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as a component of Exploit Intelligence","status":"known_affected","remediations":[{"category":"workaround","details":"--- CME Mitigation Guidance (2026-10-20) ---\nDisclaimer: 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.\n\nThe highest-value action is to validate all input image bands to reject 4-byte pixel sizes and 32-bit storage modes prior to invoking Image.merge(): upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate all input bands and reject any band with a 4-byte pixel size or non-single band configuration with a mode error, closing all 2 injection vectors (crafted IPTC image file parsed during standard open and load operations, direct invocation of Image.merge() with a 32-bit image band). Until patched, this is a concern on applications using Pillow to process untrusted image files or calling Image.merge() on untrusted image bands, so restrict image ingestion pipelines from processing untrusted IPTC files or passing unvalidated 32-bit single-band images into Image.merge(). As a compensating measure, enforce an explicit allowlist of permitted image modes and band configurations before invoking Image.merge() to prevent processing unsupported 32-bit image bands. These controls limit blast radius and contain exploitation, but they do not fix the underlying null pointer dereference defect — apply the upstream patch to fully remediate.\n\nHighest-impact CME: CME-1315 Allowlist-Preferred Input Validation (Deny-by-Default Filtering) (medium)"},{"category":"none_available","details":"Affected"}],"purl":"pkg:oci/vulnerability-analysis-rhel9@sha256:64fb01357ccdad3fde5b4448664a57967117e94418a26c6d8022fb4a7f31a4de?repository_url=registry.redhat.io/exploit-intelligence/vulnerability-analysis-rhel9","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"openshift_lightspeed:openshift-lightspeed-tech-preview/lightspeed-rag-tool-rhel9","product":"openshift-lightspeed-tech-preview/lightspeed-rag-tool-rhel9 as a component of OpenShift Lightspeed","status":"known_affected","remediations":[{"category":"workaround","details":"--- CME Mitigation Guidance (2026-10-20) ---\nDisclaimer: 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.\n\nThe highest-value action is to validate all input image bands to reject 4-byte pixel sizes and 32-bit storage modes prior to invoking Image.merge(): upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate all input bands and reject any band with a 4-byte pixel size or non-single band configuration with a mode error, closing all 2 injection vectors (crafted IPTC image file parsed during standard open and load operations, direct invocation of Image.merge() with a 32-bit image band). Until patched, this is a concern on applications using Pillow to process untrusted image files or calling Image.merge() on untrusted image bands, so restrict image ingestion pipelines from processing untrusted IPTC files or passing unvalidated 32-bit single-band images into Image.merge(). As a compensating measure, enforce an explicit allowlist of permitted image modes and band configurations before invoking Image.merge() to prevent processing unsupported 32-bit image bands. These controls limit blast radius and contain exploitation, but they do not fix the underlying null pointer dereference defect — apply the upstream patch to fully remediate.\n\nHighest-impact CME: CME-1315 Allowlist-Preferred Input Validation (Deny-by-Default Filtering) (medium)"},{"category":"none_available","details":"Affected"}],"purl":"pkg:oci/lightspeed-rag-tool-rhel9@sha256:fb2ea7e901d290ab2e64cb9070690ba3a1dd0f621d27b379d1b75e0d315a803a?repository_url=registry.redhat.io/openshift-lightspeed-tech-preview/lightspeed-rag-tool-rhel9","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_ai_inference_server:rhaii/vllm-cpu-rhel9","product":"rhaii/vllm-cpu-rhel9 as a component of Red Hat AI Inference Server","status":"known_affected","remediations":[{"category":"workaround","details":"--- CME Mitigation Guidance (2026-10-20) ---\nDisclaimer: 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.\n\nThe highest-value action is to validate all input image bands to reject 4-byte pixel sizes and 32-bit storage modes prior to invoking Image.merge(): upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate all input bands and reject any band with a 4-byte pixel size or non-single band configuration with a mode error, closing all 2 injection vectors (crafted IPTC image file parsed during standard open and load operations, direct invocation of Image.merge() with a 32-bit image band). Until patched, this is a concern on applications using Pillow to process untrusted image files or calling Image.merge() on untrusted image bands, so restrict image ingestion pipelines from processing untrusted IPTC files or passing unvalidated 32-bit single-band images into Image.merge(). As a compensating measure, enforce an explicit allowlist of permitted image modes and band configurations before invoking Image.merge() to prevent processing unsupported 32-bit image bands. These controls limit blast radius and contain exploitation, but they do not fix the underlying null pointer dereference defect — apply the upstream patch to fully remediate.\n\nHighest-impact CME: CME-1315 Allowlist-Preferred Input Validation (Deny-by-Default Filtering) (medium)"},{"category":"none_available","details":"Affected"}],"purl":"pkg:oci/vllm-cpu-rhel9@sha256:f8a692451f509d11bf166288d614660cf8c15bab7494a822276bf458cfeb757a?repository_url=registry.redhat.io/rhaii/vllm-cpu-rhel9","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_ai_inference_server:rhaii/vllm-rocm-rhel9","product":"rhaii/vllm-rocm-rhel9 as a component of Red Hat AI Inference Server","status":"known_affected","remediations":[{"category":"workaround","details":"--- CME Mitigation Guidance (2026-10-20) ---\nDisclaimer: 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.