CVE-2025-62372

vLLM is an inference and serving engine for large language models (LLMs). From version 0.5.5 to before 0.11.1, users can crash the vLLM engine serving multimodal models by passing multimodal embedding inputs with correct ndim but incorrect shape (e.g. hidden dimension is wrong), regardless of whether the model is intended to support such inputs (as defined in the Supported Models page). This issue has been patched in version 0.11.1.

The following products are affected by CVE-2025-62372 vulnerability.

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Here, you will find a curated list of external links that provide in-depth information to CVE-2025-62372.

URL	Resource
https://github.com/vllm-project/vllm/commit/58fab50d82838d5014f4a14d991fdb9352c9c84b
https://github.com/vllm-project/vllm/pull/27204
https://github.com/vllm-project/vllm/pull/6613
https://github.com/vllm-project/vllm/security/advisories/GHSA-pmqf-x6x8-p7qw