vLLM: Out-of-vocabulary prompt token id passes input validation and triggers a CUDA device-side assert (engine crash / DoS)
Default status is the baseline for the product, each version can override it (e.g. patched versions marked unaffected).
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| vllm-project | vllm | affected |
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| Vllm | Vllm |
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| Vllm-project | Vllm |
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GHSA-q97c-p368-75c4 | vLLM: Out-of-vocabulary prompt token id passes input validation and triggers a CUDA device-side assert (engine crash / DoS) |
No CVSS v4.0
No CVSS v3.0
No CVSS v2
This CVE is not in the KEV list.
Exploit prediction score: < 1% (0.312% probability within 30 days)
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| CPEs | cpe:2.3:a:vllm:vllm:*:*:*:*:*:*:*:* |
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| First Time appeared |
Vllm
Vllm vllm Vllm-project Vllm-project vllm |
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Vllm
Vllm vllm Vllm-project Vllm-project vllm |
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| 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. | |
| Title | vLLM: Out-of-vocabulary prompt token id passes input validation and triggers a CUDA device-side assert (engine crash / DoS) | |
| Weaknesses | CWE-129 CWE-193 |
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| Metrics |
cvssV3_1
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