> [!NOTE]
> **[Shannon 2.0 is officially here](https://github.com/KeygraphHQ/shannon/discussions/405)**

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### Shannon is an autonomous, AI pentester for web applications and APIs. 

It analyzes your source code, identifies attack paths, and executes real exploits to prove vulnerabilities before they reach production.

**This repository is Shannon Open Source: the full agent, run locally from your command line.**

---

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> [!TIP]
> **AI agents and LLMs:** start with [llms.txt](llms.txt) for a concise map of this repository, or use [llms-full.txt](llms-full.txt) for the README and docs combined into one file.

## Table of Contents

- [What is Shannon?](#what-is-shannon)
- [Shannon in Action](#shannon-in-action)
- [Quick Start](#quick-start)
- [Key Capabilities](#key-capabilities)
- [Editions](#editions)
- [Architecture](#architecture)
- [Documentation](#documentation)
- [Safety, Scope, and Limitations](#safety-scope-and-limitations)
- [License](#license)
- [About Keygraph](#about-keygraph)
- [Community and Support](#community-and-support)
- [Common Questions](#common-questions)

## What is Shannon?

Shannon is an autonomous AI pentester developed by [Keygraph](https://keygraph.io). It performs security testing of web applications and their underlying APIs by combining source-code analysis with live exploitation.

Shannon analyzes your web application's source code to identify potential attack vectors, then uses browser automation and command-line tools to execute real exploits against the running application and its APIs. Only vulnerabilities with a working proof-of-concept are included in the final report.

Shannon is the agent. This repository is Shannon Open Source, the standalone pentester you run yourself. The same Shannon also powers the [Keygraph platform](https://keygraph.io), Keygraph's commercial pentesting product. See [Editions](#editions) for how the two compare.

### Why Shannon Exists

Thanks to tools like Claude Code and Cursor, your team ships code non-stop. But your penetration test? That happens once a year. This creates a massive security gap. For the other 364 days, you could be unknowingly shipping vulnerabilities to production.

Shannon closes that gap by providing on-demand, automated penetration testing that can run against every build or release.

## Shannon in Action

<p align="center">
  <img src="assets/shannon-action.gif" alt="Shannon running an autonomous pentest" width="100%">
</p>

Sample penetration test reports from intentionally vulnerable applications, produced by Shannon Open Source:

| Target | Summary | Report |
| --- | --- | --- |
| OWASP Juice Shop | 20+ vulnerabilities, including authentication bypass, SQL injection, IDOR, and SSRF. | [View report](sample-reports/shannon-report-juice-shop.md) |
| c{api}tal API | Approximately 15 critical and high-severity API findings, including command injection, auth bypass, and mass assignment. | [View report](sample-reports/shannon-report-capital-api.md) |
| OWASP crAPI | 15+ critical and high-severity findings across JWT, injection, SSRF, and API authorization paths. | [View report](sample-reports/shannon-report-crapi.md) |

## Quick Start

### Prerequisites

- **Docker**: required for the worker container.
- **Node.js 18+**: required for the recommended `npx` workflow.
- **AI provider credentials**: Shannon runs on Anthropic, OpenAI, xAI, AWS Bedrock, [any other provider](docs/ai-providers.md#any-other-provider) in the harness catalogue, and any endpoint that speaks the Anthropic Messages API or the OpenAI Chat Completions or Responses API through a [custom base URL](docs/ai-providers.md#custom-base-url). You bring your own key, and Keygraph never proxies your model traffic. Shannon is provider-agnostic. See [AI providers](docs/ai-providers.md#suggested-models) for suggested model IDs.
- **Cyber safeguards cleared with your provider**: Anthropic and OpenAI apply real-time safeguards to cyber-security workloads, which can interrupt a scan mid-run. Complete their guidance for legitimate security testers before your first run - see [AI providers](docs/ai-providers.md#cyber-safeguards-do-this-before-your-first-scan).

### Run Shannon

> [!WARNING]
> Shannon actively executes exploits. Run it only against applications and environments you own or have explicit written authorization to test. Do not run Shannon against production systems.

```bash
# Configure credentials with the interactive wizard.
npx @keygraph/shannon setup

# Run a pentest against a source-available target.
npx @keygraph/shannon start -u https://your-app.com -r /path/to/your-repo
```

Shannon pulls the worker image from Docker Hub, starts the required local infrastructure, mounts the target repository read-only inside an ephemeral worker container, and writes results to a local workspace.

For source builds, authenticated scans, provider-specific setup, and platform notes, see [Documentation](#documentation).

