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CVE-2026-22807

Fixed in a distro release EPSS <1%CVSS 8.8

vLLM is an inference and serving engine for large language models (LLMs). Starting in version 0.10.1 and prior to version 0.14.0, vLLM loads Hugging Face `auto_map` dynamic modules during model resolution without gating on `trust_remote_code`, allowing attacker-controlled Python code in a model repo/path to execute at server startup. An attacker who can influence the model repo/path (local directory or remote Hugging Face repo) can achieve arbitrary code execution on the vLLM host during model load. This happens before any request handling and does not require API access. Version 0.14.0 fixes the issue.

Published 2026-01-21 · CVE record · OSV

Products: vllm-project vllm, Red Hat AI Inference Server 3.2, Red Hat AI Inference Server 3.3, Red Hat OpenShift AI 2.25, Red Hat OpenShift AI 3.3, Red Hat OpenShift AI 3.4, Red Hat AI Inference Server, Red Hat Enterprise Linux AI (RHEL AI) 3, Red Hat OpenShift AI (RHOAI)

Fixed upstream

EcosystemPackageFixed in
PyPIvllm0.14.0

Distro releases

ReleasePackageFixed in
Chainguardpy3.10-vllm-cuda-12.40.14.0-r0
Chainguardpy3.12-vllm-cuda-12.40.14.0-r0
Chainguardtritonserver-backend-vllm-cuda-12.925.9.0_git20251112-r6
Chainguardtritonserver-backend-vllm-cuda-12.925.9.0_git20251112-r7
Chainguardtritonserver-backend-vllm-cuda-12.925.9.0_git20260318-r0
Chainguardtritonserver-backend-vllm-cuda-13.025.11-r2