CVE Vulnerabilities

CVE-2026-85999

Uncontrolled Resource Consumption

Published: Sep 17, 2026 | Modified: Sep 23, 2026
CVSS 3.x
N/A
Source:
NVD
CVSS 2.x
RedHat/V2
RedHat/V3
5.9 MODERATE
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Ubuntu
MEDIUM

Soup Sieve is a CSS selector library designed to be used with Beautiful Soup 4. Prior to 2.9, selector_iter in src/soupsieve/css_parser.py trims the raw selector with RE_WS_END, an end-anchored WSC whitespace-and-comment expression used with search(), so the regular expression engine retries a greedy scan at every starting offset. An attacker-controlled valid selector containing a long internal whitespace run, or a selector containing a long CSS comment run followed by another token, causes quadratic CPU work before tokenization. User-controlled selectors can reach the path through soupsieve.compile() and BeautifulSoup.select(), while applications using only hard-coded selectors are unaffected. This root cause is separate from the IDENTIFIER and VALUE backtracking vulnerability because the cost occurs in RE_WS_END.search during trimming rather than token matching. The resulting CPU consumption can hold the Python GIL, exhaust workers, and stall a service without causing memory corruption or code execution. The issue is fixed in version 2.9.

Weakness

The product does not properly control the allocation and maintenance of a limited resource.

Affected Software

NameVendorStart VersionEnd Version
Red Hat OpenShift AI 3.4RedHatrhoai/odh-automl-rhel9:1791535789*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-autorag-rhel9:1791557539*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-feature-server-rhel9:1791863220*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9:1791829804*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-pipeline-runtime-minimal-cpu-py312-rhel9:1791829069*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9:1791829182*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-pipeline-runtime-pytorch-llmcompressor-cuda-py312-rhel9:1791829658*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9:1791868244*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9:1791828837*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9:1791868241*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-th06-cpu-torch210-py312-rhel9:1791874335*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-th06-cuda130-torch210-py312-rhel9:1791961113*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-th06-rocm64-torch291-py312-rhel9:1791872119*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-trustyai-nemo-guardrails-server-rhel9:1791556128*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9:1791872084*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-workbench-jupyter-minimal-cpu-py312-rhel9:1791870673*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-workbench-jupyter-minimal-cuda-py312-rhel9:1791953196*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-workbench-jupyter-minimal-rocm-py312-rhel9:1791869801*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9:1791829615*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-workbench-jupyter-pytorch-llmcompressor-cuda-py312-rhel9:1791832538*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9:1791868194*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9:1791833225*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9:1791868238*
Red Hat OpenShift AI 3.4RedHatrhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9:1791829530*

Potential Mitigations

  • Mitigation of resource exhaustion attacks requires that the target system either:

  • The first of these solutions is an issue in itself though, since it may allow attackers to prevent the use of the system by a particular valid user. If the attacker impersonates the valid user, they may be able to prevent the user from accessing the server in question.

  • The second solution is simply difficult to effectively institute – and even when properly done, it does not provide a full solution. It simply makes the attack require more resources on the part of the attacker.

References