> [!TIP]
> **Prefer to use a subscription instead of API credits?**
>
> - **OpenAI Codex:** The latest version of Shannon supports ChatGPT Plus and Pro subscriptions. Follow the [OpenAI Codex subscription setup guide](docs/ai-providers.md#openai-codex-chatgpt-pluspro-subscription) to get started.
> - **xAI (Grok):** The latest version of Shannon supports xAI subscriptions. Follow the [xAI subscription setup guide](docs/ai-providers.md#xai-grok-subscription) to get started.
> - **Claude Code:** The latest version of Shannon does not support Claude Code subscriptions. Follow the [Claude Code subscription setup guide](docs/ai-providers.md#claude-code-subscription) to use version `1.9.0`, which is the final release built on the Claude Agent SDK.

## Key Capabilities

- **Proof-by-exploitation reports**: Shannon reports validated findings with reproducible proof-of-concept steps instead of speculative warnings.
- **White-box attack planning**: Shannon uses source-code analysis to guide dynamic testing and focus on realistic attack paths.
- **Autonomous execution**: Shannon launches reconnaissance, vulnerability analysis, exploitation, and report generation from a single command.
- **Authenticated testing**: configuration files can describe login flows, test credentials, TOTP, email-based login flows, focus areas, and rules of engagement.
- **OWASP-focused coverage**: Shannon targets exploitable Injection, XSS, SSRF, Broken Authentication, and Broken Authorization issues.
- **Resumable workspaces**: Shannon can resume interrupted runs without re-running completed agents.
- **Machine-readable output**: Shannon emits findings as structured JSON, and as SARIF 2.1.0 by default on exploit-mode scans (opt out with `report.sarif: "false"`). SARIF is the OASIS standard for static analysis results, so findings flow into any code scanning service, vulnerability management platform, security dashboard, or CI/CD pipeline that reads it.
- **Bring your own key, provider-agnostic**: Shannon runs on Anthropic, OpenAI, xAI, AWS Bedrock, and any endpoint speaking the Anthropic Messages API or the OpenAI Chat Completions or Responses API, including self-hosted models served through Ollama, vLLM, or LM Studio and gateways such as OpenRouter and LiteLLM. You supply the credentials, so source code and model traffic stay inside your infrastructure. Local and self-hosted models are technically supported but not recommended: they may not follow Shannon's instructions or tool-use constraints as reliably as frontier models, so take that path only if you know how your chosen model behaves.

## Editions

Shannon ships in two ways: **Shannon Open Source**, the pentester you run yourself, and the **Keygraph platform**, the commercial pentesting product that runs Shannon continuously and closes the full AppSec lifecycle around it.

**Shannon Open Source** (this repository) is the standalone pentester: a CLI agent for white-box, proof-by-exploitation testing of web applications and APIs you own or are authorized to test. It reads your source, plans attacks, executes real exploits, and reports only what it can prove. It runs on demand and is complete in that lane. You point it at a target, it pentests, it reports.

The **Keygraph platform** is the enterprise-ready, continuous pentesting product powered by Shannon. In the Keygraph platform, an enhanced build of Shannon runs continuously in a hardened, orchestrated environment fed by Keygraph's full code-analysis stack. Around that engine, the platform closes the entire vulnerability lifecycle, from analysis to a verified fix:

- **Analyze**: Code Property Graph SAST, SCA with reachability, secrets, IaC, and container scanning. First-class detection in their own right, and context that sharpens Shannon's attacks.
- **Prove**: autonomous black-box and source-aware white-box pentests turn candidate findings into proven, exploited vulnerabilities rather than speculative alerts.
- **Manage**: one canonical record per vulnerability per repository, deduplicated across every source, with ownership, status, SLA tracking, dashboards, and bidirectional Jira sync.
- **Remediate and verify**: patches written automatically and re-tested against the patched code before delivery, landing in your existing review workflow rather than auto-applied.
- **Deploy**: self-hosted and air-gapped environments, strict bring-your-own-key model access, and customer-controlled LLM gateway patterns, so source, results, and model traffic stay inside your perimeter.

