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Vulnerability · Published Aug 10, 2026 · Assigned by redhat

CVE-2026-18951Odh-training-operator-rhel9: [trainer v2 security] trn-02: rhoai overlay aggregates trainjobs crud into standard edit clusterrole

High 8.8

In plain English

A high-severity improper access control in Red Hat OpenShift AI 3.3 from Red Hat. There are no confirmed reports of exploitation so far. The chance it is exploited in the next 30 days is estimated at 0.9% (higher than 60% of all known vulnerabilities).

Severity (CVSS 3.1)8.8High
Exploit odds (30 days)0.9%top 39.7% of all CVEs
Exploited in the wildNo reportsCISA SSVC: none
Attack toolingNoneno public tooling known

Official description

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.

Affected products (as reported)

VendorProductVersions
Red Hat Red Hat OpenShift AI 3.3 see references
Red Hat Red Hat OpenShift AI 3.3 see references
Red Hat Red Hat OpenShift AI 3.4 see references
Red Hat Red Hat OpenShift AI 3.4 see references
Red Hat Red Hat OpenShift AI 3.5 see references
Red Hat Red Hat OpenShift AI 3.5 see references

Weakness: CWE-267, CWE-284 · Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

References