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CVE-2026-112894

HIGH 8.7

Published 2026-10-19 · Last modified 2026-10-20

Pillow is a Python imaging library. From 5.1.0 until 13.0.0, Pillow takes quadratic time to reserve PDF object identifiers when saving many frames with save_all enabled. PdfParser.next_object_id() repeatedly rebuilds and scans all previously reserved identifiers for every object. An attacker can supply a multi-frame image, including a small APNG with a large declared frame count, to an application that converts it to a multipage PDF. This can consume excessive CPU and deny service. This issue is fixed in version 13.0.0.

ELEVATED IMPACT

Severe if exploited (CVSS 8.7), but no known exploitation and low modeled probability. Patch on a normal cadence.

Exploitation likelihood

0.5%chance of exploitation in 30 days · 43rd percentile

○ In CISA KEV ○ Catalogued PoC

Impact if exploited

8.7CVSS 4.0 · HIGH

  • ConfidentialityNone
  • IntegrityNone
  • AvailabilityHigh

What an attacker needs

  • ✓Access: Reachable over the network — no local access needed
  • ✓Privileges: No account or privileges required
  • ✓User interaction: No user interaction needed
  • ✓Complexity: No special conditions — reliably repeatable
  • ✓Requirements: No special attack requirements

✓ lowers the bar for an attacker · ⚠ raises it

Proof of concept

No public PoC is currently catalogued.

Search for new PoCs

Search GitHub now — results may be empty or unverified.

Tracked sources are checked daily for recent CVEs, including PoCs published after the original disclosure. A later release appears after a tracked source lists it and a refresh succeeds.

Data snapshot:

Affected

Vendors Python Pillow

Products Pillow

Weakness (CWE)

  • CWE-407: : Inefficient Algorithmic Complexity

CVSS vector

CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

References and research data (JSON)

Packages and version ranges

Each advisory describes its own package and affected ranges. A boundary applies to that range; it is not a universal upgrade recommendation.

  • pillow PyPI

    pkg:pypi/pillow

    ECOSYSTEM range
    • Introduced version (included): 5.1.0
    • Fixed boundary (excluded): 13.0.0
    49 explicitly listed affected versions

    10.0.0, 10.0.1, 10.1.0, 10.2.0, 10.3.0, 10.4.0, 11.0.0, 11.1.0, 11.2.1, 11.3.0, 12.0.0, 12.1.0, 12.1.1, 12.2.0, 12.3.0, 5.1.0, 5.2.0, 5.3.0, 5.4.0, 5.4.0.dev0, 5.4.1, 6.0.0, 6.1.0, 6.2.0, 6.2.1, 6.2.2, 7.0.0, 7.1.0, 7.1.1, 7.1.2, 7.2.0, 8.0.0, 8.0.1, 8.1.0, 8.1.1, 8.1.2, 8.2.0, 8.3.0, 8.3.1, 8.3.2, 8.4.0, 9.0.0, 9.0.1, 9.1.0, 9.1.1, 9.2.0, 9.3.0, 9.4.0, 9.5.0

    Additional upstream package constraints
    {
      "database": {
        "source": "https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2026/10/GHSA-jg86-v3jv-hrpm/GHSA-jg86-v3jv-hrpm.json"
      }
    }
    GitHub Advisory Database · GHSA-jg86-v3jv-hrpm · Updated 2026-10-26T08:56:08.669907131Z

Vendor product assessments

Showing 32 of 94 vendor product statements; 62 omitted. Read the full vendor advisory.

  • exploit-intelligence/vulnerability-analysis-rhel9 as a component of Exploit Intelligence · known affected

    Vendor assessment for this product only.

    pkg:oci/vulnerability-analysis-rhel9@sha256:64fb01357ccdad3fde5b4448664a57967117e94418a26c6d8022fb4a7f31a4de?repository_url=registry.redhat.io/exploit-intelligence/vulnerability-analysis-rhel9

    • workaround: --- 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 validate and enforce upper bounds on image frame counts before passing untrusted files to Pillow multi-page PDF conversion with save_all enabled: 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 maintain a running maximum object ID attribute on XrefTable updated upon key insertion to resolve identifiers in constant time instead of scanning all keys with max(), closing all 2 injection vectors (crafted multi-frame image with a large number of frames, crafted small APNG image with an inflated declared frame count). Until patched, this is a concern on applications converting untrusted user-supplied multi-frame images to PDF documents using save_all=True across all platforms, so Restrict untrusted image uploads, enforce strict frame count validation before processing, or disable multi-page PDF conversion using save_all=True. As a compensating measure, Impose per-process CPU time limits using ulimit or prlimit (RLIMIT_CPU) to terminate runaway PDF conversion processes and bound CPU starvation, Configure service watchdog timers such as systemd WatchdogSec and Restart to restart processes that hang during quadratic object scanning, and Constrain cgroups v2 CPU quotas to restrict the blast radius of excessive CPU utilization during multi-frame PDF generation. These controls limit blast radius and contain exploitation, but they do not fix the underlying quadratic object identifier scanning defect — apply the upstream patch to fully remediate. Highest-impact CME: CME-1311 Input Size and Quantity Bounds Enforcement (high)
    • none available: Affected
    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • openshift-lightspeed-tech-preview/lightspeed-rag-tool-rhel9 as a component of OpenShift Lightspeed · known affected

    Vendor assessment for this product only.

