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Advisory severityHigh7.5Red Hat Linux

High [CVE-2026-59200] Denial of service via crafted PDF stream

This high-severity Red Hat Linux advisory covers CVE-2026-59200 affecting Red Hat AI Inference Server 3.3, Red Hat AI Inference Server 3.4, Red Hat Enterprise Linux AI 3.3.

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

CVE-2026-59200 Source published Source updated

VulniPulse record published Record updated

Affected products & platforms
Red Hat LinuxUnclassified
Open source advisory

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Summary

Pillow is a Python imaging library. From 5.1.0 until 12.3.0, PdfParser.

PdfStream.decode() in PIL/PdfParser.py calls zlib.decompress() with bufsize set to the PDF stream Length field without bounding the decompressed output size, allowing a crafted FlateDecode PDF stream to exhaust memory from a small file. This issue is fixed in version 12.3.0.

By providing a specially designed PDF file, the attacker could cause the application to exhaust available memory, leading to a denial of service (DoS). The impact is limited to denial of service via memory exhaustion.

A small crafted PDF input can force unbounded decompression, but this does not lead to code execution or information disclosure. 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-409.

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

Affected versions

No affected-version range was extracted from the source record. The vendor advisory is authoritative — check it before change work.

Official advisory · high-confidence parse· fetched 18 days ago·verify at source

Fixed versions
  • 12.3.0
  • rhaiis/model-opt-cuda-rhel9:1787601159
  • rhaii/vllm-spyre-rhel9:1789681201
  • rhaii/vllm-cpu-rhel9:1789681128
  • rhaii/vllm-cuda-rhel9:1789681126
  • rhaii/model-opt-cuda-rhel9:1789681126
  • rhaii/vllm-rocm-rhel9:1789681126
  • rhaii/vllm-cpu-rhel9:1790075793
  • rhaii/vllm-spyre-rhel9:1790076141
  • rhaii/vllm-cuda-rhel9:1790090131
  • rhaii/vllm-rocm-rhel9:1790109620
  • rhaii/model-opt-cuda-rhel9:1790076498
  • rhelai3/disk-image-cuda-rhel9:1788290314
  • rhelai3/bootc-aws-cuda-rhel9:1788273908
  • rhelai3/bootc-azure-cuda-rhel9:1788273909
  • rhelai3/bootc-cuda-rhel9:1788260684
  • rhelai3/bootc-gcp-cuda-rhel9:1788273977
  • rhoai/odh-llm-d-inference-scheduler-rhel9:1789662430
  • rhoai/odh-mlflow-rhel9:1789653606
  • 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
  • RHSA-2026:59518
  • RHSA-2026:69464
  • RHSA-2026:69466
  • RHSA-2026:69467
  • RHSA-2026:69468
  • RHSA-2026:69469
  • RHSA-2026:70965
  • RHSA-2026:70969
  • RHSA-2026:70979

Official advisory · high-confidence parse· fetched 18 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 18 days ago·verify at source

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