The document introduces SecureTF, a framework designed to ensure the confidentiality and integrity of machine learning data and models using Intel SGX technology. It addresses limitations of existing systems by supporting both training and inference while maintaining security and performance. The evaluation shows that SecureTF incurs only minimal overhead compared to native implementations, providing a transparent solution for unmodified TensorFlow applications.