Remarkably-Mind-Blowing-Lab/Awesome-MLSecOps
A reading list for MLSecOps!
This project offers a comprehensive reading list for professionals integrating security into machine learning systems. It provides curated resources, from academic papers on model provenance and adversarial examples to tools and business platforms, helping you understand and implement security measures across the ML lifecycle. This is for ML engineers, security analysts, and operations teams tasked with building and maintaining secure AI applications.
141 stars. No commits in the last 6 months.
Use this if you need to research or implement security best practices for your machine learning models and pipelines.
Not ideal if you are looking for a software tool or library to directly implement MLSecOps solutions.
Stars
141
Forks
2
Language
JavaScript
License
MIT
Category
Last pushed
Mar 18, 2025
Commits (30d)
0
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