GPU VulnDB

Database/AI/ML frameworks & serving

OpenShift AI guardrails-detectors: unauthenticated blind SSRF and file read via crafted XSD

CVE-2026-15378AI/ML frameworks & servingcurated

Impact

A crafted XML Schema Definition string submitted to the guardrails-detectors component drives a blind server-side request from inside the cluster, and Red Hat names the targets explicitly: cloud metadata services, the Kubernetes API, internal MinIO, and other internal endpoints. The same flaw also reads local files, which on a pod means the mounted ServiceAccount token and pod secrets. That turns a guardrails endpoint - typically one of the more exposed pieces of an inference stack - into a route to cluster credentials and to the object storage holding model weights and datasets. Confidentiality is the main loss here; the CVSS vector rates integrity low and availability none.

Who can reach it

Anyone able to reach the guardrails-detectors endpoint and submit a schema string. The CVSS vector records no privileges required, so treat it as unauthenticated from wherever that endpoint is exposed.

What to do

Apply RHSA-2026:60520 for Red Hat OpenShift AI 3.4 and let the operator redeploy the detector pods - a rolling restart of the affected deployment, no node maintenance. Until then, keep the detector endpoint off any network path reachable by untrusted callers, and rotate ServiceAccount tokens and MinIO credentials the pod could have read if you believe it was exposed.

References

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This entry is curated: imported from vendor advisories with machine assistance, not yet individually verified. Confirm against your vendor's advisory before acting, and report anything wrong.