vllm-project vLLM up to 0.28.x SamplingParams._validate_allowed_token_ids input validation

Summaryinfo

A vulnerability was found in vllm-project vLLM up to 0.28.x. It has been classified as problematic. Impacted is the function SamplingParams._validate_allowed_token_ids. This manipulation causes input validation. This vulnerability is tracked as CVE-2026-93840. The attack is possible to be carried out remotely. No exploit exists. Upgrading the affected component is recommended.

Detailsinfo

A vulnerability was found in vllm-project vLLM up to 0.28.x. It has been declared as problematic. Affected by this vulnerability is the function SamplingParams._validate_allowed_token_ids. The manipulation with an unknown input leads to a input validation vulnerability. The CWE definition for the vulnerability is CWE-20. The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly. As an impact it is known to affect integrity, and availability. The summary by CVE is:

vLLM before 0.29.0 validates allowed_token_ids against tokenizer length instead of model output logits width in SamplingParams._validate_allowed_token_ids(). Attackers can supply token IDs above the output vocabulary that pass validation, causing LogitBiasState to corrupt GPU logits state and allow concurrent requests to sample tokens outside their allowlists.

The advisory is shared at github.com. This vulnerability is known as CVE-2026-93840 since 09/18/2026. The exploitation appears to be easy. The attack can be launched remotely. Technical details are known, but no exploit is available.

Upgrading to version 0.29.0 eliminates this vulnerability.

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Productinfo

Type

• Project Management Software

Vendor

• vllm-project

Name

• vLLM

Version

• 0.1
• 0.2
• 0.3
• 0.4
• 0.5
• 0.6
• 0.7
• 0.8
• 0.9
• 0.10
• 0.11
• 0.12
• 0.13
• 0.14
• 0.15
• 0.16
• 0.17
• 0.18
• 0.19
• 0.20
• 0.21
• 0.22
• 0.23
• 0.24
• 0.25
• 0.26
• 0.27
• 0.28

Website

• Product: https://github.com/vllm-project/vllm/

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