\n\nThe highest-value action is to validate all input image bands to reject 4-byte pixel sizes and 32-bit storage modes prior to invoking Image.merge(): upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate all input bands and reject any band with a 4-byte pixel size or non-single band configuration with a mode error, closing all 2 injection vectors (crafted IPTC image file parsed during standard open and load operations, direct invocation of Image.merge() with a 32-bit image band). Until patched, this is a concern on applications using Pillow to process untrusted image files or calling Image.merge() on untrusted image bands, so restrict image ingestion pipelines from processing untrusted IPTC files or passing unvalidated 32-bit single-band images into Image.merge(). As a compensating measure, enforce an explicit allowlist of permitted image modes and band configurations before invoking Image.merge() to prevent processing unsupported 32-bit image bands. These controls limit blast radius and contain exploitation, but they do not fix the underlying null pointer dereference defect — apply the upstream patch to fully remediate.\n\nHighest-impact CME: CME-1315 Allowlist-Preferred Input Validation (Deny-by-Default Filtering) (medium)"},{"category":"none_available","details":"Affected"}],"purl":"pkg:oci/vllm-rocm-rhel9@sha256:7b64ac6e235a073d437c3da172c537347c7b54092c09d4ca11594b52ddbd1852?repository_url=registry.redhat.io/rhaii/vllm-rocm-rhel9","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_ai_inference_server:rhaiis/vllm-cuda-rhel9","product":"rhaiis/vllm-cuda-rhel9 as a component of Red Hat AI Inference Server","status":"known_affected","remediations":[{"category":"workaround","details":"--- CME Mitigation Guidance (2026-10-20) ---\nDisclaimer: 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.\n\nThe highest-value action is to validate all input image bands to reject 4-byte pixel sizes and 32-bit storage modes prior to invoking Image.merge(): upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate all input bands and reject any band with a 4-byte pixel size or non-single band configuration with a mode error, closing all 2 injection vectors (crafted IPTC image file parsed during standard open and load operations, direct invocation of Image.merge() with a 32-bit image band). Until patched, this is a concern on applications using Pillow to process untrusted image files or calling Image.merge() on untrusted image bands, so restrict image ingestion pipelines from processing untrusted IPTC files or passing unvalidated 32-bit single-band images into Image.merge(). As a compensating measure, enforce an explicit allowlist of permitted image modes and band configurations before invoking Image.merge() to prevent processing unsupported 32-bit image bands. These controls limit blast radius and contain exploitation, but they do not fix the underlying null pointer dereference defect — apply the upstream patch to fully remediate.\n\nHighest-impact CME: CME-1315 Allowlist-Preferred Input Validation (Deny-by-Default Filtering) (medium)"},{"category":"none_available","details":"Affected"}],"purl":"pkg:oci/vllm-cuda-rhel9@sha256:73bbc4560132c4aaa9bbd608ce9560eeae7b30bcc8f014da460afa5622139372?repository_url=registry.redhat.io/rhaiis/vllm-cuda-rhel9","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_ansible_automation_platform_2:ansible-automation-platform-26/hub-rhel9","product":"ansible-automation-platform-26/hub-rhel9 as a component of Red Hat Ansible Automation Platform 2","status":"known_affected","remediations":[{"category":"workaround","details":"--- CME Mitigation Guidance (2026-10-20) ---\nDisclaimer: 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.\n\nThe highest-value action is to validate all input image bands to reject 4-byte pixel sizes and 32-bit storage modes prior to invoking Image.merge(): upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate all input bands and reject any band with a 4-byte pixel size or non-single band configuration with a mode error, closing all 2 injection vectors (crafted IPTC image file parsed during standard open and load operations, direct invocation of Image.merge() with a 32-bit image band). Until patched, this is a concern on applications using Pillow to process untrusted image files or calling Image.merge() on untrusted image bands, so restrict image ingestion pipelines from processing untrusted IPTC files or passing unvalidated 32-bit single-band images into Image.merge(). As a compensating measure, enforce an explicit allowlist of permitted image modes and band configurations before invoking Image.merge() to prevent processing unsupported 32-bit image bands. These controls limit blast radius and contain exploitation, but they do not fix the underlying null pointer dereference defect — apply the upstream patch to fully remediate.\n\nHighest-impact CME: CME-1315 Allowlist-Preferred Input Validation (Deny-by-Default Filtering) (medium)"},{"category":"none_available","details":"Affected"}],"purl":"pkg:oci/hub-rhel9@sha256:a89626cb36ee12ab3e31794662d3c791e0b3d3e7e9f4fb4624c0c4c096c0d445?repository_url=registry.redhat.io/ansible-automation-platform-26/hub-rhel9","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_ansible_automation_platform_2:python3.12-pillow.src","product":"python3.12-pillow.src as a component of Red Hat Ansible Automation Platform 2","status":"known_affected","remediations":[{"category":"workaround","details":"--- CME Mitigation Guidance (2026-10-20) ---\nDisclaimer: 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.