A flaw was found in guardrails-detectors, a component of Red Hat OpenShift AI. (CVE-2026-15154)
A Regular Expression Denial of Service (ReDoS) vulnerability was identified in guardrails-detectors, a component of Red Hat OpenShift AI. This flaw allows remote attackers to submit crafted regular expressions to the public detection API, causing catastrophic backtracking that leads to 100% CPU consumption by a worker process and denial of service for the guardrails-mediated LLM pipeline. The vulnerability has a CVSS score of 6.5, indicating medium severity. Red Hat has released updated images for Red Hat OpenShift AI versions 2.25.10 and 3.4.3 that address this issue. Users are advised to upgrade to these versions following Red Hat's official documentation to mitigate the risk.
AI Analysis
Technical Summary
CVE-2026-15154 is a Regular Expression Denial of Service (ReDoS) vulnerability in the guardrails-detectors component of Red Hat OpenShift AI. It allows remote attackers to provide specially crafted regular expressions to the public detection API, triggering catastrophic backtracking that causes a worker process to consume 100% CPU indefinitely. This results in denial of service for the entire guardrails-mediated large language model (LLM) pipeline. The vulnerability is tracked under CWE-1333. Red Hat has issued security advisories RHSA-2026:53261 and RHSA-2026:53262, releasing updated images in RHOAI 2.25.10 and 3.4.3 respectively, which include fixes for this and other CVEs. Detailed upgrade instructions are available in Red Hat's official OpenShift AI documentation.
Potential Impact
Exploitation of this vulnerability results in denial of service by causing a worker process to consume all CPU resources indefinitely, disrupting the guardrails-mediated LLM pipeline in Red Hat OpenShift AI. There is no impact on confidentiality or integrity reported. The attack vector is remote with low attack complexity and no privileges or user interaction required.
Mitigation Recommendations
Red Hat has released updated images for Red Hat OpenShift AI versions 2.25.10 and 3.4.3 that address this vulnerability. Users should upgrade their OpenShift AI clusters to these versions following the official Red Hat documentation to fully apply the errata updates. No other mitigation or workaround is indicated in the vendor advisories.
A flaw was found in guardrails-detectors, a component of Red Hat OpenShift AI. (CVE-2026-15154)
Description
A Regular Expression Denial of Service (ReDoS) vulnerability was identified in guardrails-detectors, a component of Red Hat OpenShift AI. This flaw allows remote attackers to submit crafted regular expressions to the public detection API, causing catastrophic backtracking that leads to 100% CPU consumption by a worker process and denial of service for the guardrails-mediated LLM pipeline. The vulnerability has a CVSS score of 6.5, indicating medium severity. Red Hat has released updated images for Red Hat OpenShift AI versions 2.25.10 and 3.4.3 that address this issue. Users are advised to upgrade to these versions following Red Hat's official documentation to mitigate the risk.
CVSS v3.1
Score 6.5medium
Weaknesses
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
CVE-2026-15154 is a Regular Expression Denial of Service (ReDoS) vulnerability in the guardrails-detectors component of Red Hat OpenShift AI. It allows remote attackers to provide specially crafted regular expressions to the public detection API, triggering catastrophic backtracking that causes a worker process to consume 100% CPU indefinitely. This results in denial of service for the entire guardrails-mediated large language model (LLM) pipeline. The vulnerability is tracked under CWE-1333. Red Hat has issued security advisories RHSA-2026:53261 and RHSA-2026:53262, releasing updated images in RHOAI 2.25.10 and 3.4.3 respectively, which include fixes for this and other CVEs. Detailed upgrade instructions are available in Red Hat's official OpenShift AI documentation.
Potential Impact
Exploitation of this vulnerability results in denial of service by causing a worker process to consume all CPU resources indefinitely, disrupting the guardrails-mediated LLM pipeline in Red Hat OpenShift AI. There is no impact on confidentiality or integrity reported. The attack vector is remote with low attack complexity and no privileges or user interaction required.
Mitigation Recommendations
Red Hat has released updated images for Red Hat OpenShift AI versions 2.25.10 and 3.4.3 that address this vulnerability. Users should upgrade their OpenShift AI clusters to these versions following the official Red Hat documentation to fully apply the errata updates. No other mitigation or workaround is indicated in the vendor advisories.
Technical Details
- Gcve Source
- db.gcve.eu
- Osv Id
- GHSA-jm96-7wvj-j3r9
- Osv Schema Version
- 1.4.0
- Aliases
- ["CVE-2026-15154"]
- Ecosystems
- []
- Database Specific Severity
- MODERATE
- Cvss Version
- 3.1
Patch Information
Threat ID: 6a7c9b7dbf8831d539ce15d3
Added to database: 08/12/2026, 16:12:45 UTC
Last enriched: 08/12/2026, 17:36:39 UTC
Last updated: 08/12/2026, 17:36:39 UTC
Views: 4
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