Shannon is the proof engine at the center of the Keygraph platform. Shannon Open Source gives you that engine to run yourself. The Keygraph platform surrounds Shannon with continuous analysis, finding management, remediation, verification, and enterprise deployment.

| AppSec lifecycle stage | Shannon Open Source | Keygraph platform |
| --- | --- | --- |
| Analyze | Basic LLM pass-through of source to plan attacks | Actual code-base parsing, plus Code Property Graph, SAST, SCA with reachability, secrets, IaC, and containers |
| Pentest and prove | White-box only, proof by exploitation | Enhanced white-box, plus black-box and grey-box modes, run continuously |
| Manage findings | Local Markdown report | Canonical findings system: deduplication across sources, ownership, SLA, dashboards, Jira sync, and professional pentest-grade PDF reports |
| Remediate and verify | Fix manually from the report, then re-run the full scan to verify | Automated remediation: opens a PR with the fix, verified by point re-test without re-running the full scan |
| Deploy and operate | Local CLI and Docker worker | Self-hosted, air-gapped, BYOK, continuous, enterprise integrations |
| License and support | AGPL-3.0, community | Commercial, supported |

Learn more on the [Keygraph website](https://keygraph.io), read the [Keygraph platform technical overview](docs/keygraph-platform.md), start a free trial or book a [demo](https://cal.com/team/keygraph/shannon-pro), or contact [shannon@keygraph.io](mailto:shannon@keygraph.io).

## Architecture

Shannon uses a multi-agent workflow that combines source-code analysis with live exploitation:

```text
        ┌──────────────────────┐
        │   Pre-Reconnaissance │
        │   (source code scan) │
        └──────────┬───────────┘
                   │
                   ▼
        ┌──────────────────────┐
        │   Reconnaissance     │
        │  (attack surface     │
        │   mapping)           │
        └──────────┬───────────┘
                   │
                   ▼
        ┌──────────┴───────────┐
        │          │           │
        ▼          ▼           ▼
  ┌───────────┐ ┌───────────┐ ┌───────────┐
  │ Vuln      │ │ Vuln      │ │   ...     │
  │(Injection)│ │  (XSS)    │ │           │
  └─────┬─────┘ └─────┬─────┘ └─────┬─────┘
        │              │             │
        ▼              ▼             ▼
  ┌───────────┐ ┌───────────┐ ┌───────────┐
  │ Exploit   │ │ Exploit   │ │   ...     │
  │(Injection)│ │  (XSS)    │ │           │
  └─────┬─────┘ └─────┬─────┘ └─────┬─────┘
        │              │             │
        └──────┬───────┴─────────────┘
               │
               ▼
        ┌──────────────────────┐
        │      Reporting       │
        └──────────────────────┘
```

At a high level:

- **Pre-reconnaissance** identifies frameworks, entry points, data flows, and likely attack surfaces from the repository.
- **Reconnaissance** explores the live application and correlates runtime behavior with code-level context.
- **Vulnerability analysis** runs specialized agents for Injection, XSS, SSRF, Authentication, and Authorization.
- **Exploitation** attempts real proof-of-concept attacks and discards hypotheses that cannot be proven.
- **Reporting** compiles validated findings, evidence, and remediation guidance into a final Markdown report.

Each scan runs in an ephemeral Docker container with an isolated workspace and per-invocation orchestration.

## Documentation

Use these guides for operational detail:

| Guide | Use it for |
| --- | --- |
| [Source build and CLI commands](docs/development.md) | Cloning, building, common commands, output paths, and local development. |
| [Configuration](docs/configuration.md) | Authenticated testing, login flows, rules of engagement, and report filters. |
| [AI providers](docs/ai-providers.md) | Selecting the model, the supported providers (Anthropic, OpenAI, xAI, AWS Bedrock, and any other Pi-supported provider), and custom gateways. |
| [Platforms and networking](docs/platforms.md) | Windows/WSL2, Linux, macOS, Docker networking, local apps, and custom hostnames. |
| [Workspaces and resuming](docs/workspaces.md) | Naming workspaces, resuming interrupted scans, and workspace storage. |
| [Safety and limitations](docs/safety.md) | Authorized-use requirements, non-production guidance, mutative effects, cost, and model caveats. |
| [Coverage and roadmap](docs/coverage-roadmap.md) | Current vulnerability coverage and planned work. |
| [Keygraph platform](docs/keygraph-platform.md) | The continuous, agentic pentesting platform: code analysis, black-box and white-box testing, finding management, remediation, verification, and enterprise deployment. |

## Safety, Scope, and Limitations

Shannon is not a passive scanner. Its exploitation agents can create users, submit forms, mutate application state, trigger outbound requests, and otherwise affect the target system. Use sandboxed, staging, or local development environments with disposable data.

You are responsible for using Shannon legally and ethically. Do not point Shannon at systems, repositories, or applications you do not own or do not have explicit authorization to test.

