Shannon is an open-source, fully autonomous AI pentester for web applications and APIs developed by Keygraph. It analyzes source code, identifies attack vectors, and executes real exploits without human intervention. Powered by Anthropic's Claude models, Shannon achieves a 96.15% success rate on the hint-free, source-aware XBOW Benchmark, making it one of the most effective automated security testing tools available. The tool operates through a multi-stage pipeline: a reconnaissance phase identifies application endpoints, vulnerability analysis agents examine code patterns across five attack domains (injection, XSS, SSRF, authentication, and authorization), parallel exploitation agents attempt proof-of-concept attacks against the running application, and a final report is generated containing only validated findings with working exploits. Shannon integrates security staples including Nmap for port scanning, Subfinder for subdomain enumeration, WhatWeb for tech fingerprinting, and Schemathesis for API fuzzing. It supports 2FA/TOTP authentication handling, SSO login, and workspace functionality that enables interrupted runs to resume without re-execution. The project offers a Lite edition under AGPL-3.0 and a commercial Pro edition for enterprise use.