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
Product
Action
Vendor
Vllm
Product
Vllm
Vllm
Vllm
Vendor
Vllm-project
Product
Vllm
Vllm-project
Vllm
Exploits
No exploit reference
Common Weakness Enumeration
Common Attack Pattern Enumeration and Classification (CAPEC)
Related CVEs
Common Vulnerability Scoring System
Attack Vector
Network
Adjacent
Local
Physical
Privileges Required
None
Low
High
User Interaction
None
Required
Scope
Unchanged
Changed
Confidentiality
None
Low
High
Integrity
None
Low
High
Availability
None
Low
High
