PentAGI: AI-Powered Penetration Testing Tool Integrates 20+ Security Tools for Automated Assessments
PentAGI automates penetration testing with AI agents. It integrates over 20 security tools like Nmap and Metasploit. The open-source tool runs fully autonomous scans in Docker sandboxes. Users get detailed reports with exploit proofs.
VXControl developed PentAGI. They released it on GitHub in early 2025. Security teams use it to find vulnerabilities fast. No manual scripting needed. The multi-agent system plans attacks dynamically. It recalls past tests via long-term memory.
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PentAGI uses top LLMs for smarts. Models include OpenAI, Anthropic Claude, Google Gemini, and local Ollama. External search APIs like Tavily and Perplexity fetch real-time data. A built-in scraper pulls target info safely.
Reports save in PostgreSQL with pgvector. Users query them semantically. Grafana dashboards track agent performance. Chain summarization keeps LLM context tight. This handles long pentests without overflow.
Key features :
- Autonomous multi-agent pentesting.
- 20+ tool integrations.
- Docker isolation for safety.
- Persistent memory and reporting.
Core Architecture
PentAGI builds on microservices.
- Frontend: React/TypeScript.
- Backend: Go with REST/GraphQL.
- Database: PostgreSQL + Neo4j for knowledge graphs.
- Monitoring: OpenTelemetry, Jaeger, Loki.
Deployment uses Docker Compose. Clone repo, set .env keys, run one command. Access at localhost:8443.
Integrated Security Tools
| Tool | Purpose | Usage in PentAGI |
|---|---|---|
| Nmap | Network discovery | Port scanning, service enum |
| Metasploit | Exploitation | Payload delivery, modules |
| sqlmap | Database attacks | SQL injection testing |
| Nuclei | Vulnerability scanning | Template-based checks |
| Burp Suite | Web app proxy/testing | Traffic interception |
Over 20 tools chain automatically. Agents pick based on target.
Key Configuration Parameters
| Parameter | Environment Variable | Default | Description |
|---|---|---|---|
| Preserve Last | SUMMARIZER_PRESERVE_LAST | true | Keep recent messages intact |
| Last Section Size | SUMMARIZER_LAST_SEC_BYTES | 51200 | Max bytes for last section (50KB) |
| Max QA Size | SUMMARIZER_MAX_QA_BYTES | 65536 | Max bytes for QA pairs (64KB) |
Assistant settings boost context to 75KB for complex chains.
Agent Roles and Workflow
- Researcher: Gathers intel, plans strategy.
- Developer: Crafts exploits, scripts tools.
- Executor: Runs scans, verifies findings.
Workflow: Define target. Agents collaborate. Generate PoC exploits. Output reports with steps.
Security features isolate networks. TLS secures traffic. Proxy support for air-gapped setups.
Deployment Steps
- Clone:Â
git clone https://github.com/vxcontrol/pentagi - CopyÂ
.env.example toÂ.env. Add API keys. - Run:Â
docker compose up -d - Open:Â https://localhost:8443
Scale with worker nodes. Add OAuth for teams.
Why PentAGI Stands Out
Manual pentests take days. PentAGI cuts to hours. Self-hosted control beats SaaS costs. LLM flexibility fits budgets. Knowledge graphs link vulns smartly.
Teams manage LLM rate limits. AWS Bedrock or local models work. 2026 sees it top open-source lists.
Red teams adopt for speed. Blue teams use for validation. Developers test apps early.
FAQ
AI-driven pentesting tool with 20+ integrations for autonomous
OpenAI, Claude, Gemini, Ollama for cloud or local use.
All tests run in Docker sandboxes. No host impact.
PostgreSQL with pgvector. Neo4j for graphs.
Yes, open-source on GitHub. LLM APIs may cost extra.
Supports scaling, OAuth, monitoring stacks like Jaeger.
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