    pkg:oci/lightspeed-rag-tool-rhel9@sha256:fb2ea7e901d290ab2e64cb9070690ba3a1dd0f621d27b379d1b75e0d315a803a?repository_url=registry.redhat.io/openshift-lightspeed-tech-preview/lightspeed-rag-tool-rhel9

    • workaround: --- 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 validate and enforce upper bounds on image frame counts before passing untrusted files to Pillow multi-page PDF conversion with save_all enabled: 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 maintain a running maximum object ID attribute on XrefTable updated upon key insertion to resolve identifiers in constant time instead of scanning all keys with max(), closing all 2 injection vectors (crafted multi-frame image with a large number of frames, crafted small APNG image with an inflated declared frame count). Until patched, this is a concern on applications converting untrusted user-supplied multi-frame images to PDF documents using save_all=True across all platforms, so Restrict untrusted image uploads, enforce strict frame count validation before processing, or disable multi-page PDF conversion using save_all=True. As a compensating measure, Impose per-process CPU time limits using ulimit or prlimit (RLIMIT_CPU) to terminate runaway PDF conversion processes and bound CPU starvation, Configure service watchdog timers such as systemd WatchdogSec and Restart to restart processes that hang during quadratic object scanning, and Constrain cgroups v2 CPU quotas to restrict the blast radius of excessive CPU utilization during multi-frame PDF generation. These controls limit blast radius and contain exploitation, but they do not fix the underlying quadratic object identifier scanning defect — apply the upstream patch to fully remediate. Highest-impact CME: CME-1311 Input Size and Quantity Bounds Enforcement (high)
    • none available: Affected
    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • rhaii/vllm-cpu-rhel9 as a component of Red Hat AI Inference Server · known affected

    Vendor assessment for this product only.

    pkg:oci/vllm-cpu-rhel9@sha256:f8a692451f509d11bf166288d614660cf8c15bab7494a822276bf458cfeb757a?repository_url=registry.redhat.io/rhaii/vllm-cpu-rhel9

    • workaround: --- 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 validate and enforce upper bounds on image frame counts before passing untrusted files to Pillow multi-page PDF conversion with save_all enabled: 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 maintain a running maximum object ID attribute on XrefTable updated upon key insertion to resolve identifiers in constant time instead of scanning all keys with max(), closing all 2 injection vectors (crafted multi-frame image with a large number of frames, crafted small APNG image with an inflated declared frame count). Until patched, this is a concern on applications converting untrusted user-supplied multi-frame images to PDF documents using save_all=True across all platforms, so Restrict untrusted image uploads, enforce strict frame count validation before processing, or disable multi-page PDF conversion using save_all=True. As a compensating measure, Impose per-process CPU time limits using ulimit or prlimit (RLIMIT_CPU) to terminate runaway PDF conversion processes and bound CPU starvation, Configure service watchdog timers such as systemd WatchdogSec and Restart to restart processes that hang during quadratic object scanning, and Constrain cgroups v2 CPU quotas to restrict the blast radius of excessive CPU utilization during multi-frame PDF generation. These controls limit blast radius and contain exploitation, but they do not fix the underlying quadratic object identifier scanning defect — apply the upstream patch to fully remediate. Highest-impact CME: CME-1311 Input Size and Quantity Bounds Enforcement (high)
    • none available: Affected
    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • rhaii/vllm-rocm-rhel9 as a component of Red Hat AI Inference Server · known affected

    Vendor assessment for this product only.

    pkg:oci/vllm-rocm-rhel9@sha256:7b64ac6e235a073d437c3da172c537347c7b54092c09d4ca11594b52ddbd1852?repository_url=registry.redhat.io/rhaii/vllm-rocm-rhel9

    • workaround: --- 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 validate and enforce upper bounds on image frame counts before passing untrusted files to Pillow multi-page PDF conversion with save_all enabled: 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 maintain a running maximum object ID attribute on XrefTable updated upon key insertion to resolve identifiers in constant time instead of scanning all keys with max(), closing all 2 injection vectors (crafted multi-frame image with a large number of frames, crafted small APNG image with an inflated declared frame count). Until patched, this is a concern on applications converting untrusted user-supplied multi-frame images to PDF documents using save_all=True across all platforms, so Restrict untrusted image uploads, enforce strict frame count validation before processing, or disable multi-page PDF conversion using save_all=True. As a compensating measure, Impose per-process CPU time limits using ulimit or prlimit (RLIMIT_CPU) to terminate runaway PDF conversion processes and bound CPU starvation, Configure service watchdog timers such as systemd WatchdogSec and Restart to restart processes that hang during quadratic object scanning, and Constrain cgroups v2 CPU quotas to restrict the blast radius of excessive CPU utilization during multi-frame PDF generation. These controls limit blast radius and contain exploitation, but they do not fix the underlying quadratic object identifier scanning defect — apply the upstream patch to fully remediate. Highest-impact CME: CME-1311 Input Size and Quantity Bounds Enforcement (high)
    • none available: Affected
    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • rhaiis/vllm-cuda-rhel9 as a component of Red Hat AI Inference Server · known affected

    Vendor assessment for this product only.

    pkg:oci/vllm-cuda-rhel9@sha256:73bbc4560132c4aaa9bbd608ce9560eeae7b30bcc8f014da460afa5622139372?repository_url=registry.redhat.io/rhaiis/vllm-cuda-rhel9

