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Shannon: Automated AI Attacker Achieves 96.15% Success Rate in Web Application Vulnerability Discovery

Shannon, an automated AI attacker developed by KeygraphHQ, has demonstrated a 96.15% success rate in discovering real vulnerabilities within web applications. This achievement was recorded in prompt-less, source-aware XBOW benchmark testing. The project, available on GitHub Trending, is currently under active development, indicating ongoing enhancements and features for this AI-driven security tool.

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Shannon, an innovative automated AI attacker, has been developed to identify actual vulnerabilities within web applications. The tool, created by KeygraphHQ, has achieved a remarkable 96.15% success rate in prompt-less, source-aware XBOW benchmark testing. This high success rate highlights its effectiveness in autonomously discovering security flaws. The project is currently in active development, as noted on its GitHub repository, suggesting continuous improvements and new functionalities are being integrated. Shannon is listed on GitHub Trending, indicating its growing recognition and interest within the developer and cybersecurity communities.

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