Privilege escalation via aggregated TrainJob permissions
Published Aug 10, 2026 · Updated Aug 10, 2026
Improper access control in Red Hat OpenShift AI 3.3 and 3.4 allows remote authenticated users to gain TrainJob management privileges. The training-operator overlay labels a TrainJob CRUD ClusterRole for aggregation into Kubernetes' built-in edit ClusterRole, silently extending every namespace editor's permissions. Namespace editor access is required, and arbitrary code execution additionally depends on a separate flaw that permits attacker-controlled pod configurations.
Summary
What happened
Improper access control in Red Hat OpenShift AI 3.3 and 3.4 allows remote authenticated users to gain TrainJob management privileges. The training-operator overlay labels a TrainJob CRUD ClusterRole for aggregation into Kubernetes' built-in edit ClusterRole, silently extending every namespace editor's permissions. Namespace editor access is required, and arbitrary code execution additionally depends on a separate flaw that permits attacker-controlled pod configurations.
The record
- CVE
- CVE-2026-18951
- Published
- Aug 10, 2026
- Updated
- Aug 10, 2026
- Vendor
- 389 Directory Server
- Product
- Red Hat OpenShift AI
- Classifications
- CWE-284, T1068
- Attack vector
- network
- Privileges
- authenticated
Timeline
How it unfolded
- Aug 10, 2026CVE publishedPublication date reported by the CVE source.
- Aug 10, 2026Record updatedLatest update available in the CVE record.
Exploitability
Present is not the same as exploitable
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What is affected?
Published CVSS scores
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Attacks
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Weakness, pattern, technique
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Technologies
Your stack
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Your stack
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