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Advisory severityHigh7.5Red Hat Linux

High [CVE-2026-49477] Denial of Service via crafted CSS selector strings

This high-severity Red Hat Linux advisory covers CVE-2026-49477 affecting Red Hat Hardened Images, Red Hat OpenShift AI 3.4, Red Hat Quay 3.10.

Aggregated and source-linked by VulniPulse. Data sources, validation and limitations.

CVE-2026-49477 Source published Source updated

VulniPulse record published Record updated

CVE-2026-49477
Affected products & platforms
Red Hat LinuxUnclassified
Open source advisory

Summary

Soup Sieve is a CSS selector library designed to be used with Beautiful Soup 4.

Prior to 2.8.4, the CSS selector parser in soupsieve contains a regular expression vulnerable to catastrophic backtracking when processing an attribute selector with an unterminated quoted value in soupsieve/css_parser.py, allowing an attacker who can supply untrusted CSS selector strings to soupsieve.compile() or Beautiful Soup.select() /.select_one() to cause CPU exhaustion and denial of service.

This issue is fixed in version 2.8.4. A remote attacker can exploit this by supplying a small, specially crafted CSS selector string to applications that process untrusted CSS, potentially blocking worker threads and causing a complete service denial in affected Red Hat products.

Red Hat severity: Important — CVSS 7.5 (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H). Weakness: CWE-1333.

Affected Red Hat products: Red Hat Hardened Images; Red Hat OpenShift AI 3.4; Red Hat Quay 3.10; Red Hat Quay 3.12; Red Hat Quay 3.14; Red Hat Quay 3.15; Red Hat Quay 3.16; Red Hat Quay 3.17; Red Hat Quay 3.18; Red Hat Quay 3.9; Exploit Intelligence; Lightspeed Core; Migration Toolkit for Applications 8; Red Hat Ansible Automation Platform 2; Red Hat OpenShift AI (RHOAI); Red Hat OpenShift Container Platform 4; Red Hat OpenShift Virtualization 4.

Will not fix / out of support: Red Hat Ansible Automation Platform 2.

Is CVE-2026-49477 exploited?

No exploitation is reported in the sources VulniPulse tracks: CVE-2026-49477 is not in the CISA KEV catalog (checked ) and this advisory does not report exploitation. That is not proof the vulnerability cannot be exploited.

How do I fix CVE-2026-49477?

Upgrade to a fixed release named by Red Hat:

  • 2.8.4
  • python-rpds-py-main-2026.6.3-1.hum1
  • rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9:1787073866
  • rhoai/odh-pipeline-runtime-minimal-cpu-py312-rhel9:1787073936
  • rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9:1787073873
  • rhoai/odh-pipeline-runtime-pytorch-llmcompressor-cuda-py312-rhel9:1787073459
  • rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9:1787073611
  • rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9:1787073451
  • rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9:1787073451
  • rhoai/odh-th06-cpu-torch210-py312-rhel9:1787076778
  • rhoai/odh-th06-cuda130-torch210-py312-rhel9:1787077779
  • rhoai/odh-th06-rocm64-torch291-py312-rhel9:1787076481

27 more fixed releases are listed below.

Confirm against the vendor advisory before you patch.

Affected versions
  • < 2.8.4

Official advisory · high-confidence parse· fetched 6 days ago·verify at source

Fixed versions
  • 2.8.4
  • python-rpds-py-main-2026.6.3-1.hum1
  • rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9:1787073866
  • rhoai/odh-pipeline-runtime-minimal-cpu-py312-rhel9:1787073936
  • rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9:1787073873
  • rhoai/odh-pipeline-runtime-pytorch-llmcompressor-cuda-py312-rhel9:1787073459
  • rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9:1787073611
  • rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9:1787073451
  • rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9:1787073451
  • rhoai/odh-th06-cpu-torch210-py312-rhel9:1787076778
  • rhoai/odh-th06-cuda130-torch210-py312-rhel9:1787077779
  • rhoai/odh-th06-rocm64-torch291-py312-rhel9:1787076481
  • rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9:1787074331
  • rhoai/odh-workbench-jupyter-minimal-cpu-py312-rhel9:1787073913
  • rhoai/odh-workbench-jupyter-minimal-cuda-py312-rhel9:1787074078
  • rhoai/odh-workbench-jupyter-minimal-rocm-py312-rhel9:1787073929
  • rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9:1787073605
  • rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9:1787073546
  • rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9:1787073717
  • rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9:1787073713
  • rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9:1787073593
  • quay/quay-rhel8:1788561841
  • quay/quay-rhel8:1788594376
  • quay/quay-rhel8:1788593843
  • quay/quay-rhel8:1788191755
  • quay/quay-rhel9:1789563753
  • quay/quay-rhel9:1790690298
  • quay/quay-rhel9:1791265590
  • quay/quay-rhel8:1788595574
  • RHSA-2026:34119
  • RHSA-2026:60520
  • RHSA-2026:66084
  • RHSA-2026:66523
  • RHSA-2026:70267
  • RHSA-2026:63307
  • RHSA-2026:69255
  • RHSA-2026:74511
  • RHSA-2026:81110
  • RHSA-2026:65514

Official advisory · high-confidence parse· fetched 6 days ago·verify at source

Mitigation

Upgrade to a fixed release: 2.8.4, python-rpds-py-main-2026.6.3-1.hum1, rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9:1787073866, rhoai/odh-pipeline-runtime-minimal-cpu-py312-rhel9:1787073936, rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9:1787073873, rhoai/odh-pipeline-runtime-pytorch-llmcompressor-cuda-py312-rhel9:1787073459. That is the remediation for this advisory.

The vendor advisory may list interim mitigations or workarounds not captured here. Review it before change work.

Official advisory · high-confidence parse· fetched 6 days ago·verify at source

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