Search Results for "attack surface management"

...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.

Shannon is an autonomous AI penetration testing system built to find and prove real, exploitable vulnerabilities in web applications rather than stopping at static warnings or best-guess alerts. It focuses on “proof by exploitation,” meaning it actively hunts for attack vectors in your code and then attempts to execute end-to-end exploits to demonstrate impact. The project blends source-aware analysis with automated web interaction so it can validate issues like injection flaws,...