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  <updated>2026-10-07T23:26:02.578925+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-2026-105754</id>
    <title>CVE-2026-105754 — vLLM: Scale-out disaggregated multimodal transport trusts caller-supplied features</title>
    <updated>2026-10-07T23:26:02.595198+00:00</updated>
    <content type="xhtml">
      <div xmlns="http://www.w3.org/1999/xhtml"><p><strong>Affected:</strong> vllm-project vllm</p>
<p>vLLM is an inference and serving engine for large language models. Prior to 0.30.0, the /inference/v1/generate endpoint in the disaggregated scale-out path accepts caller-supplied tensors in the features.kwargs_data field, cache identifiers in the features.mm_hashes field, ranges in the features.mm_placeholders field, and wire-selected multimodal field processors without rebinding them to the active model renderer contract. Forged grid geometry, field types, or non-positive placeholder lengths can terminate the shared EngineCore; when an attacker knows or can induce a victim's content hash, forged cache hashes can poison or retrieve cross-request encoder-cache state; and dropped sparse placeholder masks can alter replayed transport semantics. This issue is fixed in version 0.30.0.</p></div>
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    <link href="https://cve.radiocsirt.org/vuln/cve-2026-105754"/>
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