\n\nThe highest-value action is to validate all input image bands to reject 4-byte pixel sizes and 32-bit storage modes prior to invoking Image.merge(): upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate all input bands and reject any band with a 4-byte pixel size or non-single band configuration with a mode error, closing all 2 injection vectors (crafted IPTC image file parsed during standard open and load operations, direct invocation of Image.merge() with a 32-bit image band). Until patched, this is a concern on applications using Pillow to process untrusted image files or calling Image.merge() on untrusted image bands, so restrict image ingestion pipelines from processing untrusted IPTC files or passing unvalidated 32-bit single-band images into Image.merge(). As a compensating measure, enforce an explicit allowlist of permitted image modes and band configurations before invoking Image.merge() to prevent processing unsupported 32-bit image bands. These controls limit blast radius and contain exploitation, but they do not fix the underlying null pointer dereference defect — apply the upstream patch to fully remediate.\n\nHighest-impact CME: CME-1315 Allowlist-Preferred Input Validation (Deny-by-Default Filtering) (medium)"},{"category":"none_available","details":"Affected"}],"purl":"pkg:rpm/redhat/python3.12-pillow@12.3.0-1.el9ap?arch=src","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_enterprise_linux_8:python3-pillow-doc","product":"python3-pillow-doc as a component of Red Hat Enterprise Linux 8","status":"known_affected","remediations":[{"category":"workaround","details":"--- CME Mitigation Guidance (2026-10-20) ---\nDisclaimer: 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.\n\nThe highest-value action is to validate all input image bands to reject 4-byte pixel sizes and 32-bit storage modes prior to invoking Image.merge(): upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate all input bands and reject any band with a 4-byte pixel size or non-single band configuration with a mode error, closing all 2 injection vectors (crafted IPTC image file parsed during standard open and load operations, direct invocation of Image.merge() with a 32-bit image band). Until patched, this is a concern on applications using Pillow to process untrusted image files or calling Image.merge() on untrusted image bands, so restrict image ingestion pipelines from processing untrusted IPTC files or passing unvalidated 32-bit single-band images into Image.merge(). As a compensating measure, enforce an explicit allowlist of permitted image modes and band configurations before invoking Image.merge() to prevent processing unsupported 32-bit image bands. These controls limit blast radius and contain exploitation, but they do not fix the underlying null pointer dereference defect — apply the upstream patch to fully remediate.\n\nHighest-impact CME: CME-1315 Allowlist-Preferred Input Validation (Deny-by-Default Filtering) (medium)"},{"category":"none_available","details":"Affected"}],"purl":"pkg:rpm/redhat/python3-pillow-doc","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_enterprise_linux_ai_(rhel_ai)_3:rhelai3/bootc-azure-rocm-rhel9","product":"rhelai3/bootc-azure-rocm-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3","status":"known_affected","remediations":[{"category":"workaround","details":"--- CME Mitigation Guidance (2026-10-20) ---\nDisclaimer: 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.\n\nThe highest-value action is to validate all input image bands to reject 4-byte pixel sizes and 32-bit storage modes prior to invoking Image.merge(): upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate all input bands and reject any band with a 4-byte pixel size or non-single band configuration with a mode error, closing all 2 injection vectors (crafted IPTC image file parsed during standard open and load operations, direct invocation of Image.merge() with a 32-bit image band). Until patched, this is a concern on applications using Pillow to process untrusted image files or calling Image.merge() on untrusted image bands, so restrict image ingestion pipelines from processing untrusted IPTC files or passing unvalidated 32-bit single-band images into Image.merge(). As a compensating measure, enforce an explicit allowlist of permitted image modes and band configurations before invoking Image.merge() to prevent processing unsupported 32-bit image bands. These controls limit blast radius and contain exploitation, but they do not fix the underlying null pointer dereference defect — apply the upstream patch to fully remediate.\n\nHighest-impact CME: CME-1315 Allowlist-Preferred Input Validation (Deny-by-Default Filtering) (medium)"},{"category":"none_available","details":"Affected"}],"purl":"pkg:oci/bootc-azure-rocm-rhel9@sha256:87723c21f48eb371968e2d68346953f2a03a3cf643a967801b84696ee3e1f1e8?repository_url=registry.redhat.io/rhelai3/bootc-azure-rocm-rhel9","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_enterprise_linux_ai_(rhel_ai)_3:rhelai3/bootc-rocm-rhel9","product":"rhelai3/bootc-rocm-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3","status":"known_affected","remediations":[{"category":"workaround","details":"--- CME Mitigation Guidance (2026-10-20) ---\nDisclaimer: 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.