    • workaround: --- 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 validate and enforce upper bounds on image frame counts before passing untrusted files to Pillow multi-page PDF conversion with save_all enabled: 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 maintain a running maximum object ID attribute on XrefTable updated upon key insertion to resolve identifiers in constant time instead of scanning all keys with max(), closing all 2 injection vectors (crafted multi-frame image with a large number of frames, crafted small APNG image with an inflated declared frame count). Until patched, this is a concern on applications converting untrusted user-supplied multi-frame images to PDF documents using save_all=True across all platforms, so Restrict untrusted image uploads, enforce strict frame count validation before processing, or disable multi-page PDF conversion using save_all=True. As a compensating measure, Impose per-process CPU time limits using ulimit or prlimit (RLIMIT_CPU) to terminate runaway PDF conversion processes and bound CPU starvation, Configure service watchdog timers such as systemd WatchdogSec and Restart to restart processes that hang during quadratic object scanning, and Constrain cgroups v2 CPU quotas to restrict the blast radius of excessive CPU utilization during multi-frame PDF generation. These controls limit blast radius and contain exploitation, but they do not fix the underlying quadratic object identifier scanning defect — apply the upstream patch to fully remediate. Highest-impact CME: CME-1311 Input Size and Quantity Bounds Enforcement (high)
    • none available: Affected
    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • ansible-automation-platform-26/hub-rhel9 as a component of Red Hat Ansible Automation Platform 2 · known affected

    Vendor assessment for this product only.

    pkg:oci/hub-rhel9@sha256:a89626cb36ee12ab3e31794662d3c791e0b3d3e7e9f4fb4624c0c4c096c0d445?repository_url=registry.redhat.io/ansible-automation-platform-26/hub-rhel9

    • workaround: --- 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 validate and enforce upper bounds on image frame counts before passing untrusted files to Pillow multi-page PDF conversion with save_all enabled: 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 maintain a running maximum object ID attribute on XrefTable updated upon key insertion to resolve identifiers in constant time instead of scanning all keys with max(), closing all 2 injection vectors (crafted multi-frame image with a large number of frames, crafted small APNG image with an inflated declared frame count). Until patched, this is a concern on applications converting untrusted user-supplied multi-frame images to PDF documents using save_all=True across all platforms, so Restrict untrusted image uploads, enforce strict frame count validation before processing, or disable multi-page PDF conversion using save_all=True. As a compensating measure, Impose per-process CPU time limits using ulimit or prlimit (RLIMIT_CPU) to terminate runaway PDF conversion processes and bound CPU starvation, Configure service watchdog timers such as systemd WatchdogSec and Restart to restart processes that hang during quadratic object scanning, and Constrain cgroups v2 CPU quotas to restrict the blast radius of excessive CPU utilization during multi-frame PDF generation. These controls limit blast radius and contain exploitation, but they do not fix the underlying quadratic object identifier scanning defect — apply the upstream patch to fully remediate. Highest-impact CME: CME-1311 Input Size and Quantity Bounds Enforcement (high)
    • none available: Affected
    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • python-pillow.src as a component of Red Hat Enterprise Linux 8 · known affected

    Vendor assessment for this product only.

    pkg:rpm/redhat/[email protected]?arch=src

    • workaround: --- 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 validate and enforce upper bounds on image frame counts before passing untrusted files to Pillow multi-page PDF conversion with save_all enabled: 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 maintain a running maximum object ID attribute on XrefTable updated upon key insertion to resolve identifiers in constant time instead of scanning all keys with max(), closing all 2 injection vectors (crafted multi-frame image with a large number of frames, crafted small APNG image with an inflated declared frame count). Until patched, this is a concern on applications converting untrusted user-supplied multi-frame images to PDF documents using save_all=True across all platforms, so Restrict untrusted image uploads, enforce strict frame count validation before processing, or disable multi-page PDF conversion using save_all=True. As a compensating measure, Impose per-process CPU time limits using ulimit or prlimit (RLIMIT_CPU) to terminate runaway PDF conversion processes and bound CPU starvation, Configure service watchdog timers such as systemd WatchdogSec and Restart to restart processes that hang during quadratic object scanning, and Constrain cgroups v2 CPU quotas to restrict the blast radius of excessive CPU utilization during multi-frame PDF generation. These controls limit blast radius and contain exploitation, but they do not fix the underlying quadratic object identifier scanning defect — apply the upstream patch to fully remediate. Highest-impact CME: CME-1311 Input Size and Quantity Bounds Enforcement (high)
    • none available: Affected
    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • python3-pillow-tk as a component of Red Hat Enterprise Linux 8 · known affected

    Vendor assessment for this product only.

    pkg:rpm/redhat/python3-pillow-tk

    • workaround: --- 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 validate and enforce upper bounds on image frame counts before passing untrusted files to Pillow multi-page PDF conversion with save_all enabled: 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 maintain a running maximum object ID attribute on XrefTable updated upon key insertion to resolve identifiers in constant time instead of scanning all keys with max(), closing all 2 injection vectors (crafted multi-frame image with a large number of frames, crafted small APNG image with an inflated declared frame count). Until patched, this is a concern on applications converting untrusted user-supplied multi-frame images to PDF documents using save_all=True across all platforms, so Restrict untrusted image uploads, enforce strict frame count validation before processing, or disable multi-page PDF conversion using save_all=True. As a compensating measure, Impose per-process CPU time limits using ulimit or prlimit (RLIMIT_CPU) to terminate runaway PDF conversion processes and bound CPU starvation, Configure service watchdog timers such as systemd WatchdogSec and Restart to restart processes that hang during quadratic object scanning, and Constrain cgroups v2 CPU quotas to restrict the blast radius of excessive CPU utilization during multi-frame PDF generation. These controls limit blast radius and contain exploitation, but they do not fix the underlying quadratic object identifier scanning defect — apply the upstream patch to fully remediate. Highest-impact CME: CME-1311 Input Size and Quantity Bounds Enforcement (high)
    • none available: Affected
    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3 · known affected

