AI platforms rely on privileged credentials—API keys, service accounts, and administrative access—that, if mismanaged, can expose entire systems to compromise.
Privileged Access for Models is a technical guide for security engineers responsible for securing secrets, keys, and administrative access across machine learning infrastructure. The book focuses on practical controls that reduce blast radius while maintaining operational efficiency.
It addresses privileged access as a first-class risk in AI systems, not an afterthought inherited from traditional IT environments.
Readers will learn how to:
- Identify privileged access paths across AI platforms and pipelines
- Secure model API keys, tokens, and service credentials
- Apply least-privilege principles to model training and inference
- Integrate secrets management into MLOps workflows
- Monitor and audit privileged access to AI infrastructure
- Reduce credential sprawl across cloud and ML environments
This book helps teams prevent high-impact security failures by bringing discipline and visibility to privileged access in AI systems.
