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Contributing to AI Security Code Examples

Thank you for your interest in contributing to this project! This repository provides practical examples for implementing AI security measures.

How to Contribute

Reporting Issues

  • Use GitHub Issues to report bugs or suggest enhancements
  • Provide clear descriptions and steps to reproduce issues
  • Include relevant system information and error messages

Submitting Code

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/new-security-example)
  3. Make your changes
  4. Add tests and documentation
  5. Commit with clear messages (git commit -m 'Add new defensive prompt example')
  6. Push to your branch (git push origin feature/new-security-example)
  7. Create a Pull Request

Code Standards

Python Code

  • Follow PEP 8 style guidelines
  • Use type hints where appropriate
  • Include docstrings for functions and classes
  • Add comprehensive comments for security-related logic

YAML Configurations

  • Use consistent indentation (2 spaces)
  • Include descriptive comments
  • Validate configurations before submitting

Documentation

  • Update README files when adding new examples
  • Include usage instructions and expected results
  • Explain security concepts clearly

Security Considerations

Responsible Disclosure

  • Do not include real API keys or credentials
  • Use placeholder values in examples
  • Report security vulnerabilities privately first

Testing

  • Test all security examples thoroughly
  • Verify that defensive measures work as expected
  • Include both positive and negative test cases

Review Process

All contributions will be reviewed for:

  • Code quality and security best practices
  • Documentation completeness
  • Test coverage
  • Alignment with project goals

Questions?

Feel free to open an issue for questions about contributing or reach out to the maintainers.

Thank you for helping make AI systems more secure!