    Vendor assessment for this product only.

    pkg:oci/bootc-cuda-rhel9@sha256:e0fbb896811ab54d183e23612030072b946674824bad697bf2b3f68362651662?repository_url=registry.redhat.io/rhelai3/bootc-cuda-rhel9

    • workaround: --- 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 validate and enforce upper bounds on image frame counts before passing untrusted files to Pillow multi-page PDF conversion with save_all enabled: 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 maintain a running maximum object ID attribute on XrefTable updated upon key insertion to resolve identifiers in constant time instead of scanning all keys with max(), closing all 2 injection vectors (crafted multi-frame image with a large number of frames, crafted small APNG image with an inflated declared frame count). Until patched, this is a concern on applications converting untrusted user-supplied multi-frame images to PDF documents using save_all=True across all platforms, so Restrict untrusted image uploads, enforce strict frame count validation before processing, or disable multi-page PDF conversion using save_all=True. As a compensating measure, Impose per-process CPU time limits using ulimit or prlimit (RLIMIT_CPU) to terminate runaway PDF conversion processes and bound CPU starvation, Configure service watchdog timers such as systemd WatchdogSec and Restart to restart processes that hang during quadratic object scanning, and Constrain cgroups v2 CPU quotas to restrict the blast radius of excessive CPU utilization during multi-frame PDF generation. These controls limit blast radius and contain exploitation, but they do not fix the underlying quadratic object identifier scanning defect — apply the upstream patch to fully remediate. Highest-impact CME: CME-1311 Input Size and Quantity Bounds Enforcement (high)
    • none available: Affected
    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • rhelai3/disk-image-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3 · known affected

    Vendor assessment for this product only.

    pkg:oci/disk-image-cuda-rhel9@sha256:9d807c5381e81734b6303669421b265aea1eca54a18ca577d453508ffde1770c?repository_url=registry.redhat.io/rhelai3/disk-image-cuda-rhel9

    • workaround: --- 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 validate and enforce upper bounds on image frame counts before passing untrusted files to Pillow multi-page PDF conversion with save_all enabled: 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 maintain a running maximum object ID attribute on XrefTable updated upon key insertion to resolve identifiers in constant time instead of scanning all keys with max(), closing all 2 injection vectors (crafted multi-frame image with a large number of frames, crafted small APNG image with an inflated declared frame count). Until patched, this is a concern on applications converting untrusted user-supplied multi-frame images to PDF documents using save_all=True across all platforms, so Restrict untrusted image uploads, enforce strict frame count validation before processing, or disable multi-page PDF conversion using save_all=True. As a compensating measure, Impose per-process CPU time limits using ulimit or prlimit (RLIMIT_CPU) to terminate runaway PDF conversion processes and bound CPU starvation, Configure service watchdog timers such as systemd WatchdogSec and Restart to restart processes that hang during quadratic object scanning, and Constrain cgroups v2 CPU quotas to restrict the blast radius of excessive CPU utilization during multi-frame PDF generation. These controls limit blast radius and contain exploitation, but they do not fix the underlying quadratic object identifier scanning defect — apply the upstream patch to fully remediate. Highest-impact CME: CME-1311 Input Size and Quantity Bounds Enforcement (high)
    • none available: Affected
    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • rhai/guidellm-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · known affected

    Vendor assessment for this product only.

    pkg:oci/guidellm-rhel9@sha256:1021f45f649c8ce88799bada572bfa8d2295bca8eeb811cfc1218ef2004f4f02?repository_url=registry.redhat.io/rhai/guidellm-rhel9

    • workaround: --- 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 validate and enforce upper bounds on image frame counts before passing untrusted files to Pillow multi-page PDF conversion with save_all enabled: 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 maintain a running maximum object ID attribute on XrefTable updated upon key insertion to resolve identifiers in constant time instead of scanning all keys with max(), closing all 2 injection vectors (crafted multi-frame image with a large number of frames, crafted small APNG image with an inflated declared frame count). Until patched, this is a concern on applications converting untrusted user-supplied multi-frame images to PDF documents using save_all=True across all platforms, so Restrict untrusted image uploads, enforce strict frame count validation before processing, or disable multi-page PDF conversion using save_all=True. As a compensating measure, Impose per-process CPU time limits using ulimit or prlimit (RLIMIT_CPU) to terminate runaway PDF conversion processes and bound CPU starvation, Configure service watchdog timers such as systemd WatchdogSec and Restart to restart processes that hang during quadratic object scanning, and Constrain cgroups v2 CPU quotas to restrict the blast radius of excessive CPU utilization during multi-frame PDF generation. These controls limit blast radius and contain exploitation, but they do not fix the underlying quadratic object identifier scanning defect — apply the upstream patch to fully remediate. Highest-impact CME: CME-1311 Input Size and Quantity Bounds Enforcement (high)
    • none available: Affected
    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • rhoai/odh-feature-server-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · known affected

