CVE-2026-15154

Published Jul 8, 2026

Last updated 18 days ago

CVSS medium 6.5

Overview

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.
Source
secalert@redhat.com
NVD status
Analyzed
Products
openshift_ai

Risk scores

CVSS 3.1

Type
Secondary
Base score
6.5
Impact score
3.6
Exploitability score
2.8
Vector string
CVSS:3.1/AV:A/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Severity
MEDIUM

Weaknesses

secalert@redhat.com
CWE-1333

Social media

Hype score
Not currently trending

Configurations

Related CVEs

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  2. BerriAI LiteLLM Command Injection Vulnerability•CVE-2026-42271
  3. A vulnerability in the `TFSMLayer` class of the `keras` package, version 3.13.0, allows attacker-controlled TensorFlow SavedModels to be loaded during deserialization of `.keras` models, even when `safe_mode=True`. This bypasses the security guarantees of `safe_mode` and enables arbitrary attacker-controlled code execution during model inference under the victim's privileges. The issue arises due to the unconditional loading of external SavedModels, serialization of attacker-controlled file paths, and the lack of validation in the `from_config()` method.•CVE-2026-1462
  4. A flaw was found in odh-dashboard in Red Hat Openshift AI. This vulnerability in the `odh-dashboard` component of Red Hat OpenShift AI (RHOAI) allows for the disclosure of Kubernetes Service Account tokens through a NodeJS endpoint. This could enable an attacker to gain unauthorized access to Kubernetes resources.•CVE-2026-5483
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References

Sources include official advisories and independent security research.