graphiti --> |Graph| Neo4j

    API --> |Telemetry| OTEL
    OTEL --> |Metrics| VictoriaMetrics
    OTEL --> |Traces| Jaeger
    OTEL --> |Logs| Loki

    Grafana --> |Query| VictoriaMetrics
    Grafana -