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Ghosthunt

78degrees/ghosthunt
authSTDIOregistry active
Summary

Scans your local development machine for leaked credentials in environment files, shell history, and config files across AWS, Docker, GitHub CLI, npm, SSH, and 35+ secret patterns. Exposes two tools: scan_secrets for a full report with file paths and line numbers, and scan_summary for a quick health score from 0 to 100. Everything runs locally with no network calls. You'd reach for this when you want Claude to audit your machine for API keys you've accidentally left in .env files, pasted into bash history, or stored in ~/.aws/credentials, then get specific remediation steps for each finding.

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GhostHunt

Find every leaked secret on your machine.

GhostHunt is an MCP server that scans your development machine for API keys, tokens, and credentials hiding in places you forgot to check: .env files scattered across projects, shell history, AWS/SSH/Docker configs, and more.

Everything runs locally. No data leaves your machine.

What It Scans

  • Environment files — recursively finds every .env, .env.local, .env.production, etc. under your home directory
  • AWS credentials — ~/.aws/credentials and session tokens
  • SSH keys — unprotected private keys in ~/.ssh/
  • Docker config — registry auth tokens in ~/.docker/config.json
  • npm/PyPI tokens — ~/.npmrc, ~/.pypirc auth tokens
  • GitHub CLI — OAuth tokens in ~/.config/gh/hosts.yml
  • Shell history — API keys pasted into bash, zsh, or fish commands
  • Kubernetes — ~/.kube/config credentials
  • Netrc — ~/.netrc passwords
  • 35+ secret patterns — AWS, Stripe, GitHub, OpenAI, Anthropic, Google, Slack, Twilio, SendGrid, database connection strings, private keys, and more

Install

Claude Desktop

Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "ghosthunt": {
      "command": "npx",
      "args": ["-y", "ghosthunt"]
    }
  }
}

Restart Claude Desktop. Then ask Claude: "Scan my machine for leaked secrets"

Direct Usage

npx ghosthunt

Tools

scan_secrets

Full detailed scan. Returns every finding with file paths, line numbers, severity ratings, and remediation steps.

Example prompt: "Run a full GhostHunt scan and show me everything"

scan_summary

Quick health check. Returns your health score (0-100) and a count by severity. Run this first to see if you have a problem.

Example prompt: "Give me a quick GhostHunt health check"

Example Output

# GhostHunt Scan Report

**Health Score: 37/100** (Critical)

- Secrets found: **12**
- Critical: 3 | High: 5 | Medium: 2 | Low: 2
- Locations scanned: 47
- Scan time: 142ms

## Environment Files (.env)

- **[CRITICAL]** Stripe Live Secret Key
  - File: `/Users/you/project-a/.env:4`
  - Context: `STRIPE_SECRET_KEY`
  - Value: `sk_l****_8xQ`

- **[CRITICAL]** OpenAI API Key
  - File: `/Users/you/side-project/.env.local:12`
  - Context: `OPENAI_API_KEY`
  - Value: `sk-p****kFJ9`

## Shell History

- **[HIGH]** Bearer Token in Header
  - File: `/Users/you/.zsh_history:8847`
  - Context: `curl -H "Authorization: Bearer sk_live_...`
  - Value: `sk_l****_m3K`

## Recommendations

1. **Rotate critical secrets immediately.** Any API key marked CRITICAL
   should be revoked and regenerated from the provider's dashboard.
2. **Clear your shell history** of sensitive commands.
3. **Audit your .env files.** Ensure they are in .gitignore.

Health Score

Your score starts at 100 and drops based on what GhostHunt finds:

FindingPenalty
Critical secret-15
High severity-8
Medium severity-3
Low severity-1

A score below 50 means you have secrets that need immediate attention.

Privacy

GhostHunt runs entirely on your local machine. It does not:

  • Send any data to any server
  • Phone home or track usage
  • Store scan results anywhere
  • Access the internet

Your secrets stay on your machine. The scan results stay in your Claude conversation.

License

MIT

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Configuration

YOUR_API_KEY*secret

Your API key for the service

Categories
Developer Tools
Registryactive
Packageghosthunt
TransportSTDIO
AuthRequired
UpdatedMay 27, 2026
View on GitHub

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