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Most security scanners find problems. Shannon exploits them.

That’s the core difference. Keygraph’s Shannon doesn’t just flag a potential SQL injection and hand you a report full of maybes. It reads your source code, maps the attack surface, then fires real payloads — injection attacks, auth bypass, SSRF, XSS — against your running application. If it can’t actually break in, it doesn’t report it. Zero false positives by design.

35.3K GitHub stars. Trending #7. The AppSec community is paying attention.

What Shannon Actually Does

Shannon is a white-box AI pentester. “White-box” means it gets full access to your source code before attacking — the same access an insider or a serious attacker with a leaked repo would have. Powered by Anthropic’s Claude, it performs static analysis first to understand your codebase, identifies the juiciest attack vectors, then uses browser automation and CLI tools to execute real exploits against your live app.

The result: a proof-of-concept for every vulnerability it finds. Not a warning. Not a “might be vulnerable.” A working exploit.

On the XBOW benchmark — 104 intentionally vulnerable apps designed to test AI security agents — Shannon scored 96.15% in hint-free mode. That’s 100 out of 104 successful exploits. For comparison, most commercial DAST tools struggle to hit 30-40% on similar evaluations.

Why Traditional Tools Can’t Compete

Traditional SAST tools check code against hard-coded rules. They’ll catch eval(user_input) but miss a complex business logic flaw where three legitimate API calls chained together bypass authorization. Shannon reasons about what code actually does, not what patterns it matches.

The “No Exploit, No Report” policy solves the biggest headache in AppSec: alert fatigue. Security teams drowning in thousands of unvalidated findings from Snyk or SonarQube now have an alternative that only surfaces what’s actually exploitable.

A full scan of a medium-complexity app runs about $40-55 in Claude API credits. Takes roughly an hour.

The Open-Source vs Pro Split

Shannon Lite is AGPL-3.0 — fully open-source, covers the autonomous pentesting core. Shannon Pro bundles SAST, SCA, secrets scanning, and business logic testing into one correlated platform, replacing the typical five-tool security stack.

Security researchers on Medium are already publishing real-world test results. The conversation in AppSec has shifted from “can AI do pentesting” to “how fast will this replace manual assessments.”

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