This document outlines the security measures implemented in the WL-Viz application and areas for potential improvement.

1. Input Validation

   • Max iterations parameter validated (1-50 range) to prevent DoS attacks
   • Type checking for all user inputs
   • Graph structure validation through NetworkX

2. Error Handling

   • Generic error messages to prevent information leakage
   • Detailed errors only logged server-side
   • Proper HTTP status codes (400, 500)

3. Secure Hashing

   • SHA-256 used for deterministic color generation in WL algorithm
   • Prevents hash collisions and ensures consistency across runs

4. Configuration Security

   • Environment variables for debug mode and host configuration
   • Default to localhost (127.0.0.1) instead of public (0.0.0.0)
   • Debug mode disabled by default

5. CORS Protection

   • Flask-CORS configured for controlled cross-origin requests

1. XSS Prevention

   • HTML escaping utility function for user-controlled content
   • Node IDs and labels escaped before insertion
   • Safe DOM manipulation methods used where possible

2. Data Sanitization

   • All API responses validated before rendering
   • User inputs sanitized before transmission

1. Template Literals in HTML Generation

   • Some innerHTML usage with template literals remains
   • Mitigation: Data comes from trusted backend API
   • Future: Consider migrating to a framework with safer templating (React, Vue)

2. Native prompt() Usage

   • Uses browser's prompt() for node label editing
   • Mitigation: Input is sanitized before use
   • Future: Implement custom modal dialog

3. Graph Size Performance

   • Full graph sent in each API request
   • Mitigation: Typical use case involves small graphs
   • Future: Implement graph caching or delta updates

4. ID Management

   • Node IDs increment indefinitely without reset
   • Mitigation: Acceptable for typical use cases
   • Future: Implement ID recycling or UUID-based system

1. SHA-256 Performance
   • SHA-256 chosen over MD5 for security, even though non-cryptographic use
   • Performance impact negligible for typical graph sizes (< 1000 nodes)
   • Deterministic hashing required for consistent WL algorithm results

export FLASK_DEBUG=true
export FLASK_HOST=127.0.0.1
python app.py

1. Use a Production WSGI Server

   pip install gunicorn
   gunicorn -w 4 -b 127.0.0.1:5000 app:app

2. Reverse Proxy (Nginx/Apache)

   • Place behind a reverse proxy for SSL/TLS
   • Configure rate limiting
   • Set up proper CORS policies

3. Environment Configuration

   export FLASK_DEBUG=false
   export FLASK_HOST=127.0.0.1
   export FLASK_PORT=5000

4. Additional Security Layers

   • Enable HTTPS/TLS
   • Implement rate limiting
   • Add authentication if needed
   • Configure CSP headers
   • Regular dependency updates

If you discover a security vulnerability, please report it by creating a private security advisory on GitHub rather than opening a public issue.

• Last Review: 2025-11-24
• Tools Used:
  • CodeQL Security Scanning
  • Manual Code Review
  • Flask Security Best Practices
• Status: No critical vulnerabilities identified