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  <updated>2026-10-07T20:13:56.455292+00:00</updated>
  <author>
    <name>Vulnerability-Lookup</name>
    <email>csirt@opendfir.org</email>
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  <entry>
    <id>https://cve.radiocsirt.org/vuln/cve-2026-22807</id>
    <title>CVE-2026-22807 — vLLM affected by RCE via auto_map dynamic module loading during model initialization</title>
    <updated>2026-10-07T20:13:56.458167+00:00</updated>
    <content type="xhtml">
      <div xmlns="http://www.w3.org/1999/xhtml"><p><strong>Affected:</strong> 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)</p>
<p>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.</p></div>
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    <link href="https://cve.radiocsirt.org/vuln/cve-2026-22807"/>
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