    Vendor assessment for this product only.

    pkg:oci/odh-feature-server-rhel9@sha256:c5dd868cd66e7911969f60658d31b3714ed42f0e81b9512f89991a412bcb0fa9?repository_url=registry.redhat.io/rhoai/odh-feature-server-rhel9

    • workaround: --- 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 validate and enforce upper bounds on image frame counts before passing untrusted files to Pillow multi-page PDF conversion with save_all enabled: 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 maintain a running maximum object ID attribute on XrefTable updated upon key insertion to resolve identifiers in constant time instead of scanning all keys with max(), closing all 2 injection vectors (crafted multi-frame image with a large number of frames, crafted small APNG image with an inflated declared frame count). Until patched, this is a concern on applications converting untrusted user-supplied multi-frame images to PDF documents using save_all=True across all platforms, so Restrict untrusted image uploads, enforce strict frame count validation before processing, or disable multi-page PDF conversion using save_all=True. As a compensating measure, Impose per-process CPU time limits using ulimit or prlimit (RLIMIT_CPU) to terminate runaway PDF conversion processes and bound CPU starvation, Configure service watchdog timers such as systemd WatchdogSec and Restart to restart processes that hang during quadratic object scanning, and Constrain cgroups v2 CPU quotas to restrict the blast radius of excessive CPU utilization during multi-frame PDF generation. These controls limit blast radius and contain exploitation, but they do not fix the underlying quadratic object identifier scanning defect — apply the upstream patch to fully remediate. Highest-impact CME: CME-1311 Input Size and Quantity Bounds Enforcement (high)
    • none available: Affected
    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • rhoai/odh-kserve-router-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · known affected

    Vendor assessment for this product only.

    pkg:oci/odh-kserve-router-rhel9@sha256:0e46fd236b218fb33ffe90592f67b50d2f286356f23ecc2c4ec5ae67fa64b57a?repository_url=registry.redhat.io/rhoai/odh-kserve-router-rhel9

    • workaround: --- 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 validate and enforce upper bounds on image frame counts before passing untrusted files to Pillow multi-page PDF conversion with save_all enabled: 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 maintain a running maximum object ID attribute on XrefTable updated upon key insertion to resolve identifiers in constant time instead of scanning all keys with max(), closing all 2 injection vectors (crafted multi-frame image with a large number of frames, crafted small APNG image with an inflated declared frame count). Until patched, this is a concern on applications converting untrusted user-supplied multi-frame images to PDF documents using save_all=True across all platforms, so Restrict untrusted image uploads, enforce strict frame count validation before processing, or disable multi-page PDF conversion using save_all=True. As a compensating measure, Impose per-process CPU time limits using ulimit or prlimit (RLIMIT_CPU) to terminate runaway PDF conversion processes and bound CPU starvation, Configure service watchdog timers such as systemd WatchdogSec and Restart to restart processes that hang during quadratic object scanning, and Constrain cgroups v2 CPU quotas to restrict the blast radius of excessive CPU utilization during multi-frame PDF generation. These controls limit blast radius and contain exploitation, but they do not fix the underlying quadratic object identifier scanning defect — apply the upstream patch to fully remediate. Highest-impact CME: CME-1311 Input Size and Quantity Bounds Enforcement (high)
    • none available: Affected
    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • rhoai/odh-ogx-core-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · known affected

    Vendor assessment for this product only.

    pkg:oci/odh-ogx-core-rhel9@sha256:fba4bf80475071daa61c3b9596dd01aca08471df9ae1fe4edc6b73846c96d21b?repository_url=registry.redhat.io/rhoai/odh-ogx-core-rhel9

    • workaround: --- 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 validate and enforce upper bounds on image frame counts before passing untrusted files to Pillow multi-page PDF conversion with save_all enabled: 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 maintain a running maximum object ID attribute on XrefTable updated upon key insertion to resolve identifiers in constant time instead of scanning all keys with max(), closing all 2 injection vectors (crafted multi-frame image with a large number of frames, crafted small APNG image with an inflated declared frame count). Until patched, this is a concern on applications converting untrusted user-supplied multi-frame images to PDF documents using save_all=True across all platforms, so Restrict untrusted image uploads, enforce strict frame count validation before processing, or disable multi-page PDF conversion using save_all=True. As a compensating measure, Impose per-process CPU time limits using ulimit or prlimit (RLIMIT_CPU) to terminate runaway PDF conversion processes and bound CPU starvation, Configure service watchdog timers such as systemd WatchdogSec and Restart to restart processes that hang during quadratic object scanning, and Constrain cgroups v2 CPU quotas to restrict the blast radius of excessive CPU utilization during multi-frame PDF generation. These controls limit blast radius and contain exploitation, but they do not fix the underlying quadratic object identifier scanning defect — apply the upstream patch to fully remediate. Highest-impact CME: CME-1311 Input Size and Quantity Bounds Enforcement (high)
    • none available: Affected
    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • rhoai/odh-pipeline-runtime-pytorch-llmcompressor-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · known affected

    Vendor assessment for this product only.

