Shannon: Autonomous AI Tool with Nmap Integration Can Uncover and Exploit Security Flaws

Keygraph has released Shannon, a fully autonomous AI-powered penetration testing tool designed to identify and actively exploit real vulnerabilities in web applications before malicious actors can.

Unlike traditional scanners that generate alerts, Shannon delivers proven, reproducible exploits, closing the dangerous security gap that exists between annual pentests and continuous code deployments.

How Shannon Works

Shannon emulates a human red team operator using a four-phase multi-agent pipeline powered by Anthropic’s Claude Agent SDK.

It combines white-box source code analysis with black-box dynamic exploitation, giving it both deep code context and real-world attack validation.

The four phases operate as follows:

• Reconnaissance – Maps the full attack surface by analyzing source code and using integrated tools like Nmap, Subfinder, WhatWeb, and Schemathesis to enumerate endpoints, API routes, and authentication mechanisms​
• Vulnerability Analysis – Parallel specialized agents trace user input through data flows to identify exploitable paths across OWASP categories including Injection, XSS, SSRF, and Broken Authentication​
• Exploitation – Dedicated exploit agents attempt real-world attacks via browser automation and CLI tools; any hypothesis that cannot be actively exploited is discarded as a false positive​
• Reporting – Consolidates only verified findings into a professional report with copy-paste Proof-of-Concept exploits, eliminating noise and hallucinated artifacts

Shannon achieved a 96.15% success rate on the hint-free, source-aware XBOW Benchmark.

In testing against OWASP Juice Shop, it discovered 20+ critical vulnerabilities including full authentication bypass and complete database exfiltration in a single automated run.

Key Features

Feature	Details
Fully Autonomous Operation	Single command launch; handles 2FA/TOTP, browser navigation, and reporting
Nmap & Tool Integration	Leverages Nmap, Subfinder, WhatWeb, Schemathesis for deep recon
OWASP Vulnerability Coverage	Injection, XSS, SSRF, Broken Auth/Authorization
Code-Aware Dynamic Testing	White-box code analysis guides black-box live exploit execution
Parallel Processing	Concurrent agents for all vulnerability types reduce total run time
Pentester-Grade Reports	Reproducible PoC exploits; zero unverified findings included
Workspace & Resume Support	Checkpointed via git commits; resumes from last completed agent
Editions	Shannon Lite (AGPL-3.0) and Shannon Pro (Commercial/Enterprise)

Setup & Quick Start

Step	Command / Action
1. Prerequisites	Install Docker; obtain Anthropic API key from Anthropic Console
2. Clone Repository	git clone https://github.com/KeygraphHQ/shannon.git && cd shannon
3. Set Credentials	export ANTHROPIC_API_KEY="your-api-key" or create a .env file
4. Add Target Repo	Clone target app into ./repos/your-repo
5. Run Pentest	./shannon start URL=https://your-app.com REPO=your-repo
6. Monitor Progress	./shannon logs or open Temporal Web UI at http://localhost:8233
7. Stop / Cleanup	./shannon stop (preserve data) or ./shannon stop CLEAN=true
Local App Testing	Replace localhost with host.docker.internal in the URL

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A full test run typically takes 1 to 1.5 hours and may cost approximately $50 USD using Claude Sonnet, depending on application complexity.

Shannon is strictly designed for sandboxed, staging, or development environments; running it against production systems or unauthorised targets violates its ethical use policy and applicable laws such as the CFAA.

Shannon Pro extends the open-source foundation with an LLM-powered data flow analysis engine, CI/CD integration, and enterprise support for organizations requiring deeper coverage across large codebases.

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