We actively maintain and provide security updates for the following versions:

kernel-course is primarily an educational project with small, self-contained kernels. It does not ship production CUDA/C++ extensions, but exercises and examples may run custom kernels on your GPU when you experiment with Triton or CuTe.

When using this repository:

• Only run code you understand, especially when modifying kernels.
• Use virtual environments to isolate dependencies.
• Be careful when experimenting with very large tensor sizes, as they may cause out-of-memory errors.

If you discover a security vulnerability, please report it responsibly:

For security issues:

• Email: losercheems@gmail.com
• Subject: [SECURITY] kernel_course Vulnerability Report
• Include: Detailed description, reproduction steps, and potential impact

For general bugs:

• Use our GitHub Issues
• Follow our contributing guidelines

• Acknowledgment: Within 48 hours
• Initial Assessment: Within 1 week
• Resolution: Depends on severity and complexity

Critical security issues will be prioritized and may result in emergency releases.

When using kernel-course:

1. Environment Isolation

   # Use virtual environments
   python -m venv kernel_course_env
   source kernel_course_env/bin/activate  # Linux/Mac
   # or
   kernel_course_env\Scripts\activate     # Windows

2. Dependency Management

   # Keep dependencies updated
   pip install --upgrade torch kernel-course

3. Input Validation

   # Validate tensor shapes and dtypes before processing
   assert x.dtype in [torch.float16, torch.bfloat16, torch.float32]
   assert x.shape == y.shape

4. Resource Monitoring

   # Monitor GPU memory usage
   import torch
   print(f"GPU Memory: {torch.cuda.memory_allocated() / 1e9:.2f} GB")

• Confirmed vulnerabilities will be disclosed responsibly
• Security fixes will be released as soon as safely possible
• CVE numbers will be requested for significant vulnerabilities
• Credit will be given to security researchers who report issues responsibly

For security-related questions or concerns:

• Primary: losercheems@gmail.com
• Project maintainers: See GitHub contributors

For general support:

• GitHub Issues: https://github.com/flash-algo/kernel-course/issues
• Documentation: see the main README and docs/ in this repository.