SSRF in Red Hat Openshift Ai (Rhoai)
CVE-2026-17557
A flaw was found in the `lm-evaluation-harness` component of Red Hat OpenShift AI. An authenticated user, able to submit an evaluation job, could exploit this by providing a malicious model URL in the `JobSpec`. This vulnerability allows for the disclosure of the tenant's model authentication secret to an attacker-controlled external listener. Additionally, it enables Server-Side Request Forgery (SSRF) attacks against internal network endpoints reachable from the evaluation job pod.
Vulnerability class: SSRF (Server-Side Request Forgery)
Published · last modified .
CVSS v3 metric
CVSS v3 base score 6.5 (Medium). Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N.
EPSS exploit prediction
No EPSS score from FIRST.org yet. New CVEs usually get one within a few days; no score means no signal yet, not low risk. How EPSS works.
Affected products
Weakness classification (CWE)
References
- access.redhat.com/security/cve/CVE-2026-17557 (vdb-entry)
- bugzilla.redhat.com/show_bug.cgi (issue-tracking)
Frequently asked questions
- What is CVE-2026-17557?
- CVE-2026-17557 is a medium-severity vulnerability in Red Hat Openshift Ai (Rhoai), classified under Server-Side Request Forgery (SSRF). CVSS score: 6.5/10. Published 2026-10-21.
- How severe is CVE-2026-17557?
- Medium severity. CVSS v3 base score is 6.5 out of 10.