AI Security: Identity And Access Control
Red Hat, March 27,2026
In our first 3 articles, we framed AI security as protecting the system, not just the model, across confidentiality, integrity, and availability, and we showed why the traditional secure development lifecycle (SDLC) discipline still applies to modern AI deployments.
This article completes the defense strategy by focusing on the backbone that makes guardrails enforceable in production-identity, authentication, authorization, and zero trust.
Guardrails reduce the likelihood of unsafe behavior, but identity and authorization limit the damage if something goes wrong. If an AI system runs with broad, always-on permissions, a clever prompt can turn "text" into "action." Strong identity access management (IAM) helps prevent that by making sure the system cannot execute privileged operations unless the right identity is proven and the right authorization is present.