AakilAhamed/risk-scanner
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Compliance Security MCP server is designed for regulatory checks and monitoring, ensuring adherence to compliance standards.
Risk Scanner
A compliance and security scanner that detects secrets, tokens, and insecure code patterns in GitHub repositories, files, or directories.
Includes a web application with PDF reporting and a CLI tool for local use.
🚀 Live Demo
The web app is deployed on Render:
👉 https://risk-scanner.onrender.com/
✨ Features
- Scan GitHub repositories, local files, or directories
- Detect common secrets (AWS keys, GitHub tokens, Slack tokens, etc.)
- Identify debug statements and weak patterns
- Severity breakdown with risk score
- Export a neatly formatted PDF report
- Web app (Flask + Gunicorn) and CLI modes
- Deployable to Render with one click
📦 Local Setup
1. Clone the repository
git clone https://github.com/yourusername/risk-scanner.git
cd risk-scanner
2. Install dependencies
pip install -r requirements.txt
3. Set up GitHub token (optional but recommended)
Without a token, you are limited to 60 GitHub API requests/hour.
With a token, you get 5,000 requests/hour.
-
Windows (Command Prompt):
set GITHUB_TOKEN=ghp_yourtokenhere -
Windows (PowerShell):
$env:GITHUB_TOKEN="ghp_yourtokenhere" -
Linux / macOS (Bash / Zsh):
export GITHUB_TOKEN=ghp_yourtokenhere
🖥️ CLI Usage
Scan a GitHub repository:
python cli_wrapper.py scan-repo https://github.com/GitGuardian/sample_secrets
Scan a local file:
python cli_wrapper.py scan-file path/to/file.py
Scan a directory:
python cli_wrapper.py scan-dir ./src
Save results to JSON:
python cli_wrapper.py scan-repo https://github.com/GitGuardian/sample_secrets --output results.json
🌐 Web Application (Local)
Run the Flask app locally:
python app.py
Then open http://localhost:8000 in your browser.
Features:
- Enter a GitHub repo URL and scan
- View summary and findings
- Export a neatly formatted PDF report
🔎 Example
Try scanning this repo with test secrets:
python cli_wrapper.py scan-repo https://github.com/GitGuardian/sample_secrets
📄 License
MIT