What’s Vulnerable › Vulnerabilities

CVE-2026-115916: vLLM: Out-of-vocabulary prompt token id passes input validation and triggers a CUDA device-side assert (engine crash / DoS)

• Severity: medium (CVSS 6.5 v3.1)
• Exploited in the wild: not listed in CISA KEV
• EPSS: 0.3% probability of exploitation in the next 30 days
• Public exploit or detection template: none known
• Published: 2026-10-26 · updated 2026-10-28
• Weakness: CWE-129

Description

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.

Affected products

• vllm-project vllm: before 0.32.0 — fixed in 0.32.0
• vllm-project vllm: before 0.32.0

How to fix

Upgrade to a fixed version: vllm-project vllm 0.32.0. Check the vendor advisory for mitigations.

References

• https://github.com/vllm-project/vllm/commit/37cecc8141e2dcba9dd534897a164d4baaf27229
• https://github.com/vllm-project/vllm/pull/59491
• https://github.com/vllm-project/vllm/releases/tag/v0.32.0
• https://github.com/vllm-project/vllm/security/advisories/GHSA-q97c-p368-75c4

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