Shannon: AI-Powered Application Security
Agentic static analysis combined with autonomous pentesting. Zero configuration. Real exploits, near-zero false positives.
Scan your code. Exploit the findings.
Shannon operates as a two-stage pipeline: agentic static analysis of the codebase, followed by autonomous dynamic penetration testing against the running application. Findings from both stages are correlated to produce a unified, high-confidence result set with reproducible proof-of-concept exploits for every finding.
Stage 1: Agentic Static Analysis
Comprehensive code-level security assessment using LLM-powered agents across five core capabilities.
Data Flow Analysis
Your codebase is transformed into a Code Property Graph (CPG) — a unified representation of AST, control flow, and data flow — then analyzed in three phases. First, sources (user inputs, API parameters, file reads, environment variables) and sinks (SQL queries, shell commands, file writes, response outputs) are extracted using deterministic patterns plus AI-discovered custom input handlers unique to your framework. Then we trace backward from each sink toward potential sources, with an LLM evaluating at each node whether the specific sanitization actually addresses the specific risk — not just "is there a sanitizer," but "does this particular encoding prevent this particular injection in this context." Finally, an autonomous agent validates each candidate path for control flow correctness (can this branch actually execute?) and logic correctness (do the types and constraints line up?), producing confidence scores. Only validated, high-confidence paths make the final report, which means near-zero false positives on taint-style vulnerabilities like SQL injection, XSS, SSRF, path traversal, and command injection.
Stage 2: Autonomous Dynamic Penetration Testing
Shannon implements this methodology with 13 specialized agents across 5 phases. Phases 1, 2, and 5 are sequential. Phases 3 and 4 run as pipelined parallel: each vuln/exploit pair is independent.
Phase 1: Pre-Reconnaissance
Static analysis maps the entire codebase, entry points, auth systems, database patterns, and security sinks, without ever touching a browser. This architectural blueprint tells downstream agents exactly where to focus and what to skip.
Phase 2: Reconnaissance
Browser automation validates code findings against the live application, confirming real endpoints, auth flows, and input vectors. Infrastructure discovery tools like Nmap and Subfinder extend coverage to the network perimeter.
Phase 3: Vulnerability Analysis
Five parallel agents (Injection, XSS, SSRF, Auth, and Authz) each combine code analysis with runtime probing to build structured exploitation queues. If an agent finds nothing in its domain, the corresponding exploit agent is skipped entirely, saving time and cost.
Phase 4: Exploitation
Exploit agents consume each queue and attempt real attacks via Playwright browser automation, classifying every finding as EXPLOITED, POTENTIAL, or FALSE POSITIVE.
Phase 5: Reporting
A reporting agent synthesizes confirmed evidence into a pentest-grade executive report with severity ratings, remediation guidance, and reproducible steps. Raw hypotheses and potential findings are programmatically stripped, only verified exploits reach the deliverable.
True black box pentesting.
We never see your code.
Point Shannon at a URL and let it attack. Our agents autonomously navigate your application using a real browser and terminal, just like a human pentester would. Test as often as you like. No source code access, ever.
Context configuration
All fields optional. Leave blank for pure black box, or fill in for gray box.
Up to 4 login credentials. Supports Google OAuth, GitHub, and custom auth. Multiple credentials enable privilege escalation and IDOR testing across different roles and organizations.
Direct testing toward specific areas: your auth flow, a particular feature, a sub-service, or endpoints you're nervous about. "I built this quickly and I'm not sure how secure it is."
For a gray box feel, describe business logic invariants, assumptions your app makes, legacy infrastructure details, or tech stack info to help target more accurate business logic testing.
Exclude specific features, flows, or sub-services from testing. Useful for protecting production data, skipping known-good areas, or avoiding destructive operations.
For the most thorough coverage, provide an OpenAPI specification. Gives the agent complete documentation of your endpoints for comprehensive analysis.
Test against localhost dev setups via ngrok, or target staging and sandbox URLs after verifying domain ownership through DNS TXT record confirmation.
Get started with Shannon
Open Source
The autonomous AI pentest framework. Run it yourself, extend it however you want.
Shannon Pentest
Dynamic-only testing from an external attacker perspective. No source code required. Test as often as you like.
Shannon Cloud
Full SAST + DAST platform hosted by Keygraph. Start scanning in minutes. Unlimited runs.
Shannon Enterprise
Self-hosted deployment. Your code never leaves your infrastructure. Unlimited runs.