CVE-2026-105760

Description

vLLM is an inference and serving engine for large language models. Prior to 0.30.0, a caller can use the request-level media_io_kwargs field to select the GLMGA video backend and supply large values for the fps and max_frames options without a strict work ceiling. GLMGA constructs and deduplicates an attacker-sized pre-decode frame-index list, allowing a compact request and tiny valid video to consume disproportionate CPU time and memory in the shared media-loading executor. This issue is fixed in version 0.30.0.

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Produits concernés

• vllm-project vllm
• Vllm vllm

Scores CVSS

Faiblesses (CWE)

• CWE-400

Références

• https://github.com/vllm-project/vllm/commit/8b6de0eb9a09ef53f20cf06bd4d17ee264b9c2a7 Patch
• https://github.com/vllm-project/vllm/pull/54935 Issue TrackingPatch
• https://github.com/vllm-project/vllm/releases/tag/v0.30.0 Release Notes
• https://github.com/vllm-project/vllm/security/advisories/GHSA-58v5-2m8f-94pr MitigationVendor Advisory

Ailleurs

• NVD
• CVE.org
• CIRCL Vulnerability-Lookup
• CERT-FR
• GitHub Advisories