Shannon

Overview

Shannon is a fully autonomous AI penetration tester designed to find and exploit actual vulnerabilities in web applications before attackers do. Built by Keygraph, Shannon performs code-aware dynamic testing: it requires source code access to guide its attack strategy, then executes real exploits on running applications to deliver proof-of-concept rather than just security alerts.

Unlike traditional vulnerability scanners that generate long lists of potential issues, Shannon operates like a human pentester: it analyzes your code, leverages reconnaissance tools to identify attack vectors, executes real browser-based exploits, and delivers reproducible proof-of-concepts. Keygraph reports a 96.15% success rate on their hint-free, source-aware XBOW benchmark variant.

Shannon addresses a critical security gap in modern development. While teams ship code daily using tools like Claude Code and Cursor, penetration tests typically happen once a year. Shannon closes this gap by providing on-demand, automated pentesting for every build, branch, or deployment.

Key Features

• Fully Autonomous Operation — Launch pentests with a single command. Shannon handles everything from advanced 2FA/TOTP logins to the final report with zero manual intervention, saving hours of security analyst time. This AI agent approach eliminates the need for constant human oversight.

• Real Exploit Validation — Executes actual browser-based attacks including injection, XSS, SSRF, and authentication bypass to prove vulnerabilities are exploitable, significantly reducing false positives compared to traditional scanners.

• Code-Aware Dynamic Testing — Analyzes source code to guide attack strategy, then performs live exploits on running applications to confirm real-world risk with context-aware precision. This makes it a specialized AI code checker focused on security vulnerabilities.

• Pentester-Grade Reports — Delivers actionable reports focused on proven findings with copy-and-paste Proof-of-Concepts, enabling developers to reproduce and fix issues immediately.

• Parallel Processing Architecture — Runs analysis and exploitation for all vulnerability types concurrently, completing comprehensive pentests in 1-1.5 hours instead of days.

• Integrated Security Tools — Enhances discovery with industry-standard tools including Nmap, Subfinder, WhatWeb, and Schemathesis for deep environment analysis.

Pricing & Plans

Shannon Lite is completely free and open-source under the AGPL-3.0 license. Shannon Pro is a commercial version for enterprise needs.

Shannon Lite (Free)

• Full autonomous pentesting capabilities
• No subscription fees or usage limits
• Requires authorization for all tested systems
• Complete access to source code
• Community support via GitHub and Discord
• Targets critical OWASP vulnerabilities: Injection, XSS, SSRF, Broken Auth/Authorization

Shannon Pro (Commercial)

• Advanced LLM-powered data flow analysis engine
• Deeper vulnerability detection across entire codebase
• CI/CD pipeline integration (specific integration methods require confirmation with sales)
• Enterprise features and dedicated support
• Contact sales for pricing and feature details

Operating Costs
While Shannon itself is free, running tests requires AI API access. Using Anthropic's Claude Sonnet 4.5 costs approximately $50 per full test run (token-based estimate). Costs vary based on application complexity and model pricing.

Pros & Cons

Pros:

• Shannon Lite is completely free and open-source
• High accuracy (96.15% on hint-free, source-aware XBOW variant)
• Significantly reduces false positives through exploit validation (human review still recommended)
• Delivers actionable, reproducible proof-of-concepts
• Saves significant time compared to manual penetration testing
• Integrates seamlessly with development workflows

Cons:

• Requires white-box access (source code must be available)
• Relatively long test duration (1-1.5 hours per full run)
• API costs approximately $50 per test using Claude Sonnet 4.5 (token-based estimate)
• Limited to specific OWASP categories (Injection, XSS, SSRF, Auth issues)
• May cause mutative effects on test environments
• Not suitable for production environment testing

Best For

Shannon is ideal for:

• Security teams conducting continuous application security testing on every code commit
• DevSecOps engineers integrating automated pentesting into CI/CD pipelines
• Development teams using AI code generators who need rapid vulnerability validation
• Independent security researchers testing white-box web applications
• Startups and SMBs requiring professional-grade pentesting without expensive consultant fees
• Organizations with rapid release cycles (daily/weekly deployments) needing security validation at scale

FAQ