A flaw was found in the Red Hat OpenShift AI (RHOAI) overlay for the training operator. The RHOAI overlay incorrectly aggregates trainjobs management permissions into the native Kubernetes edit ClusterRole. This allows any user with edit ClusterRole permissions in a namespace to create, modify, and delete TrainJobs. When combined with a separate vulnerability (TRN-01) that permits arbitrary pod configurations, a remote attacker with namespace editor privileges could exploit this to escalate privileges, potentially leading to arbitrary code execution.
Administrators should review and adjust their Kubernetes RBAC configurations within Red Hat OpenShift AI to ensure that trainjobs permissions are explicitly managed. This involves removing trainjobs from the aggregate-to-edit ClusterRole labels or requiring explicit RoleBinding for trainjobs access. This prevents implicit permission grants to namespace editors and reduces the attack surface. Consult Kubernetes documentation for specific instructions on modifying ClusterRoles and RoleBindings. A restart or reload of affected components may be required for changes to take effect.