CVE-2026-15378 (GCVE-0-2026-15378)
Vulnerability from cvelistv5 – Published: 2026-07-10 09:29 – Updated: 2026-09-30 16:20
VLAI
EPSS
VEX
Title
Guardrails-detectors: guardrails-detectors: ssrf and local file read via user-supplied xml schema (xml-with-schema:)
Summary
A flaw was found in the `guardrails-detectors` component. This vulnerability allows a remote attacker to perform a blind Server-Side Request Forgery (SSRF) by submitting a specially crafted XML Schema Definition (XSD) string. This can lead to unauthorized access to sensitive information, including credentials from cloud metadata services, Kubernetes API, internal MinIO, and other internal network endpoints. Additionally, it enables local file reads of critical data such as service account tokens and pod secrets.
Severity
9.3 (Critical)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-07-14 01:36 UTC
CWE
- CWE-918 - Server-Side Request Forgery (SSRF)
Assigner
References
5 references
| URL | Tags |
|---|---|
| https://access.redhat.com/errata/RHSA-2026:60520 | vendor-advisoryx_refsource_REDHAT |
| https://access.redhat.com/errata/RHSA-2026:65126 | vendor-advisoryx_refsource_REDHAT |
| https://access.redhat.com/errata/RHSA-2026:73987 | vendor-advisoryx_refsource_REDHAT |
| https://access.redhat.com/security/cve/CVE-2026-15378 | vdb-entryx_refsource_REDHAT |
| https://bugzilla.redhat.com/show_bug.cgi?id=2498941 | issue-trackingx_refsource_REDHAT |
Impacted products
3 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1786710963 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.3 |
Unaffected:
1789656673 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.3::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1787360218 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
Date Public
2026-07-10 09:19
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The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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