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High7.5Red Hat Linux

High [CVE-2026-59199] Denial of Service via out-of-bounds write in image processing

This high-severity Red Hat Linux advisory covers CVE-2026-59199 affecting Red Hat AI Inference Server 3.3, Red Hat OpenShift AI 3.4, Red Hat Quay 3.12.

CVE-2026-59199 Published Jul 14, 2026Updated by vendor Jul 14, 2026
Affected products & platforms
Red Hat LinuxUnclassified
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Summary

Pillow is a Python imaging library. Prior to 12.3.0, Pillow public image coordinate APIs can trigger a native heap out-of-bounds write when given coordinates near the signed 32-bit integer limits in Image.paste(), Image.crop(), or Image.alpha_composite().

This issue is fixed in version 12.3.0. A remote attacker could exploit a vulnerability in the library's image processing functions, specifically when handling image coordinates near certain limits.

This flaw, a native heap out-of-bounds write, could lead to a denial of service (DoS), making the affected system or application unavailable. While the underlying issue is a heap out-of-bounds write, it does not provide a controlled write primitive exploitable for code execution 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-190.

Affected Red Hat products: Red Hat AI Inference Server 3.3; Red Hat OpenShift AI 3.4; Red Hat Quay 3.1; Red Hat Quay 3.12; Red Hat Quay 3.15; Red Hat Quay 3.9; Lightspeed Core; OpenShift Lightspeed; Red Hat AI Inference Server; Red Hat Enterprise Linux AI (RHEL AI) 3; Red Hat OpenShift AI (RHOAI); Red Hat Quay 3.

Under investigation: Exploit Intelligence; Red Hat Ansible Automation Platform 2; Red Hat Enterprise Linux 7; Red Hat Enterprise Linux 8; Red Hat Satellite 6.

Affected versions
  • < 12.3.0

Official advisory · high-confidence parse· fetched 5 days ago·verify at source

Fixed versions
  • 12.3.0
  • rhaiis/model-opt-cuda-rhel9:1787601159
  • rhoai/odh-automl-rhel9:1786612415
  • rhoai/odh-autorag-rhel9:1786612637
  • rhoai/odh-llm-d-kv-cache-rhel9:1787169432
  • rhoai/odh-mlflow-rhel9:1787226790
  • rhoai/odh-openvino-model-server-rhel9:1787303251
  • rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9:1787073866
  • 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-training-cuda128-torch29-py312-rhel9:1786611803
  • rhoai/odh-training-rocm64-torch29-py312-rhel9:1786611435
  • rhoai/odh-trustyai-garak-lls-provider-dsp-rhel9:1786613209
  • rhoai/odh-workbench-codeserver-datascience-cpu-py312-rhel9:1787121387
  • rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9:1787074331
  • 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-rhel8:1786395065
  • quay/quay-rhel8:1786170635
  • quay/quay-rhel8:1785261506
  • quay/quay-rhel8:1785950004
  • RHSA-2026:59518
  • RHSA-2026:60520
  • RHSA-2026:53520
  • RHSA-2026:52968
  • RHSA-2026:48933
  • RHSA-2026:50931

Official advisory · high-confidence parse· fetched 5 days ago·verify at source

Mitigation checklist

Recommended fix / mitigation
  • Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base, or stability.

Official advisory · high-confidence parse· fetched 5 days ago·verify at source

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