PentAGI
Penetration testing Artificial General Intelligence
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Table of Contents
- Overview
- Features
- Architecture
- Quick Start
- How to Use PentAGI After Login
- API Access
- Advanced Setup
- 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
Container Architecture (click to expand)
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
G