    pkg:oci/odh-pipeline-runtime-pytorch-llmcompressor-cuda-py312-rhel9@sha256:22e6e780ac865b8b30089d1a2a9dcd864191f9c46c8822f2df6002a2a10694a8?repository_url=registry.redhat.io/rhoai/odh-pipeline-runtime-pytorch-llmcompressor-cuda-py312-rhel9

    • workaround: --- 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 validate and enforce upper bounds on image frame counts before passing untrusted files to Pillow multi-page PDF conversion with save_all enabled: 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 maintain a running maximum object ID attribute on XrefTable updated upon key insertion to resolve identifiers in constant time instead of scanning all keys with max(), closing all 2 injection vectors (crafted multi-frame image with a large number of frames, crafted small APNG image with an inflated declared frame count). Until patched, this is a concern on applications converting untrusted user-supplied multi-frame images to PDF documents using save_all=True across all platforms, so Restrict untrusted image uploads, enforce strict frame count validation before processing, or disable multi-page PDF conversion using save_all=True. As a compensating measure, Impose per-process CPU time limits using ulimit or prlimit (RLIMIT_CPU) to terminate runaway PDF conversion processes and bound CPU starvation, Configure service watchdog timers such as systemd WatchdogSec and Restart to restart processes that hang during quadratic object scanning, and Constrain cgroups v2 CPU quotas to restrict the blast radius of excessive CPU utilization during multi-frame PDF generation. These controls limit blast radius and contain exploitation, but they do not fix the underlying quadratic object identifier scanning defect — apply the upstream patch to fully remediate. Highest-impact CME: CME-1311 Input Size and Quantity Bounds Enforcement (high)
    • none available: Affected
    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • rhoai/odh-th-torch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · known affected

    Vendor assessment for this product only.

    pkg:oci/odh-th-torch-cuda-py312-rhel9@sha256:efd7b3607b699092c68359d20ef0d0043114191a097637667c0d2cf78fbea702?repository_url=registry.redhat.io/rhoai/odh-th-torch-cuda-py312-rhel9

    • workaround: --- 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 validate and enforce upper bounds on image frame counts before passing untrusted files to Pillow multi-page PDF conversion with save_all enabled: 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 maintain a running maximum object ID attribute on XrefTable updated upon key insertion to resolve identifiers in constant time instead of scanning all keys with max(), closing all 2 injection vectors (crafted multi-frame image with a large number of frames, crafted small APNG image with an inflated declared frame count). Until patched, this is a concern on applications converting untrusted user-supplied multi-frame images to PDF documents using save_all=True across all platforms, so Restrict untrusted image uploads, enforce strict frame count validation before processing, or disable multi-page PDF conversion using save_all=True. As a compensating measure, Impose per-process CPU time limits using ulimit or prlimit (RLIMIT_CPU) to terminate runaway PDF conversion processes and bound CPU starvation, Configure service watchdog timers such as systemd WatchdogSec and Restart to restart processes that hang during quadratic object scanning, and Constrain cgroups v2 CPU quotas to restrict the blast radius of excessive CPU utilization during multi-frame PDF generation. These controls limit blast radius and contain exploitation, but they do not fix the underlying quadratic object identifier scanning defect — apply the upstream patch to fully remediate. Highest-impact CME: CME-1311 Input Size and Quantity Bounds Enforcement (high)
    • none available: Affected
    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • rhoai/odh-th06-rocm64-torch291-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · known affected

    Vendor assessment for this product only.

    pkg:oci/odh-th06-rocm64-torch291-py312-rhel9@sha256:b2a253f3dc063a8e1cee441640cce13fcf04918ce453be8f5d488301b1458a91?repository_url=registry.redhat.io/rhoai/odh-th06-rocm64-torch291-py312-rhel9

    • workaround: --- 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 validate and enforce upper bounds on image frame counts before passing untrusted files to Pillow multi-page PDF conversion with save_all enabled: 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 maintain a running maximum object ID attribute on XrefTable updated upon key insertion to resolve identifiers in constant time instead of scanning all keys with max(), closing all 2 injection vectors (crafted multi-frame image with a large number of frames, crafted small APNG image with an inflated declared frame count). Until patched, this is a concern on applications converting untrusted user-supplied multi-frame images to PDF documents using save_all=True across all platforms, so Restrict untrusted image uploads, enforce strict frame count validation before processing, or disable multi-page PDF conversion using save_all=True. As a compensating measure, Impose per-process CPU time limits using ulimit or prlimit (RLIMIT_CPU) to terminate runaway PDF conversion processes and bound CPU starvation, Configure service watchdog timers such as systemd WatchdogSec and Restart to restart processes that hang during quadratic object scanning, and Constrain cgroups v2 CPU quotas to restrict the blast radius of excessive CPU utilization during multi-frame PDF generation. These controls limit blast radius and contain exploitation, but they do not fix the underlying quadratic object identifier scanning defect — apply the upstream patch to fully remediate. Highest-impact CME: CME-1311 Input Size and Quantity Bounds Enforcement (high)
    • none available: Affected
    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • rhoai/odh-trustyai-nemo-guardrails-server-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · known affected

    Vendor assessment for this product only.

    pkg:oci/odh-trustyai-nemo-guardrails-server-rhel9@sha256:c10ff17d1912fe7a7b15b05923cefac72b355bbfb91b19f82c1d179596a7775a?repository_url=registry.redhat.io/rhoai/odh-trustyai-nemo-guardrails-server-rhel9