Important limitations:

- Shannon Open Source focuses on actively exploitable issues such as Injection, XSS, SSRF, Broken Authentication, and Broken Authorization. Broader static-analysis coverage, including vulnerable dependencies and insecure configurations, is delivered through the Keygraph platform.
- Findings still require human review. LLM-generated reports can contain weakly supported or incorrect details.
- Anthropic, OpenAI, xAI, and AWS Bedrock are built-in providers, and any Anthropic Messages API or OpenAI Chat Completions or Responses API endpoint works through a custom base URL. Model capability varies, and a model that does not follow Shannon's instructions or tool-use constraints reliably will produce weaker results.
- A full run can take roughly 1 to 1.5 hours and may incur LLM API costs depending on model pricing and application complexity.
- Do not scan untrusted or adversarial codebases. AI-powered tools that read source code can be exposed to prompt injection.

Read the full [Safety and limitations](docs/safety.md) guide before running Shannon in a new environment.

## License

Shannon Open Source is licensed under the [GNU Affero General Public License v3.0](LICENSE).

Commercial and enterprise licensing is available for organizations that need different license terms, commercial support, private redistribution, managed-service use, or broader deployment options, including the Keygraph platform.

For commercial licensing, contact [shannon@keygraph.io](mailto:shannon@keygraph.io).

## About Keygraph

**Keygraph** is the company behind Shannon. It also builds the **Keygraph platform**, the commercial agentic pentesting product that closes the full AppSec lifecycle and runs an enhanced build of Shannon as its pentesting engine.

## Community and Support

**Community office hours** are available for hands-on help with bugs, deployments, and configuration questions.

- US/EU: Thursday, 10:00 AM PT
- Asia: Thursday, 2:00 PM IST
- [Book a slot](https://cal.com/george-flores-keygraph/shannon-community-office-hours)

[Join Discord](https://discord.gg/cmctpMBXwE) to ask questions, share feedback, and connect with other Shannon users.

At this time, Keygraph is not accepting external code contributions. Issues are welcome for bug reports and feature requests:

- [Report bugs](https://github.com/KeygraphHQ/shannon/issues)
- [Suggest features](https://github.com/KeygraphHQ/shannon/discussions)

Stay connected:

- [Keygraph website](https://keygraph.io)
- [Twitter/X: @KeygraphHQ](https://twitter.com/KeygraphHQ)
- [LinkedIn: Keygraph](https://linkedin.com/company/keygraph)

## Common Questions

### Can I self-host Shannon?

Yes. Shannon Open Source runs entirely on your own infrastructure in an ephemeral Docker container. Your source code is mounted read-only and never leaves your environment.

### Does Shannon support bring your own key (BYOK)?

Yes, always. You provide the LLM credentials Shannon uses to run a pentest, in every deployment, open source and commercial. Keygraph never proxies your model traffic.

### Does Shannon output SARIF?

Yes. Shannon emits SARIF 2.1.0, the OASIS standard format for static analysis results, alongside structured JSON. Any SARIF consumer reads it: code scanning services, vulnerability management platforms, security dashboards, and CI/CD pipelines. It is written by default on exploit-mode scans; set `report.sarif` to `"false"` in your configuration file to opt out.

### Which AI providers does Shannon support?

Anthropic, OpenAI, xAI, and AWS Bedrock are built in and configured directly by provider ID. Beyond those, Shannon runs on any endpoint that implements the Anthropic Messages API or the OpenAI Chat Completions or Responses API, reached through a custom base URL. The rule is the API format, not the vendor. Shannon uses a single unified model setting throughout a pentest.

### Can I run Shannon on a local or self-hosted model?

Technically yes, but it is not recommended. Shannon works with local models served through Ollama, vLLM, or LM Studio, which expose an OpenAI-compatible endpoint, as well as routers such as OpenRouter and gateways such as LiteLLM. Point Shannon at the endpoint with a custom base URL. Capability varies, and a model that does not follow Shannon's instructions or tool-use constraints reliably will produce weaker pentests than a frontier model, so take this path only if you know how your chosen model behaves. See [AI providers](docs/ai-providers.md#custom-base-url).

### Does Shannon actually exploit vulnerabilities, or just scan?

Shannon executes real exploits. It reports a finding only when it has produced a working proof-of-concept, and discards hypotheses it cannot prove. It is a pentester, not a scanner.

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  <b>Built by <a href="https://keygraph.io">Keygraph</a></b>
</p>
