The article reviews two recent posts on AI‑assisted security testing, explains how Skills can limit large‑model performance, argues that MCP provides richer tooling, and shares a practical Burp MCP workflow with code snippets for traffic analysis in vulnerability research.
Shannon, an autonomous AI-driven penetration testing agent, bridges the speed‑security gap created by rapid AI‑assisted coding by automatically analyzing source code, mapping attack paths, and executing real exploits, achieving a 96.15% success rate on the XBOW benchmark and uncovering over 20 critical flaws in the OWASP Juice Shop demo.
The paper introduces LEGO, a sequence‑oriented DBMS fuzzing framework that leverages type‑affinity analysis to generate rich SQL statement sequences, achieving 44%‑198% higher coverage and uncovering numerous new vulnerabilities across MySQL, PostgreSQL, MariaDB, and Comdb2, as demonstrated at ICDE 2023.
The article details a step‑by‑step penetration test of a seemingly empty financial web application, describing how hidden JavaScript files and a discovered /xxxapi/file/pdf/view endpoint were leveraged to craft an SSRF payload that accessed internal services such as Elasticsearch, illustrating practical web security exploitation techniques.
