The Infrastructure That Powers AI Could Also Break It

When it comes to securing AI, most conversations focus on the model layer: Prompt injection, training data leakage and unsafe outputs. But there’s a more immediate risk that often goes overlooked: the infrastructure powering those models.

AI workloads rely on the same foundations as modern cloud native applications. That means containers, Kubernetes, shared GPU nodes and orchestration layers that were never designed with AI-specific risks in mind. And because these components are being reused at scale, any vulnerability in the stack has the…