PentAGI

Categories: Cybersecurity, Automation / Agents, Coding & Developer Tools | Pricing: Freemium | Official Website ↗

PentAGI provides autonomous AI agents for penetration testing, planning work, running tools in a sandbox, and reporting findings.

PentAGI is an open-source, self-hosted platform that uses autonomous AI agents to perform penetration tests. Users describe a target and a goal in plain language, and PentAGI's specialized agents plan the test, research, exploit vulnerabilities, and generate reports. It integrates with over 20 professional tools like nmap, Metasploit, and sqlmap, running them in isolated Docker containers. The platform supports various large language models (LLMs) including OpenAI, Anthropic, Google Gemini, AWS Bedrock, and local models, or any OpenAI-compatible endpoint. It also searches the web and exploit databases using multiple search engines. PentAGI provides a detailed view of the agents' progress, commands, and results, maintaining a long-term memory and knowledge base for continuous learning and improved performance across flows. PentAGI includes safeguards to prevent agents from looping indefinitely, such as turn limits, repeat detection, and a reflector mechanism to steer models back to tool usage. All terminal commands and file operations are executed within the flow's isolated container, enhancing security. The platform offers both an open-source edition for researchers and security teams and an Enterprise edition with additional features like customer-ready report templates and commercial support.

Key Features

Autonomous AI agents for penetration testing
Isolated sandbox for tool execution (Docker)
Support for various LLMs (cloud and local)
Web and exploit database search
Long-term memory and knowledge base
Interactive assistant
Flow reports (Markdown, PDF, DOCX for Enterprise)
Execution monitoring and task planning

Pros

Automates end-to-end penetration testing processes.
Self-hosted, allowing full control over data and infrastructure.
Open-source edition provides full agent stack for free.
Supports a wide range of LLM providers, including local models.
Tools run in isolated containers, enhancing security.
Includes safeguards to prevent infinite loops and token waste.

Cons

Requires Docker, Docker Compose, and specific hardware resources to run.
Requires access to at least one LLM provider.
Commercial license and advanced features are only in the Enterprise edition.
Community support only for the open-source edition.
Not for unauthorized security testing; requires explicit authorization.

Use Cases

Automated vulnerability discovery
Continuous security testing
Security research and development
Red team operations
Compliance auditing

Best For

Security researchers
Security teams
Penetration testers
In-house red teams
Security consultancies

Integrations: OpenAI, Anthropic, Google Gemini, AWS Bedrock, Ollama, DeepSeek, Mistral, xAI, Qwen, Kimi

Platforms: Web, Linux, macOS, Windows, Docker

Watch demo on YouTube ↗

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