\n\nThe highest-value action is to validate all input image bands to reject 4-byte pixel sizes and 32-bit storage modes prior to invoking Image.merge(): upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate all input bands and reject any band with a 4-byte pixel size or non-single band configuration with a mode error, closing all 2 injection vectors (crafted IPTC image file parsed during standard open and load operations, direct invocation of Image.merge() with a 32-bit image band). Until patched, this is a concern on applications using Pillow to process untrusted image files or calling Image.merge() on untrusted image bands, so restrict image ingestion pipelines from processing untrusted IPTC files or passing unvalidated 32-bit single-band images into Image.merge(). As a compensating measure, enforce an explicit allowlist of permitted image modes and band configurations before invoking Image.merge() to prevent processing unsupported 32-bit image bands. These controls limit blast radius and contain exploitation, but they do not fix the underlying null pointer dereference defect — apply the upstream patch to fully remediate.\n\nHighest-impact CME: CME-1315 Allowlist-Preferred Input Validation (Deny-by-Default Filtering) (medium)"},{"category":"none_available","details":"Affected"}],"purl":"pkg:oci/bootc-rocm-rhel9@sha256:8fe5203e86917e5f829bd64b831cad31536d23a213b4bfe31e652577ad0faf2e?repository_url=registry.redhat.io/rhelai3/bootc-rocm-rhel9","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_openshift_ai_(rhoai):rhai-early-access/docling-serve-cuda-rhel9","product":"rhai-early-access/docling-serve-cuda-rhel9 as a component of Red Hat OpenShift AI (RHOAI)","status":"known_affected","remediations":[{"category":"workaround","details":"--- CME Mitigation Guidance (2026-10-20) ---\nDisclaimer: 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.\n\nThe highest-value action is to validate all input image bands to reject 4-byte pixel sizes and 32-bit storage modes prior to invoking Image.merge(): upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate all input bands and reject any band with a 4-byte pixel size or non-single band configuration with a mode error, closing all 2 injection vectors (crafted IPTC image file parsed during standard open and load operations, direct invocation of Image.merge() with a 32-bit image band). Until patched, this is a concern on applications using Pillow to process untrusted image files or calling Image.merge() on untrusted image bands, so restrict image ingestion pipelines from processing untrusted IPTC files or passing unvalidated 32-bit single-band images into Image.merge(). As a compensating measure, enforce an explicit allowlist of permitted image modes and band configurations before invoking Image.merge() to prevent processing unsupported 32-bit image bands. These controls limit blast radius and contain exploitation, but they do not fix the underlying null pointer dereference defect — apply the upstream patch to fully remediate.\n\nHighest-impact CME: CME-1315 Allowlist-Preferred Input Validation (Deny-by-Default Filtering) (medium)"},{"category":"none_available","details":"Affected"}],"purl":"pkg:oci/docling-serve-cuda-rhel9@sha256:d4393882dd9adc9ee6fd03265bb20d90944906a4fa6b37db5b0a47df36ebac75?repository_url=registry.redhat.io/rhai-early-access/docling-serve-cuda-rhel9","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_openshift_ai_(rhoai):rhoai/odh-autorag-rhel9","product":"rhoai/odh-autorag-rhel9 as a component of Red Hat OpenShift AI (RHOAI)","status":"known_affected","remediations":[{"category":"workaround","details":"--- CME Mitigation Guidance (2026-10-20) ---\nDisclaimer: 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.\n\nThe highest-value action is to validate all input image bands to reject 4-byte pixel sizes and 32-bit storage modes prior to invoking Image.merge(): upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate all input bands and reject any band with a 4-byte pixel size or non-single band configuration with a mode error, closing all 2 injection vectors (crafted IPTC image file parsed during standard open and load operations, direct invocation of Image.merge() with a 32-bit image band). Until patched, this is a concern on applications using Pillow to process untrusted image files or calling Image.merge() on untrusted image bands, so restrict image ingestion pipelines from processing untrusted IPTC files or passing unvalidated 32-bit single-band images into Image.merge(). As a compensating measure, enforce an explicit allowlist of permitted image modes and band configurations before invoking Image.merge() to prevent processing unsupported 32-bit image bands. These controls limit blast radius and contain exploitation, but they do not fix the underlying null pointer dereference defect — apply the upstream patch to fully remediate.\n\nHighest-impact CME: CME-1315 Allowlist-Preferred Input Validation (Deny-by-Default Filtering) (medium)"},{"category":"none_available","details":"Affected"}],"purl":"pkg:oci/odh-autorag-rhel9@sha256:27d0833efd8096d7311746c1a4f72699b945b2b2fa88ed47073eba96bb3b9503?repository_url=registry.redhat.io/rhoai/odh-autorag-rhel9","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_openshift_ai_(rhoai):rhoai/odh-kserve-autogluon-server-rhel9","product":"rhoai/odh-kserve-autogluon-server-rhel9 as a component of Red Hat OpenShift AI (RHOAI)","status":"known_affected","remediations":[{"category":"workaround","details":"--- CME Mitigation Guidance (2026-10-20) ---\nDisclaimer: 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.