Where Security Fits in an AI Agent Stack | NVIDIA Technical Blog

This post details the security considerations for AI agent stacks, focusing on the distinction between behavioral and infrastructure controls. It introduces NVIDIA OpenShell as a secure runtime layer that enforces isolation, identity, policy, credentials, and audit for autonomous agents, and NVIDIA Dynamo as the inference data plane. Five design rules are proposed for enforceable agent security: higher layers propose actions while lower layers decide, policy remains below the security boundary, every effect is checked, access is just-in-time, and isolation enables recovery. Four security profiles (Isolated, Connected, Production, and Adversarial) are outlined, applying progressively stricter controls. The post emphasizes establishing the AI agent runtime boundary before launch and highlights common security gaps such as unclear boundaries, excessive access, untrusted data as control, uncontrolled external effects, compounding failures, and incomplete audit evidence.