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VulnerabilityPublished Updated

CVE-2026-18951: Red Hat OpenShift AI 3.3 · Privilege Defined With Unsafe Actions

Affects Red Hat OpenShift AI 3.3Source CVE Database V5

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Not known to be exploited · CVSS 8.8 High.

Data as of 7 Nov 2026, 23:24 UTC

CVSS 3.1 base score
8.8High
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.9% chance of exploitation in 30 days – higher than 60% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 10 Aug 2026

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponized: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq Mirage: no evidence on record.

    No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 8 Nov 2026.

What to do

Affected software

ProductAffectedFixed in
Red HatRed Hat OpenShift AI 3.3Affected–Fixed in–
Red HatRed Hat OpenShift AI 3.3Affected–Fixed in–
Red HatRed Hat OpenShift AI 3.4Affected–Fixed in–
Red HatRed Hat OpenShift AI 3.4Affected–Fixed in–
Red HatRed Hat OpenShift AI 3.5Affected–Fixed in–
Red HatRed Hat OpenShift AI 3.5Affected–Fixed in–

AI-suggested

Administrators should review and adjust Kubernetes RBAC configurations within Red Hat OpenShift AI to explicitly manage trainjobs permissions. This includes removing trainjobs from the aggregate-to-edit ClusterRole labels or requiring explicit RoleBindings for trainjobs access. These changes prevent implicit permission grants to namespace editors and reduce the attack surface. A restart or reload of affected components may be necessary for changes to take effect.

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.

References

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