\n\nThe highest-value action is to validate all input image bands to reject 4-byte pixel sizes and 32-bit storage modes prior to invoking Image.merge(): upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate all input bands and reject any band with a 4-byte pixel size or non-single band configuration with a mode error, closing all 2 injection vectors (crafted IPTC image file parsed during standard open and load operations, direct invocation of Image.merge() with a 32-bit image band). Until patched, this is a concern on applications using Pillow to process untrusted image files or calling Image.merge() on untrusted image bands, so restrict image ingestion pipelines from processing untrusted IPTC files or passing unvalidated 32-bit single-band images into Image.merge(). As a compensating measure, enforce an explicit allowlist of permitted image modes and band configurations before invoking Image.merge() to prevent processing unsupported 32-bit image bands. These controls limit blast radius and contain exploitation, but they do not fix the underlying null pointer dereference defect — apply the upstream patch to fully remediate.\n\nHighest-impact CME: CME-1315 Allowlist-Preferred Input Validation (Deny-by-Default Filtering) (medium)"},{"category":"none_available","details":"Affected"}],"purl":"pkg:oci/odh-kserve-autogluon-server-rhel9@sha256:d16a3db7f9491439c9ffa90d81e1e45eeaa17ce64b1dbd8eaaf6a3b7948a99fa?repository_url=registry.redhat.io/rhoai/odh-kserve-autogluon-server-rhel9","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_openshift_ai_(rhoai):rhoai/odh-llama-stack-core-rhel9","product":"rhoai/odh-llama-stack-core-rhel9 as a component of Red Hat OpenShift AI (RHOAI)","status":"known_affected","remediations":[{"category":"workaround","details":"--- CME Mitigation Guidance (2026-10-20) ---\nDisclaimer: 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.\n\nThe highest-value action is to validate all input image bands to reject 4-byte pixel sizes and 32-bit storage modes prior to invoking Image.merge(): upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate all input bands and reject any band with a 4-byte pixel size or non-single band configuration with a mode error, closing all 2 injection vectors (crafted IPTC image file parsed during standard open and load operations, direct invocation of Image.merge() with a 32-bit image band). Until patched, this is a concern on applications using Pillow to process untrusted image files or calling Image.merge() on untrusted image bands, so restrict image ingestion pipelines from processing untrusted IPTC files or passing unvalidated 32-bit single-band images into Image.merge(). As a compensating measure, enforce an explicit allowlist of permitted image modes and band configurations before invoking Image.merge() to prevent processing unsupported 32-bit image bands. These controls limit blast radius and contain exploitation, but they do not fix the underlying null pointer dereference defect — apply the upstream patch to fully remediate.\n\nHighest-impact CME: CME-1315 Allowlist-Preferred Input Validation (Deny-by-Default Filtering) (medium)"},{"category":"none_available","details":"Affected"}],"purl":"pkg:oci/odh-llama-stack-core-rhel9@sha256:4d89196e9a333993dbb01199c418a0e3e77f32e16690a4067ef10466c2e7cb03?repository_url=registry.redhat.io/rhoai/odh-llama-stack-core-rhel9","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_openshift_ai_(rhoai):rhoai/odh-openvino-model-server-rhel9","product":"rhoai/odh-openvino-model-server-rhel9 as a component of Red Hat OpenShift AI (RHOAI)","status":"known_affected","remediations":[{"category":"workaround","details":"--- CME Mitigation Guidance (2026-10-20) ---\nDisclaimer: 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.\n\nThe highest-value action is to validate all input image bands to reject 4-byte pixel sizes and 32-bit storage modes prior to invoking Image.merge(): upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate all input bands and reject any band with a 4-byte pixel size or non-single band configuration with a mode error, closing all 2 injection vectors (crafted IPTC image file parsed during standard open and load operations, direct invocation of Image.merge() with a 32-bit image band). Until patched, this is a concern on applications using Pillow to process untrusted image files or calling Image.merge() on untrusted image bands, so restrict image ingestion pipelines from processing untrusted IPTC files or passing unvalidated 32-bit single-band images into Image.merge(). As a compensating measure, enforce an explicit allowlist of permitted image modes and band configurations before invoking Image.merge() to prevent processing unsupported 32-bit image bands. These controls limit blast radius and contain exploitation, but they do not fix the underlying null pointer dereference defect — apply the upstream patch to fully remediate.\n\nHighest-impact CME: CME-1315 Allowlist-Preferred Input Validation (Deny-by-Default Filtering) (medium)"},{"category":"none_available","details":"Affected"}],"purl":"pkg:oci/odh-openvino-model-server-rhel9@sha256:b850e7e0a37c02ac0bca3967fa80c9954f3d83cfde031687d85f2045a52f6cdb?repository_url=registry.redhat.io/rhoai/odh-openvino-model-server-rhel9","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_openshift_ai_(rhoai):rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9","product":"rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI)","status":"known_affected","remediations":[{"category":"workaround","details":"--- CME Mitigation Guidance (2026-10-20) ---\nDisclaimer: 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.