    • workaround: --- 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 validate and enforce upper bounds on image frame counts before passing untrusted files to Pillow multi-page PDF conversion with save_all enabled: 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 maintain a running maximum object ID attribute on XrefTable updated upon key insertion to resolve identifiers in constant time instead of scanning all keys with max(), closing all 2 injection vectors (crafted multi-frame image with a large number of frames, crafted small APNG image with an inflated declared frame count). Until patched, this is a concern on applications converting untrusted user-supplied multi-frame images to PDF documents using save_all=True across all platforms, so Restrict untrusted image uploads, enforce strict frame count validation before processing, or disable multi-page PDF conversion using save_all=True. As a compensating measure, Impose per-process CPU time limits using ulimit or prlimit (RLIMIT_CPU) to terminate runaway PDF conversion processes and bound CPU starvation, Configure service watchdog timers such as systemd WatchdogSec and Restart to restart processes that hang during quadratic object scanning, and Constrain cgroups v2 CPU quotas to restrict the blast radius of excessive CPU utilization during multi-frame PDF generation. These controls limit blast radius and contain exploitation, but they do not fix the underlying quadratic object identifier scanning defect — apply the upstream patch to fully remediate. Highest-impact CME: CME-1311 Input Size and Quantity Bounds Enforcement (high)
    • none available: Affected
    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • rhoai/odh-workbench-jupyter-pytorch-llmcompressor-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · known affected

    Vendor assessment for this product only.

    pkg:oci/odh-workbench-jupyter-pytorch-llmcompressor-cuda-py312-rhel9@sha256:af7c11030f155c3d07465e65ed7aff32861e3893e838d9d744e5bb3700f865dd?repository_url=registry.redhat.io/rhoai/odh-workbench-jupyter-pytorch-llmcompressor-cuda-py312-rhel9

    • workaround: --- 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 validate and enforce upper bounds on image frame counts before passing untrusted files to Pillow multi-page PDF conversion with save_all enabled: 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 maintain a running maximum object ID attribute on XrefTable updated upon key insertion to resolve identifiers in constant time instead of scanning all keys with max(), closing all 2 injection vectors (crafted multi-frame image with a large number of frames, crafted small APNG image with an inflated declared frame count). Until patched, this is a concern on applications converting untrusted user-supplied multi-frame images to PDF documents using save_all=True across all platforms, so Restrict untrusted image uploads, enforce strict frame count validation before processing, or disable multi-page PDF conversion using save_all=True. As a compensating measure, Impose per-process CPU time limits using ulimit or prlimit (RLIMIT_CPU) to terminate runaway PDF conversion processes and bound CPU starvation, Configure service watchdog timers such as systemd WatchdogSec and Restart to restart processes that hang during quadratic object scanning, and Constrain cgroups v2 CPU quotas to restrict the blast radius of excessive CPU utilization during multi-frame PDF generation. These controls limit blast radius and contain exploitation, but they do not fix the underlying quadratic object identifier scanning defect — apply the upstream patch to fully remediate. Highest-impact CME: CME-1311 Input Size and Quantity Bounds Enforcement (high)
    • none available: Affected
    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · known affected

    Vendor assessment for this product only.

    pkg:oci/odh-workbench-jupyter-trustyai-cpu-py312-rhel9@sha256:90da115e64c80fbf57802442848ff8eee18d8c38e6e30edfdb374bb94dd84735?repository_url=registry.redhat.io/rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9

    • workaround: --- 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 validate and enforce upper bounds on image frame counts before passing untrusted files to Pillow multi-page PDF conversion with save_all enabled: 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 maintain a running maximum object ID attribute on XrefTable updated upon key insertion to resolve identifiers in constant time instead of scanning all keys with max(), closing all 2 injection vectors (crafted multi-frame image with a large number of frames, crafted small APNG image with an inflated declared frame count). Until patched, this is a concern on applications converting untrusted user-supplied multi-frame images to PDF documents using save_all=True across all platforms, so Restrict untrusted image uploads, enforce strict frame count validation before processing, or disable multi-page PDF conversion using save_all=True. As a compensating measure, Impose per-process CPU time limits using ulimit or prlimit (RLIMIT_CPU) to terminate runaway PDF conversion processes and bound CPU starvation, Configure service watchdog timers such as systemd WatchdogSec and Restart to restart processes that hang during quadratic object scanning, and Constrain cgroups v2 CPU quotas to restrict the blast radius of excessive CPU utilization during multi-frame PDF generation. These controls limit blast radius and contain exploitation, but they do not fix the underlying quadratic object identifier scanning defect — apply the upstream patch to fully remediate. Highest-impact CME: CME-1311 Input Size and Quantity Bounds Enforcement (high)
    • none available: Affected
    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • python3.12-pillow.src as a component of Red Hat Satellite 6 · known affected

    Vendor assessment for this product only.

