Upstream information
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.SUSE information
Overall state of this security issue: Does not affect SUSE products
This issue is currently rated as having moderate severity.
| CVSS detail | CNA (GitHub) |
|---|---|
| Base Score | 6.5 |
| Vector | CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H |
| Attack Vector | Network |
| Attack Complexity | Low |
| Privileges Required | Low |
| User Interaction | None |
| Scope | Unchanged |
| Confidentiality Impact | None |
| Integrity Impact | None |
| Availability Impact | High |
| CVSSv3 Version | 3.1 |
SUSE Timeline for this CVE
CVE page created: Tue Oct 27 21:53:35 2026CVE page last modified: Tue Oct 27 21:53:35 2026