\n\nThe highest-value action is to validate all input image bands to reject 4-byte pixel sizes and 32-bit storage modes prior to invoking Image.merge(): upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate all input bands and reject any band with a 4-byte pixel size or non-single band configuration with a mode error, closing all 2 injection vectors (crafted IPTC image file parsed during standard open and load operations, direct invocation of Image.merge() with a 32-bit image band). Until patched, this is a concern on applications using Pillow to process untrusted image files or calling Image.merge() on untrusted image bands, so restrict image ingestion pipelines from processing untrusted IPTC files or passing unvalidated 32-bit single-band images into Image.merge(). As a compensating measure, enforce an explicit allowlist of permitted image modes and band configurations before invoking Image.merge() to prevent processing unsupported 32-bit image bands. These controls limit blast radius and contain exploitation, but they do not fix the underlying null pointer dereference defect — apply the upstream patch to fully remediate.\n\nHighest-impact CME: CME-1315 Allowlist-Preferred Input Validation (Deny-by-Default Filtering) (medium)"},{"category":"none_available","details":"Affected"}],"purl":"pkg:oci/odh-pipeline-runtime-pytorch-rocm-py312-rhel9@sha256:8bf2de878394390a6254b889783bd87185b573d93487055364326e864a404dc7?repository_url=registry.redhat.io/rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_openshift_ai_(rhoai):rhoai/odh-th-torch-cuda-py312-rhel9","product":"rhoai/odh-th-torch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI)","status":"known_affected","remediations":[{"category":"workaround","details":"--- CME Mitigation Guidance (2026-10-20) ---\nDisclaimer: 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.\n\nThe highest-value action is to validate all input image bands to reject 4-byte pixel sizes and 32-bit storage modes prior to invoking Image.merge(): upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate all input bands and reject any band with a 4-byte pixel size or non-single band configuration with a mode error, closing all 2 injection vectors (crafted IPTC image file parsed during standard open and load operations, direct invocation of Image.merge() with a 32-bit image band). Until patched, this is a concern on applications using Pillow to process untrusted image files or calling Image.merge() on untrusted image bands, so restrict image ingestion pipelines from processing untrusted IPTC files or passing unvalidated 32-bit single-band images into Image.merge(). As a compensating measure, enforce an explicit allowlist of permitted image modes and band configurations before invoking Image.merge() to prevent processing unsupported 32-bit image bands. These controls limit blast radius and contain exploitation, but they do not fix the underlying null pointer dereference defect — apply the upstream patch to fully remediate.\n\nHighest-impact CME: CME-1315 Allowlist-Preferred Input Validation (Deny-by-Default Filtering) (medium)"},{"category":"none_available","details":"Affected"}],"purl":"pkg:oci/odh-th-torch-cuda-py312-rhel9@sha256:efd7b3607b699092c68359d20ef0d0043114191a097637667c0d2cf78fbea702?repository_url=registry.redhat.io/rhoai/odh-th-torch-cuda-py312-rhel9","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_openshift_ai_(rhoai):rhoai/odh-th06-rocm64-torch291-py312-rhel9","product":"rhoai/odh-th06-rocm64-torch291-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI)","status":"known_affected","remediations":[{"category":"workaround","details":"--- CME Mitigation Guidance (2026-10-20) ---\nDisclaimer: 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.\n\nThe highest-value action is to validate all input image bands to reject 4-byte pixel sizes and 32-bit storage modes prior to invoking Image.merge(): upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate all input bands and reject any band with a 4-byte pixel size or non-single band configuration with a mode error, closing all 2 injection vectors (crafted IPTC image file parsed during standard open and load operations, direct invocation of Image.merge() with a 32-bit image band). Until patched, this is a concern on applications using Pillow to process untrusted image files or calling Image.merge() on untrusted image bands, so restrict image ingestion pipelines from processing untrusted IPTC files or passing unvalidated 32-bit single-band images into Image.merge(). As a compensating measure, enforce an explicit allowlist of permitted image modes and band configurations before invoking Image.merge() to prevent processing unsupported 32-bit image bands. These controls limit blast radius and contain exploitation, but they do not fix the underlying null pointer dereference defect — apply the upstream patch to fully remediate.\n\nHighest-impact CME: CME-1315 Allowlist-Preferred Input Validation (Deny-by-Default Filtering) (medium)"},{"category":"none_available","details":"Affected"}],"purl":"pkg:oci/odh-th06-rocm64-torch291-py312-rhel9@sha256:b2a253f3dc063a8e1cee441640cce13fcf04918ce453be8f5d488301b1458a91?repository_url=registry.redhat.io/rhoai/odh-th06-rocm64-torch291-py312-rhel9","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_openshift_ai_(rhoai):rhoai/odh-trustyai-nemo-guardrails-server-rhel9","product":"rhoai/odh-trustyai-nemo-guardrails-server-rhel9 as a component of Red Hat OpenShift AI (RHOAI)","status":"known_affected","remediations":[{"category":"workaround","details":"--- CME Mitigation Guidance (2026-10-20) ---\nDisclaimer: 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.