ThalesGroup/secure-ml

Explore ThalesGroup's comprehensive framework for secure machine learning systems on this repository. Developed by Thales experts, this framework encompasses essential security requirements, guidelines, tools, and privacy recommendations tailored specifically for machine learning applications.

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This framework helps organizations build and maintain secure machine learning systems. It provides comprehensive guidelines, policies, and a curated list of tools to protect ML datasets, models, and infrastructure. Security architects, data scientists, and ML engineers can use this to ensure compliance, mitigate threats, and implement privacy-preserving techniques throughout the ML lifecycle.

Use this if you are responsible for the security and privacy of machine learning systems within your organization and need a structured approach to protect against threats and ensure compliance.

Not ideal if you are looking for a plug-and-play software solution rather than a comprehensive set of policies, guidelines, and tool recommendations.

MLSecOps data-privacy cybersecurity-governance AI-risk-management compliance-auditing
No Package No Dependents
Maintenance 10 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 16 / 25

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Category

ai-red-teaming

Last pushed

Feb 01, 2026

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