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      <title>CVE-2026-115916 — vLLM: Out-of-vocabulary prompt token id passes input validation and triggers a CUDA device-side assert (engine crash /…</title>
      <link>https://db.gcve.eu/vuln/cve-2026-115916</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; vllm-project vllm&lt;/p&gt;
&lt;p&gt;vLLM is an inference and serving engine for large language models. Prior to 0.32.0, vllm/tokenizers/hf.py computes max_token_id with an off-by-one upper bound, allowing a pre-tokenized prompt ID equal to the vocabulary size to pass validation. For a tensor-parallel size of one and an exact multiple-of-64 vocabulary, VocabParallelEmbedding.forward does not mask that value before F.embedding uses it, causing a CUDA device-side assertion and terminating the engine. This issue is fixed in version 0.32.0.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; vllm-project vllm&lt;/p&gt;
&lt;p&gt;vLLM is an inference and serving engine for large language models. Prior to 0.32.0, vllm/tokenizers/hf.py computes max_token_id with an off-by-one upper bound, allowing a pre-tokenized prompt ID equal to the vocabulary size to pass validation. For a tensor-parallel size of one and an exact multiple-of-64 vocabulary, VocabParallelEmbedding.forward does not mask that value before F.embedding uses it, causing a CUDA device-side assertion and terminating the engine. This issue is fixed in version 0.32.0.&lt;/p&gt;</content:encoded>
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