vllm-project vLLM up to 0.29.0 Triton _bincount_kernel prompt token IDs out-of-bounds write

Summaryinfo

A vulnerability classified as problematic was found in vllm-project vLLM up to 0.29.0. Affected by this vulnerability is the function _bincount_kernel of the component Triton. Such manipulation of the argument prompt token IDs leads to out-of-bounds write. This vulnerability is uniquely identified as CVE-2026-93841. The attack can be launched remotely. No exploit exists.

Detailsinfo

A vulnerability, which was classified as problematic, has been found in vllm-project vLLM up to 0.29.0. Affected by this issue is the function _bincount_kernel of the component Triton. The manipulation of the argument prompt token IDs with an unknown input leads to a out-of-bounds write vulnerability. Using CWE to declare the problem leads to CWE-787. The product writes data past the end, or before the beginning, of the intended buffer. Impacted is integrity. CVE summarizes:

vLLM through 0.29.0 contains a memory corruption vulnerability in the Triton _bincount_kernel where prompt token IDs index the penalty prompt-presence bitset without bounds checking against vocabulary size. Attackers can submit multimodal audio requests with tokens equal to vocabulary size, causing out-of-bounds writes that corrupt concurrent requests' sampler state and alter repetition penalty behavior.

The advisory is shared for download at github.com. This vulnerability is handled as CVE-2026-93841 since 09/18/2026. The exploitation is known to be easy. The attack may be launched remotely. No form of authentication is required for exploitation. There are known technical details, but no exploit is available. The current price for an exploit might be approx. USD $0-$5k (estimation calculated on 09/18/2026).

There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.

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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
• 0.29.0

Website

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

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