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  <updated>2026-10-07T15:02:34.331695+00:00</updated>
  <author>
    <name>Vulnerability-Lookup</name>
    <email>csirt@opendfir.org</email>
  </author>
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  <entry>
    <id>https://cve.radiocsirt.org/vuln/euvd-2026-383056</id>
    <title>EUVD-2026-383056</title>
    <updated>2026-10-07T15:02:34.379504+00:00</updated>
    <content>EUVD-2026-383056</content>
    <link href="https://cve.radiocsirt.org/vuln/euvd-2026-383056"/>
  </entry>
  <entry>
    <id>https://cve.radiocsirt.org/vuln/fkie_cve-2026-105754</id>
    <title>fkie_cve-2026-105754</title>
    <updated>2026-10-07T15:02:34.379544+00:00</updated>
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        <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>
    </content>
    <link href="https://cve.radiocsirt.org/vuln/fkie_cve-2026-105754"/>
  </entry>
  <entry>
    <id>https://cve.radiocsirt.org/vuln/ghsa-ph72-cqr5-qpp7</id>
    <title>GHSA-ph72-cqr5-qpp7 — vLLM: Scale-out disaggregated multimodal transport trusts caller-supplied features</title>
    <updated>2026-10-07T15:02:34.379583+00:00</updated>
    <content type="xhtml">
      <div xmlns="http://www.w3.org/1999/xhtml"><p><strong>Affected:</strong> PyPI: vllm</p>
<p>## Affected</p>
<p>- **Ecosystem / package:** pip / `vllm`
- **Affected versions:** vLLM ≤ 0.25.1 (confirmed on 0.25.1, commit [`752a3a504485`](https://github.com/vllm-project/vllm/tree/752a3a504485790a2e8491cacbb35c137339ad34)). The lower bound predates 0.25.1; maintainers can confirm how far back the scale-out transport path reaches.</p>
<p>## Summary</p>
<p>vLLM's disaggregated **scale-out** transport splits a multimodal request into a trusted render step (`POST /v1/chat/completions/render`) and a separate generate step (`POST /inference/v1/generate`). The generate route decodes a caller-supplied `features` object — serialized encoder tensors (`kwargs_data`), multimodal hashes (`mm_hashes`), placeholder ranges (`mm_placeholders`), and the internal field-processor selection — and forwards it into the engine **as if it had come from the trusted renderer**, with no rebinding to (or validation against) the active model's renderer contract. Because the two routes are ordinary auth-guarded HTTP endpoints (the `/inference` prefix is registered by default on generate-capable servers), any authenticated caller can submit an otherwise-valid render body with a single forged field.</p>
<p>Depending on which field is forged, this produces:</p>
<p>- an **engine-fatal crash** of the shared EngineCore process (denial of service), reproduced as a CUDA illegal-memory-access, a post-admission rank-mismatch `ValueError`, and a hard `assert` — three independent forged fields (sites 1, 2, 3);
- **silent cross-request encod…</p></div>
    </content>
    <link href="https://cve.radiocsirt.org/vuln/ghsa-ph72-cqr5-qpp7"/>
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