AI Identity, Access & Model Security Management Playbook
- Practitioner
- Advanced
- Template Included
A framework for AI identity, access, and model security management — access control for training data and model artifacts, protecting against model theft and extraction attacks, and securing AI-specific attack surfaces — treating AI systems as production infrastructure requiring dedicated security discipline, not an afterthought relative to traditional application security.
Does standard application security cover AI system security
adequately? Standard application security addresses infrastructure and access concerns AI systems share with other software, but AI introduces distinctive attack surfaces — model extraction, training data poisoning, prompt injection — that require dedicated security consideration beyond traditional application security practices.
What's "model extraction" and why does it matter for AI security?
Model extraction refers to attacks that attempt to reconstruct or steal a proprietary model's behavior through systematic querying, a risk specific to AI systems that traditional application security practices don't typically address, requiring dedicated access control and monitoring for query patterns.
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