\n\nThe highest-value action is to validate all input image bands to reject 4-byte pixel sizes and 32-bit storage modes prior to invoking Image.merge(): upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate all input bands and reject any band with a 4-byte pixel size or non-single band configuration with a mode error, closing all 2 injection vectors (crafted IPTC image file parsed during standard open and load operations, direct invocation of Image.merge() with a 32-bit image band). Until patched, this is a concern on applications using Pillow to process untrusted image files or calling Image.merge() on untrusted image bands, so restrict image ingestion pipelines from processing untrusted IPTC files or passing unvalidated 32-bit single-band images into Image.merge(). As a compensating measure, enforce an explicit allowlist of permitted image modes and band configurations before invoking Image.merge() to prevent processing unsupported 32-bit image bands. These controls limit blast radius and contain exploitation, but they do not fix the underlying null pointer dereference defect — apply the upstream patch to fully remediate.\n\nHighest-impact CME: CME-1315 Allowlist-Preferred Input Validation (Deny-by-Default Filtering) (medium)"},{"category":"none_available","details":"Affected"}],"purl":"pkg:oci/odh-trustyai-nemo-guardrails-server-rhel9@sha256:c10ff17d1912fe7a7b15b05923cefac72b355bbfb91b19f82c1d179596a7775a?repository_url=registry.redhat.io/rhoai/odh-trustyai-nemo-guardrails-server-rhel9","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-pytorch-llmcompressor-cuda-py312-rhel9","product":"rhoai/odh-workbench-jupyter-pytorch-llmcompressor-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI)","status":"known_affected","remediations":[{"category":"workaround","details":"--- CME Mitigation Guidance (2026-10-20) ---\nDisclaimer: 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.\n\nThe highest-value action is to validate all input image bands to reject 4-byte pixel sizes and 32-bit storage modes prior to invoking Image.merge(): upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate all input bands and reject any band with a 4-byte pixel size or non-single band configuration with a mode error, closing all 2 injection vectors (crafted IPTC image file parsed during standard open and load operations, direct invocation of Image.merge() with a 32-bit image band). Until patched, this is a concern on applications using Pillow to process untrusted image files or calling Image.merge() on untrusted image bands, so restrict image ingestion pipelines from processing untrusted IPTC files or passing unvalidated 32-bit single-band images into Image.merge(). As a compensating measure, enforce an explicit allowlist of permitted image modes and band configurations before invoking Image.merge() to prevent processing unsupported 32-bit image bands. These controls limit blast radius and contain exploitation, but they do not fix the underlying null pointer dereference defect — apply the upstream patch to fully remediate.\n\nHighest-impact CME: CME-1315 Allowlist-Preferred Input Validation (Deny-by-Default Filtering) (medium)"},{"category":"none_available","details":"Affected"}],"purl":"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","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9","product":"rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI)","status":"known_affected","remediations":[{"category":"workaround","details":"--- CME Mitigation Guidance (2026-10-20) ---\nDisclaimer: 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.\n\nThe highest-value action is to validate all input image bands to reject 4-byte pixel sizes and 32-bit storage modes prior to invoking Image.merge(): upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate all input bands and reject any band with a 4-byte pixel size or non-single band configuration with a mode error, closing all 2 injection vectors (crafted IPTC image file parsed during standard open and load operations, direct invocation of Image.merge() with a 32-bit image band). Until patched, this is a concern on applications using Pillow to process untrusted image files or calling Image.merge() on untrusted image bands, so restrict image ingestion pipelines from processing untrusted IPTC files or passing unvalidated 32-bit single-band images into Image.merge(). As a compensating measure, enforce an explicit allowlist of permitted image modes and band configurations before invoking Image.merge() to prevent processing unsupported 32-bit image bands. These controls limit blast radius and contain exploitation, but they do not fix the underlying null pointer dereference defect — apply the upstream patch to fully remediate.\n\nHighest-impact CME: CME-1315 Allowlist-Preferred Input Validation (Deny-by-Default Filtering) (medium)"},{"category":"none_available","details":"Affected"}],"purl":"pkg:oci/odh-workbench-jupyter-trustyai-cpu-py312-rhel9@sha256:90da115e64c80fbf57802442848ff8eee18d8c38e6e30edfdb374bb94dd84735?repository_url=registry.redhat.io/rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_satellite_6:python3.12-pillow.src","product":"python3.12-pillow.src as a component of Red Hat Satellite 6","status":"known_affected","remediations":[{"category":"workaround","details":"--- CME Mitigation Guidance (2026-10-20) ---\nDisclaimer: 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.