CVE-2026-18951: CWE-267
Source GCVE Database
Not known to be exploited · CVSS 8.8 High : patch Red Hat OpenShift AI 3.3 soon.
Data as of 10 Nov 2026, 23:24 UTC
- 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:HExploitation evidence
Disclosed: evidence found.
CVE published 10 Aug 2026
Detectable: no evidence on record.
No public nuclei template indexed
Weaponized: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by 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 10 Nov 2026.
What to do
Patches and advisories
- access.redhat.com/errata/RHSA-2026:53262 (opens in a new tab)
- access.redhat.com/errata/RHSA-2026:53263 (opens in a new tab)
- access.redhat.com/errata/RHSA-2026:60367 (opens in a new tab)
- access.redhat.com/errata/RHSA-2026:60520 (opens in a new tab)
- access.redhat.com/errata/RHSA-2026:73987 (opens in a new tab)
Affected software
| Product | Affected | Fixed in |
|---|---|---|
| Red HatRed Hat OpenShift AI 3.3 | Affected– | Fixed in– |
| Red HatRed Hat OpenShift AI 3.3 | Affected– | Fixed in– |
| Red HatRed Hat OpenShift AI 3.4 | Affected– | Fixed in– |
| Red HatRed Hat OpenShift AI 3.4 | Affected– | Fixed in– |
| Red HatRed Hat OpenShift AI 3.5 | Affected– | Fixed in– |
| Red HatRed Hat OpenShift AI 3.5 | Affected– | Fixed in– |
AI-suggested
Red Hat has released OpenShift AI version 3.4.3 which addresses this vulnerability. Users should upgrade to RHOAI 3.4.3 following the official Red Hat documentation to fully apply the errata update. No other mitigations are indicated by the vendor advisory.
Description
A vulnerability in the Red Hat OpenShift AI (RHOAI) overlay for the training operator allows users with Kubernetes 'edit ClusterRole' permissions in a namespace to create, modify, and delete TrainJobs. This permission aggregation flaw, when combined with another vulnerability permitting arbitrary pod configurations, could enable a remote attacker with namespace editor privileges to escalate privileges and potentially execute arbitrary code.
References
- nvd.nist.gov/vuln/detail/CVE-2026-18951 (opens in a new tab)
- access.redhat.com/errata/RHSA-2026:53262 (opens in a new tab)
- access.redhat.com/errata/RHSA-2026:53263 (opens in a new tab)
- access.redhat.com/errata/RHSA-2026:60367 (opens in a new tab)
- access.redhat.com/errata/RHSA-2026:60520 (opens in a new tab)
- access.redhat.com/errata/RHSA-2026:73987 (opens in a new tab)
- access.redhat.com/security/cve/CVE-2026-18951 (opens in a new tab)
- bugzilla.redhat.com/show_bug.cgi?id=2511187 (opens in a new tab)