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SecureAIML v0.1.2 - AI ML Model Security

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@ronykris ronykris released this 25 Dec 18:09
· 8 commits to master since this release
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πŸŽ‰ SecureAIML v0.1.2 - Initial Public Release

Welcome to SecureAIML! The first public release of enterprise-ready ML model security built on OpenSSF Model Signing standards.

πŸš€ What is SecureAIML?

SecureAIML is the "Stripe for model security" - making enterprise-grade AI model protection accessible, user-friendly, and production-ready for every organization.

✨ Core Features

Universal Model Support:

  • Traditional ML: scikit-learn, XGBoost, LightGBM, CatBoost
  • Deep Learning: PyTorch, TensorFlow, Keras, JAX
  • Large Language Models: HuggingFace Transformers
  • Computer Vision: ONNX

Security Features:

  • πŸ”’ Model watermarking (parameter, trigger set, statistical)
  • ✍️ Cryptographic signing via OpenSSF Model Signing
  • πŸ›‘οΈ Model fingerprinting and integrity verification
  • πŸ“Š Compliance framework support (SOC2, ISO27001, HIPAA, GDPR)

Developer Experience:

  • Simple, Pythonic API
  • Comprehensive CLI interface
  • Extensive documentation and examples
  • Interactive demos and tutorials

πŸ§ͺ Quality Assurance

  • βœ… 34 comprehensive unit tests (48% code coverage)
  • βœ… Automated CI/CD with GitHub Actions
  • βœ… Multi-Python support (3.8, 3.9, 3.10, 3.11)
  • βœ… Professional threat model documentation

πŸ“¦ Installation

pip install secureaiml

🏁 Quick Start

from secureml import SecureModel
import joblib

# Load your model
model = joblib.load("model.pkl")

# Secure it in one line
secure_model = SecureModel(model)
secure_model.sign_and_save("model.sml", identity="[email protected]")

# Load and verify
verified_model = SecureModel.load("model.sml", verify=True)
predictions = verified_model.predict(X_test)

πŸ“š Documentation

πŸ”— Links


Welcome to the future of ML model security! πŸš€πŸ”

Made with ❀️ by the OWASP community


This version emphasizes that it's the inaugural release and welcomes users to the project! 🎊