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    CVE-2026-115916

    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.

    Published:Oct 26, 2026
    Last Modified:Nov 2, 2026
    EPS:Oct 26, 2026
    EPSS Score:0.00312
    CVSS Score:6.5

    Affected Products

    Vendor
    Vllm
    Product
    Vllm
    Vendor
    Vllm-project
    Product
    Vllm

    Exploits

    No exploit reference

    Common Attack Pattern Enumeration and Classification (CAPEC)

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    Privileges Required
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    User Interaction
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    Scope
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    None
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    Integrity
    None
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    Availability
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    High