vllm-project vLLM up to 0.28.x Audio Decoding memory allocation

Summaryinfo

A vulnerability has been found in vllm-project vLLM up to 0.28.x and classified as problematic. Impacted is an unknown function of the component Audio Decoding. Performing a manipulation results in memory allocation. This vulnerability is cataloged as CVE-2026-100648. It is possible to initiate the attack remotely. There is no exploit available. The affected component should be upgraded.

Detailsinfo

A vulnerability classified as problematic has been found in vllm-project vLLM up to 0.28.x. This affects an unknown part of the component Audio Decoding. The manipulation with an unknown input leads to a memory allocation vulnerability. CWE is classifying the issue as CWE-789. The product allocates memory based on an untrusted, large size value, but it does not ensure that the size is within expected limits, allowing arbitrary amounts of memory to be allocated. This is going to have an impact on availability. The summary by CVE is:

vllm before 0.29.0 fails to enforce VLLM_MAX_AUDIO_CLIP_FILESIZE_MB limit in multimodal chat audio decoding, allowing unauthenticated clients to bypass file size restrictions. Attackers can submit oversized audio files through chat endpoints to consume excessive memory and CPU resources during decoding.

It is possible to read the advisory at github.com. This vulnerability is uniquely identified as CVE-2026-100648 since 09/26/2026. The exploitability is told to be easy. It is possible to initiate the attack remotely. No form of authentication is needed for exploitation. The technical details are unknown and an exploit is not publicly 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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