CVE-2026-15154: Inefficient Regular Expression Complexity in Red Hat Red Hat OpenShift AI (RHOAI)
A flaw was found in `guardrails-detectors`, a component of Red Hat OpenShift AI. This vulnerability, known as Regular Expression Denial of Service (ReDoS), allows a remote attacker to provide specially crafted regular expressions to the public detection API. This can cause catastrophic backtracking, leading to a worker process consuming 100% CPU indefinitely and resulting in a denial of service for the entire guardrails-mediated LLM pipeline.
AI Analysis
Technical Summary
This vulnerability in Red Hat OpenShift AI's guardrails-detectors component allows remote attackers to exploit inefficient regular expression handling via the public detection API. By submitting crafted regex patterns, attackers can trigger catastrophic backtracking, causing a worker process to consume full CPU resources indefinitely. This leads to denial of service for the guardrails-mediated LLM pipeline. The CVSS vector indicates the attack requires adjacent network access, no privileges, and no user interaction, impacting availability only. No vendor advisory states a fix or mitigation at this time.
Potential Impact
The impact is a denial of service condition where a worker process in the guardrails-detectors component consumes 100% CPU indefinitely, disrupting the availability of the guardrails-mediated LLM pipeline. There is no confidentiality or integrity impact reported. The vulnerability can be triggered remotely by an attacker with network access to the public detection API.
Mitigation Recommendations
Patch status is not yet confirmed — check the Red Hat advisory at https://access.redhat.com/security/cve/CVE-2026-15154 for current remediation guidance. No official fix or workaround is currently documented. Until a patch is available, consider restricting access to the public detection API to trusted users or networks to reduce exposure.
CVE-2026-15154: Inefficient Regular Expression Complexity in Red Hat Red Hat OpenShift AI (RHOAI)
Description
A flaw was found in `guardrails-detectors`, a component of Red Hat OpenShift AI. This vulnerability, known as Regular Expression Denial of Service (ReDoS), allows a remote attacker to provide specially crafted regular expressions to the public detection API. This can cause catastrophic backtracking, leading to a worker process consuming 100% CPU indefinitely and resulting in a denial of service for the entire guardrails-mediated LLM pipeline.
CVSS v3.1
Score 6.5medium
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
This vulnerability in Red Hat OpenShift AI's guardrails-detectors component allows remote attackers to exploit inefficient regular expression handling via the public detection API. By submitting crafted regex patterns, attackers can trigger catastrophic backtracking, causing a worker process to consume full CPU resources indefinitely. This leads to denial of service for the guardrails-mediated LLM pipeline. The CVSS vector indicates the attack requires adjacent network access, no privileges, and no user interaction, impacting availability only. No vendor advisory states a fix or mitigation at this time.
Potential Impact
The impact is a denial of service condition where a worker process in the guardrails-detectors component consumes 100% CPU indefinitely, disrupting the availability of the guardrails-mediated LLM pipeline. There is no confidentiality or integrity impact reported. The vulnerability can be triggered remotely by an attacker with network access to the public detection API.
Mitigation Recommendations
Patch status is not yet confirmed — check the Red Hat advisory at https://access.redhat.com/security/cve/CVE-2026-15154 for current remediation guidance. No official fix or workaround is currently documented. Until a patch is available, consider restricting access to the public detection API to trusted users or networks to reduce exposure.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- redhat
- Date Reserved
- 2026-07-08T19:44:43.020Z
- Cvss Version
- 3.1
- State
- PUBLISHED
- Remediation Level
- null
- Vendor Advisory Urls
- [{"url":"https://access.redhat.com/security/cve/CVE-2026-15154","vendor":"Red Hat"}]
Threat ID: 6a4eafe7c9d9e3dbe3adea04
Added to database: 07/08/2026, 20:15:35 UTC
Last enriched: 07/08/2026, 20:29:25 UTC
Last updated: 07/08/2026, 20:44:00 UTC
Views: 2
Community Reviews
0 reviewsCrowdsource mitigation strategies, share intel context, and vote on the most helpful responses. Sign in to add your voice and help keep defenders ahead.
Want to contribute mitigation steps or threat intel context? Sign in or create an account to join the community discussion.
Actions
Updates to AI analysis require Pro Console access. Upgrade inside Console → Billing.
Need more coverage?
Upgrade to Pro Console for AI refresh and higher limits.
For incident response and remediation, OffSeq services can help resolve threats faster.
Latest Threats
Check if your credentials are on the dark web
Instant breach scanning across billions of leaked records. Free tier available.