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RedAmon is an AI-powered red team framework designed to automate offensive cybersecurity operations from reconnaissance to exploitation and post-exploitation. It combines artificial intelligence with traditional penetration testing tools to create a fully autonomous pipeline capable of discovering vulnerabilities and executing security assessments without human intervention. It begins with a multi-phase reconnaissance engine that maps the entire attack surface of a target, collecting information such as subdomains, open ports, services, and potential vulnerabilities. RedAmon then uses an AI agent orchestrator to analyze this data, select appropriate tools, and perform exploitation steps such as credential brute forcing or CVE-based attacks. All discovered assets, relationships, and vulnerabilities are stored in a Neo4j knowledge graph, allowing the system to reason about the environment and make informed decisions during the attack process.
Features
- Autonomous AI agent that conducts reconnaissance, exploitation, and post-exploitation
- Six-phase reconnaissance pipeline for mapping a target’s attack surface
- Neo4j knowledge graph that stores assets, vulnerabilities, and relationships
- Integration with security tools through the Model Context Protocol
- Automated vulnerability detection, credential brute forcing, and CVE exploitation
- Containerized architecture using Docker for isolated tool execution
Project Samples