\n\nThe highest-value action is to validate all input image bands to reject 4-byte pixel sizes and 32-bit storage modes prior to invoking Image.merge(): upgrade to Pillow 13.0.0 (or the fixed Python Pillow/Python3.11 Pillow/Rhoai/Odh Openvino Model Server Rhel/Rhelai3/Bootc Cuda Rhel/Rhelai3/Bootc Gaudi Rhel/Rhelai3/Bootc Rocm Rhel/Rhelai3/Disk Image Cuda Rhel/Python3X Pillow/Rhaiis/Vllm Spyre Rhel/Rhoai/Odh Kserve Storage Initializer Rhel/Rhoai/Odh Kserve Agent Rhel/Rhoai/Odh Kserve Controller Rhel/Rhoai/Odh Kserve Router Rhel/Rhoai/Odh Feature Server Rhel/Rhoai/Odh Trustyai Nemo Guardrails Server Rhel/Rhaiis/Vllm Tpu Rhel/Rhoai/Odh Training Cuda128 Torch29 Py312 Rhel/Rhoai/Odh Training Rocm64 Torch29 Py312 Rhel/Rhaiis/Vllm Cpu Rhel/Rhaiis/Vllm Neuron Rhel/Ansible Automation Platform 25/Lightspeed Chatbot Rhel/Openshift Lightspeed/Lightspeed Ocp Rag Rhel/Rhoai/Odh Th06 Cpu Torch291 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch291 Py312 Rhel/Rhoai/Odh Vllm Gaudi Rhel/Python3.12 Pillow/Rhaii/Vllm Gaudi Rhel/Rhaii/Vllm Neuron Rhel/Rhaii/Vllm Tpu Rhel/Lightspeed Core/Lightspeed Stack Rhel/Rhoai/Odh Kserve Autogluon Server Rhel/Rhai Early Access/Docling Sdk Cuda Rhel/Rhai Early Access/Docling Serve Cuda Rhel/Rhoai/Odh Llm D Kv Cache Rhel/Rhoai/Odh Th06 Cpu Torch210 Py312 Rhel/Rhoai/Odh Th06 Cuda130 Torch210 Py312 Rhel/Rhoai/Odh Th06 Rocm64 Torch291 Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Llmcompressor Cuda Py312 Rhel/Ask Sre/Rhel Cla/Rlsapi Rhel/Rhaiis/Model Opt Cuda Rhel/Rhaiis/Vllm Cuda Rhel/Rhaiis/Vllm Rocm Rhel/Rhaii/Model Opt Cuda Rhel/Rhaii/Vllm Cpu Rhel/Rhaii/Vllm Cuda Rhel/Rhaii/Vllm Rocm Rhel/Rhaii/Vllm Spyre Rhel/Ansible Automation Platform/Automation Dashboard Rhel/Ansible Automation Platform 26/Hub Rhel/Ansible Automation Platform 26/Lightspeed Chatbot Rhel/Ansible Automation Platform 27/Hub Rhel/Ansible Automation Platform 27/Lightspeed Chatbot Rhel/Galaxy Ng/Automation Hub Container/Aap Rag Content/Ansible Chatbot Stack/Koku Report Emailer/Exploit Intelligence/Vulnerability Analysis Rhel/Insights Host Inventory/Google Lightspeed Agent/Lscore Deploy/Lightspeed Core/Rag Tool Cpu Rhel/Lightspeed Core/Rag Tool Cuda 12.9 Rhel/Lightspeed Services Ocp/Ocp Rules Rhel/Openshift Lightspeed Tech Preview/Lightspeed Rag Tool Rhel/Openshift Lightspeed/Lightspeed Service Api Rhel/Rhoai/Odh Caikit Tgis Serving Rhel/Rhoai/Odh Llama Stack Core Rhel/Rhoai/Odh Pipeline Runtime Pytorch Llmcompressor Cuda Py312 Rhel/Rhoai/Odh Automl Rhel/Rhoai/Odh Autorag Rhel/Rhoai/Odh Mlflow Rhel/Rhoai/Odh Pipeline Runtime Datascience Cpu Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Pytorch Rocm Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Cuda Py312 Rhel/Rhoai/Odh Pipeline Runtime Tensorflow Rocm Py312 Rhel/Rhoai/Odh Trustyai Garak Lls Provider Dsp Rhel/Rhoai/Odh Workbench Codeserver Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Datascience Cpu Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Pytorch Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Cuda Py312 Rhel/Rhoai/Odh Workbench Jupyter Tensorflow Rocm Py312 Rhel/Rhoai/Odh Workbench Jupyter Trustyai Cpu Py312 Rhel/Rhai/Guidellm Rhel/Rhoai/Odh Ogx Core Rhel/Rhoai/Odh Th Torch Cpu Py312 Rhel/Rhoai/Odh Th Torch Cuda Py312 Rhel/Rhoai/Odh Th Torch Rocm Py312 Rhel/Quay/Quay Service Tool/Quay/Quay Rhel/Rhelai3/Bootc Aws Cuda Rhel/Rhelai3/Bootc Azure Cuda Rhel/Rhelai3/Bootc Azure Rocm Rhel/Rhelai3/Bootc Gcp Cuda Rhel builds), which validate all input bands and reject any band with a 4-byte pixel size or non-single band configuration with a mode error, closing all 2 injection vectors (crafted IPTC image file parsed during standard open and load operations, direct invocation of Image.merge() with a 32-bit image band). Until patched, this is a concern on applications using Pillow to process untrusted image files or calling Image.merge() on untrusted image bands, so restrict image ingestion pipelines from processing untrusted IPTC files or passing unvalidated 32-bit single-band images into Image.merge(). As a compensating measure, enforce an explicit allowlist of permitted image modes and band configurations before invoking Image.merge() to prevent processing unsupported 32-bit image bands. These controls limit blast radius and contain exploitation, but they do not fix the underlying null pointer dereference defect — apply the upstream patch to fully remediate.\n\nHighest-impact CME: CME-1315 Allowlist-Preferred Input Validation (Deny-by-Default Filtering) (medium)"},{"category":"none_available","details":"Affected"}],"purl":"pkg:rpm/redhat/python3.12-pillow@12.3.0-1.el9ap?arch=src","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_ai_inference_server:rhaiis/vllm-cpu-rhel9","product":"rhaiis/vllm-cpu-rhel9 as a component of Red Hat AI Inference Server","status":"known_not_affected","remediations":[],"justification":"vulnerable_code_not_present","purl":"pkg:oci/vllm-cpu-rhel9@sha256:fb7791bbfea99e9f81529fe8cc1e7c834ca470585c27590e3d0a6834167cd436?repository_url=registry.redhat.io/rhaiis/vllm-cpu-rhel9","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_ai_inference_server:rhaiis/vllm-neuron-rhel9","product":"rhaiis/vllm-neuron-rhel9 as a component of Red Hat AI Inference 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2","status":"known_not_affected","remediations":[],"justification":"vulnerable_code_not_present","purl":"pkg:oci/lightspeed-chatbot-rhel8@sha256:3e61238b7400447dfd7999d053e7f701d7c84d62e4a0ef29950c39f3843fb467?repository_url=registry.redhat.io/ansible-automation-platform-25/lightspeed-chatbot-rhel8","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_ansible_automation_platform_2:ansible-automation-platform/automation-dashboard-rhel9","product":"ansible-automation-platform/automation-dashboard-rhel9 as a component of Red Hat Ansible Automation Platform 2","status":"known_not_affected","remediations":[],"justification":"vulnerable_code_not_present","purl":"pkg:oci/automation-dashboard-rhel9@sha256:3971cc95bbedd16996776c4aadfaeac576ef3b0ad212825a4035fb40849b2bc4?repository_url=registry.redhat.io/ansible-automation-platform/automation-dashboard-rhel9","origins":[{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json"}]},{"source":"redhat","sourceId":"CVE-2026-112405","modified":"2026-10-23T10:50:16+00:00","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-112405.json","productId":"red_hat_ansible_automation_platform_2:python-pillow.src","product":"python-pillow.src as a component of Red Hat Ansible Automation Platform 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