Autonomous penetration testing is addressed by Pentest-Swarm-AI, a Go-native platform that orchestrates a swarm of specialist AI agents for full-cycle security assessments. It targets security engineers, bug bounty hunters, and CTF participants, offering an automated, efficient, and adaptive approach to identifying and exploiting vulnerabilities.

How It Works

The project employs a coordinated swarm of purpose-built AI agents (Recon, Classification, Exploitation, Reporting) managed by a Swarm Orchestrator. This orchestrator utilizes a ReAct (Reason, Act, Observe, Adapt) loop for real-time planning and adaptation. Specialist agents leverage native Go security tools, enabling parallel execution and efficient, automated penetration testing from initial reconnaissance to final report generation.

Quick Start & Requirements

Installation is supported via Homebrew (brew install armur-ai/tap/pentestswarm), a script (curl -sSL https://install.pentestswarm.ai | sh), Docker (docker compose -f deploy/docker-compose.yml up), or Go (go install github.com/Armur-Ai/Pentest-Swarm-AI/cmd/pentestswarm@latest). The sole configuration requirement is setting the Claude API key (export PENTESTSWARM_ORCHESTRATOR_API_KEY=sk-ant-your-key-here). Notably, no GPU, Ollama, or model downloads are necessary for the default setup.

Highlighted Details

• Features a 5-agent architecture: Orchestrator plus four specialist agents.
• Integrates 7 native Go security tools (subfinder, httpx, nuclei, naabu, katana, dnsx, gau) to minimize subprocess overhead.
• Employs ReAct orchestration for dynamic, adaptive attack planning.
• Supports multiple modes: manual (full autonomous), bugbounty (H1/Bugcrowd scope integration), asm (continuous monitoring), and ctf (automated machine solving).
• Offers extensive integrations, including MCP Server (for Claude Desktop/Cursor), VS Code Extension, GitHub Actions, Jira, Slack, SIEM (CEF, STIX 2.1, SARIF), and Webhooks.
• Provides a Next.js 15 dashboard with live visualizations and a multi-panel Terminal TUI for monitoring agent activity.
• Supports multiple LLM providers: Claude API (default), Ollama, and LM Studio for local execution.

Maintenance & Community

The project features "Community Playbooks" for shared attack chains and an opt-in "Shared Intelligence" network for collective learning across installations. Development is by Armur AI. Specific details regarding active contributors, sponsorships, or dedicated community channels like Discord or Slack are not provided in the README.

Licensing & Compatibility

The project is licensed under the Apache 2.0 license, which generally permits commercial use and integration into closed-source projects. No specific compatibility restrictions for commercial use or linking are mentioned.

Limitations & Caveats

The default and highest-quality experience relies on the paid Claude API; local LLM providers are supported but require additional setup. While designed for autonomy, the tool's effectiveness and safety are contingent on accurate scope definition and user understanding of its capabilities and potential risks.