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CVE-2026-112400

Description

A flaw was found in Pillow. When parsing a crafted GIF image, the library fails to discard rejected frame dimensions after encountering an excessively large image exception. If an application catches this exception and continues processing the image, subsequent operations attempt to allocate memory based on the oversized dimensions. A remote attacker can exploit this issue to exhaust system memory, resulting in a Denial of Service (DoS).

Statement

Red Hat rates this vulnerability as Important because an unauthenticated remote attacker can supply a malicious graphic file that forces extensive memory allocations, leading to daemon termination or denial of service. The flaw requires consuming applications to catch decompression bomb exceptions and reuse the same image object across subsequent frame operations, allowing oversized geometry values to trigger high resource exhaustion. Exposure is largely concentrated in containerized services and image-processing pipelines that handle untrusted animation uploads directly.

Mitigation

--- CME Mitigation Guidance (2026-10-20) ---
Disclaimer: The following mitigation solutions are provided as a courtesy, pending the application of an official patch. This content was generated utilizing AI tools in conjunction with data from https://cmetaxonomy.org. Customers are advised to independently evaluate and test these temporary mitigations within their own infrastructure.

The highest-value action is to discard image objects immediately upon catching DecompressionBombError rather than continuing seek or load operations: upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate computed frame dimensions with _decompression_bomb_check before updating self._size, closing crafted GIF image with oversized frame extents. Until patched, this is a concern on applications parsing untrusted GIF images that catch DecompressionBombError exceptions and continue operating on the same image object, so avoid catching DecompressionBombError to reuse the same image instance, and ensure failed image processing operations immediately destroy or discard the affected object. As a compensating measure, monitor cgroup memory pressure via memory.events and PSI to detect anomalous memory spikes and pending OOM events, restrict process virtual address space using ulimit or prlimit (RLIMIT_AS) to bound oversized allocations, and enforce cgroups v2 memory resource limits on containers or process groups to prevent host-wide memory exhaustion. These controls limit blast radius and contain exploitation, but they do not fix the underlying retained image dimension defect — apply the upstream patch to fully remediate.

Highest-impact CME: CME-1010 cgroup Memory Pressure Monitoring (memory.events / PSI) (medium)

Common Vulnerability Scoring System (CVSS) Score Details

Info alert:Important note

CVSS scores for open source components depend on vendor-specific factors (e.g. version or build chain). Therefore, Red Hat's score and impact rating can be different from NVD and other vendors. Red Hat remains the authoritative CVE Naming Authority (CNA) source for its products and services (see Red Hat classifications).

CVSS v3 Score Breakdown

Red HatNVDcve.org
Base Score7.57.5N/A
Attack VectorNetworkNetworkN/A
Attack ComplexityLowLowN/A
Privileges RequiredNoneNoneN/A
User InteractionNoneNoneN/A
ScopeUnchangedUnchangedN/A
ConfidentialityNoneNoneN/A
Integrity ImpactNoneNoneN/A
Availability ImpactHighHighN/A

Vector

Red Hat: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

NVD: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

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