CVE-2026-15467 (GCVE-0-2026-15467)

Vulnerability from cvelistv5 – Published: 2026-08-10 20:44 – Updated: 2026-09-21 10:24
VLAI
Title
Trustyai-service-operator: trustyai-service-operator: lmevaljob sidecar containers bypass protected environment variable filtering, allowing trust_remote_code policy override
Summary
A flaw was found in the trustyai-service-operator's LMEvalJob controller. An authenticated user within the cluster can exploit this vulnerability by configuring a sidecar container to bypass existing security policies. This allows the user to enable and execute untrusted remote code, leading to arbitrary code execution within the cluster.
SSVC
Exploitation: none Automatable: no Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-08-12 15:42 UTC
CWE
  • CWE-266 - Incorrect Privilege Assignment
References
URL Tags
https://access.redhat.com/errata/RHSA-2026:53261 vendor-advisoryx_refsource_REDHAT
https://access.redhat.com/errata/RHSA-2026:53262 vendor-advisoryx_refsource_REDHAT
https://access.redhat.com/errata/RHSA-2026:53263 vendor-advisoryx_refsource_REDHAT
https://access.redhat.com/errata/RHSA-2026:60367 vendor-advisoryx_refsource_REDHAT
https://access.redhat.com/errata/RHSA-2026:60520 vendor-advisoryx_refsource_REDHAT
https://access.redhat.com/security/cve/CVE-2026-15467 vdb-entryx_refsource_REDHAT
https://bugzilla.redhat.com/show_bug.cgi?id=2499086 issue-trackingx_refsource_REDHAT
Impacted products
Vendor Product Version CPE status
Red Hat Red Hat OpenShift AI 2.25 Unaffected: 1785187119 , < * (rpm)
    cpe:/a:redhat:openshift_ai:2.25::el9
Create a notification for this product.
Red Hat Red Hat OpenShift AI 3.3 Unaffected: 1785187521 , < * (rpm)
    cpe:/a:redhat:openshift_ai:3.3::el9
Create a notification for this product.
Red Hat Red Hat OpenShift AI 3.4 Unaffected: 1784993206 , < * (rpm)
    cpe:/a:redhat:openshift_ai:3.4::el9
Create a notification for this product.
Red Hat Red Hat OpenShift AI 3.4 Unaffected: 1786614608 , < * (rpm)
    cpe:/a:redhat:openshift_ai:3.4::el9
Create a notification for this product.
Red Hat Red Hat OpenShift AI 3.5 Unaffected: 1786552271 , < * (rpm)
    cpe:/a:redhat:openshift_ai:3.5::el9
Create a notification for this product.
Red Hat Red Hat OpenShift AI 3.5 Unaffected: 1786552250 , < * (rpm)
    cpe:/a:redhat:openshift_ai:3.5::el9
Create a notification for this product.
Date Public
2026-08-10 18:43
Show details on NVD website

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              "lang": "en",
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                "confidentialityImpact": "HIGH",
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              "time": "2026-06-17T07:54:22.732Z",
              "value": "Reported to Red Hat."
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              "lang": "en",
              "time": "2026-08-10T18:43:08.877Z",
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          ],
          "title": "Trustyai-service-operator: trustyai-service-operator: lmevaljob sidecar containers bypass protected environment variable filtering, allowing trust_remote_code policy override",
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        "dateReserved": "2026-07-10T21:18:20.245Z",
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      },
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    }
  }
}



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Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

Sightings

Author Source Type Date Other

Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
  • Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

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Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.


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