Guide
Your Blueprint to Securing AI Workloads, the Right Way
The blueprint explains how AI workloads expand the cloud attack surface because they are dynamic, API-heavy, data-intensive, and often run in short-lived containers across hybrid and multicloud environments, which makes perimeter-style security insufficient. It recommends comprehensive cloud security spanning the stack, organized into three pillars: visibility (build an inventory of models, where they run, what data they touch, and who can access them), prevention (least-privilege identity controls, continuous vulnerability scanning for images and dependencies, and posture management to reduce misconfigurations, with emerging AI-SPM as a next step), and real-time detection and response that assumes breach, correlates signals, and automates containment. It includes a 10-question self-assess