    pkg:rpm/redhat/[email protected]?arch=src

    • workaround: --- 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 validate and enforce upper bounds on image frame counts before passing untrusted files to Pillow multi-page PDF conversion with save_all enabled: 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 maintain a running maximum object ID attribute on XrefTable updated upon key insertion to resolve identifiers in constant time instead of scanning all keys with max(), closing all 2 injection vectors (crafted multi-frame image with a large number of frames, crafted small APNG image with an inflated declared frame count). Until patched, this is a concern on applications converting untrusted user-supplied multi-frame images to PDF documents using save_all=True across all platforms, so Restrict untrusted image uploads, enforce strict frame count validation before processing, or disable multi-page PDF conversion using save_all=True. As a compensating measure, Impose per-process CPU time limits using ulimit or prlimit (RLIMIT_CPU) to terminate runaway PDF conversion processes and bound CPU starvation, Configure service watchdog timers such as systemd WatchdogSec and Restart to restart processes that hang during quadratic object scanning, and Constrain cgroups v2 CPU quotas to restrict the blast radius of excessive CPU utilization during multi-frame PDF generation. These controls limit blast radius and contain exploitation, but they do not fix the underlying quadratic object identifier scanning defect — apply the upstream patch to fully remediate. Highest-impact CME: CME-1311 Input Size and Quantity Bounds Enforcement (high)
    • none available: Affected
    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • rhaiis/vllm-cpu-rhel9 as a component of Red Hat AI Inference Server · known not affected

    Vendor assessment for this product only.

    Reason: vulnerable code not present

    pkg:oci/vllm-cpu-rhel9@sha256:fb7791bbfea99e9f81529fe8cc1e7c834ca470585c27590e3d0a6834167cd436?repository_url=registry.redhat.io/rhaiis/vllm-cpu-rhel9

    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • rhaiis/vllm-neuron-rhel9 as a component of Red Hat AI Inference Server · known not affected

    Vendor assessment for this product only.

    Reason: vulnerable code not present

    pkg:oci/vllm-neuron-rhel9@sha256:8ba72cec5d79b1a751eb09774c81fd6181b43ec69a2e5116982661b34366874d?repository_url=registry.redhat.io/rhaiis/vllm-neuron-rhel9

    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • ansible-automation-platform-25/lightspeed-chatbot-rhel8 as a component of Red Hat Ansible Automation Platform 2 · known not affected

    Vendor assessment for this product only.

    Reason: vulnerable code not present

    pkg:oci/lightspeed-chatbot-rhel8@sha256:3e61238b7400447dfd7999d053e7f701d7c84d62e4a0ef29950c39f3843fb467?repository_url=registry.redhat.io/ansible-automation-platform-25/lightspeed-chatbot-rhel8

    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • ansible-automation-platform/automation-dashboard-rhel9 as a component of Red Hat Ansible Automation Platform 2 · known not affected

    Vendor assessment for this product only.

    Reason: vulnerable code not present

    pkg:oci/automation-dashboard-rhel9@sha256:3971cc95bbedd16996776c4aadfaeac576ef3b0ad212825a4035fb40849b2bc4?repository_url=registry.redhat.io/ansible-automation-platform/automation-dashboard-rhel9

    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • python-pillow.src as a component of Red Hat Ansible Automation Platform 2 · known not affected

    Vendor assessment for this product only.

    Reason: vulnerable code not in execute path

    pkg:rpm/redhat/[email protected]?arch=src

    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • python3.11-pillow.src as a component of Red Hat Ansible Automation Platform 2 · known not affected

    Vendor assessment for this product only.

    Reason: vulnerable code not in execute path

    pkg:rpm/redhat/[email protected]?arch=src

    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • python3x-pillow.src as a component of Red Hat Ansible Automation Platform 2 · known not affected

    Vendor assessment for this product only.

    Reason: vulnerable code not in execute path

    pkg:rpm/redhat/[email protected]?arch=src

    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • rhoai/odh-mlflow-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · known not affected

    Vendor assessment for this product only.

    Reason: vulnerable code not in execute path

    pkg:oci/odh-mlflow-rhel9@sha256:26ac33d2d07f9d51df725604ca695c98597f9bf428f6038bb1d74f9405e8db2d?repository_url=registry.redhat.io/rhoai/odh-mlflow-rhel9

    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • rhoai/odh-th06-cpu-torch291-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · known not affected

    Vendor assessment for this product only.

    Reason: component not present

    pkg:oci/odh-th06-cpu-torch291-py312-rhel9@sha256:f41414d319c2af4a36ff991b4905dd17aaeec2db0ca0af4dd5d76501b28bbb15?repository_url=registry.redhat.io/rhoai/odh-th06-cpu-torch291-py312-rhel9

    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • rhoai/odh-th06-cuda130-torch291-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · known not affected

    Vendor assessment for this product only.

    Reason: component not present

    pkg:oci/odh-th06-cuda130-torch291-py312-rhel9@sha256:4a92ec3c409a7c6ef662a2fe902e8bfff42392385f668e20fc4825d03bc838cd?repository_url=registry.redhat.io/rhoai/odh-th06-cuda130-torch291-py312-rhel9

    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00
  • rhoai/odh-vllm-gaudi-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · known not affected

    Vendor assessment for this product only.

    Reason: vulnerable code not present

    pkg:oci/odh-vllm-gaudi-rhel9@sha256:87eec3862eb6ddef445f89dcf6fd89add7ef202ea7c563b1ee7347537fb3e250?repository_url=registry.redhat.io/rhoai/odh-vllm-gaudi-rhel9

    Red Hat · CVE-2026-112894 · Updated 2026-10-23T10:50:36+00:00

All CVSS metrics

  • HIGH 8.7 v4.0 · CNA Primary
    CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N
  • HIGH 8.7 v4.0 · NVD Secondary
    CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X

References

Exploit-tagged references (not proof of a PoC)

Advisories

Technical & other

Sources: NVD · CVE.org · EPSS