Fully autonomous AI Agents system capable of performing complex penetration testing tasks
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.
- ✓Open-source license (MIT)
- ✓Actively maintained (<30d)
- ✓Healthy fork ratio
- ✓Clear description
- ✓Topics declared
- ✓Mature repo (>1y old)
git clone https://github.com/vxcontrol/pentagi && cp pentagi/*.md ~/.claude/agents/Resumen de Subagents
# PentAGI
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<strong>P</strong>enetration testing <strong>A</strong>rtificial <strong>G</strong>eneral <strong>I</strong>ntelligence
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<br>
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> **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.
[](https://discord.gg/2xrMh7qX6m)⠀[](https://t.me/+Ka9i6CNwe71hMWQy)
<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](#overview)
- [Features](#features)
- [Architecture](#architecture)
- [Agent Supervision](#advanced-agent-supervision)
- [Quick Start](#quick-start)
- [How to Use PentAGI After Login](#how-to-use-pentagi-after-login)
- [API Access](#api-access)
- [LLM Provider Configuration](#custom-llm-provider-configuration)
- [Ollama](#ollama-provider-configuration)
- [OpenAI](#openai-provider-configuration)
- [Anthropic](#anthropic-provider-configuration)
- [Google AI (Gemini)](#google-ai-gemini-provider-configuration)
- [AWS Bedrock](#aws-bedrock-provider-configuration)
- [DeepSeek](#deepseek-provider-configuration)
- [GLM](#glm-provider-configuration)
- [Kimi](#kimi-provider-configuration)
- [Qwen](#qwen-provider-configuration)
- [Advanced Setup](#advanced-setup)
- [Langfuse Integration](#langfuse-integration)
- [Monitoring and Observability](#monitoring-and-observability)
- [Knowledge Graph (Graphiti)](#knowledge-graph-integration-graphiti)
- [OAuth Integration](#github-and-google-oauth-integration)
- [Docker Image Configuration](#docker-image-configuration)
- [Development](#development)
- [Testing LLM Agents](#testing-llm-agents)
- [Embedding Configuration and Testing](#embedding-configuration-and-testing)
- [Function Testing with ftester](#function-testing-with-ftester)
- [Building](#building)
- [Credits](#credits)
- [License](#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**:
[](https://youtu.be/R70x5Ddzs1o)
## 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.
- Knowledge Graph Integration. Graphiti-powered knowledge graph using Neo4j for semantic relationship tracking and advanced context understanding.
- Web Intelligence. Built-in browser via [scraper](https://hub.docker.com/r/vxcontrol/scraper) for gathering latest information from web sources.
- External Search Systems. Integration with advanced search APIs including [Tavily](https://tavily.com), [Traversaal](https://traversaal.ai), [Perplexity](https://www.perplexity.ai), [DuckDuckGo](https://duckduckgo.com/), [Google Custom Search](https://programmablesearchengine.google.com/), [Sploitus Search](https://sploitus.com) and [Searxng](https://searxng.org) 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](https://hub.docker.com/r/vxcontrol/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](https://platform.openai.com/), [Anthropic](https://www.anthropic.com/), [Google AI/Gemini](https://ai.google.dev/), [AWS Bedrock](https://aws.amazon.com/bedrock/), [Ollama](https://ollama.com/), [DeepSeek](https://www.deepseek.com/en/), [GLM](https://z.ai/), [Kimi](https://platform.moonshot.ai/), [Qwen](https://www.alibabacloud.com/en/), Custom) plus aggregators ([OpenRouter](https://openrouter.ai/), [DeepInfra](https://deepinfra.com/)). For production local deployments, see our [vLLM + Qwen3.5-27B-FP8 guide](examples/guides/vllm-qwen35-27b-fp8.md).
- API Token Authentication. Secure Bearer token system for programmatic access to REST and GraphQL APIs.
- Quick Deployment. Easy setup through [Docker Compose](https://docs.docker.com/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](#custom-llm-provider-configuration) and the [vLLM + Qwen3.5-27B-FP8 guide](examples/guides/vllm-qwen35-27b-fp8.md).
## Architecture
### System Context
```mermaid
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/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>
```mermaid
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 --> |Query| Jaeger
Grafana --> |Query| Loki
API --> |Analytics| Langfuse
Langfuse --> |Store| ClickHouse
Langfuse --> |Cache| Redis
Langfuse --> |Files| MinIO
classDef core fill:#f9f,stroke:#333,stroke-width:2px,color:#000
classDef knowledge fill:#ffa,stroke:#333,stroke-width:2px,color:#000
classDef monitoring fill:#bbf,stroke:#333,stroke-width:2pLo que la gente pregunta sobre pentagi
¿Qué es vxcontrol/pentagi?
+
vxcontrol/pentagi es subagents para el ecosistema de Claude AI. Fully autonomous AI Agents system capable of performing complex penetration testing tasks Tiene 17.7k estrellas en GitHub y se actualizó por última vez yesterday.
¿Cómo se instala pentagi?
+
Puedes instalar pentagi clonando el repositorio (https://github.com/vxcontrol/pentagi) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.
¿Es seguro usar vxcontrol/pentagi?
+
Nuestro agente de seguridad ha analizado vxcontrol/pentagi y le ha asignado un Trust Score de 100/100 (tier: Verified). Revisa el desglose completo de comprobaciones superadas y flags en esta página.
¿Quién mantiene vxcontrol/pentagi?
+
vxcontrol/pentagi es mantenido por vxcontrol. La última actividad registrada en GitHub es de yesterday, con 48 issues abiertos.
¿Hay alternativas a pentagi?
+
Sí. En ClaudeWave puedes explorar subagents similares en /categories/agents, ordenados por popularidad o actividad reciente.
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[](https://claudewave.com/repo/vxcontrol-pentagi)<a href="https://claudewave.com/repo/vxcontrol-pentagi"><img src="https://claudewave.com/api/badge/vxcontrol-pentagi" alt="Featured on ClaudeWave: vxcontrol/pentagi" width="320" height="64" /></a>Más Subagents
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