Shannon: Fully Automated AI Hacker Achieves 96.15% Success Rate in Web Application Vulnerability Detection
Shannon, an innovative fully automated AI hacker developed by KeygraphHQ, has demonstrated remarkable capabilities in identifying real-world vulnerabilities within web applications. The AI achieved an impressive 96.15% success rate in the prompt-less, source-aware XBOW benchmark, highlighting its effectiveness and potential for enhancing web security. This tool operates autonomously, streamlining the process of vulnerability detection.
Shannon, a cutting-edge fully automated AI hacker, has been introduced by KeygraphHQ, designed to autonomously identify genuine vulnerabilities within web applications. This AI system has showcased significant performance, achieving a 96.15% success rate in the XBOW benchmark. Notably, this success was recorded in a prompt-less and source-aware testing environment, indicating Shannon's advanced ability to operate without explicit instructions and with an understanding of the underlying source code. The development of Shannon aims to provide an efficient and automated solution for detecting security flaws in web applications, potentially revolutionizing how vulnerabilities are discovered and addressed.