5.3

CVE-2026-105760

vLLM: GLMGA video sampling permits request-driven CPU and memory exhaustion

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.
Daten sind bereitgestellt durch das CVE Programm von einer CVE Numbering Authority (CNA) (Unstrukturiert).
Herstellervllm-project
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Produkt vllm
Version >= 0.23.0rc2, < 0.30.0
Status affected
VulnDex Vulnerability Enrichment
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Zu dieser CVE wurde keine Warnung gefunden.
EPSS Metriken
Typ Quelle Score Percentile
EPSS FIRST.org 0.3% 0.209
CVSS Metriken
Quelle Base Score Exploit Score Impact Score Vector String
security-advisories@github.com 5.3 3.9 1.4
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L
CWE-400 Uncontrolled Resource Consumption

The product does not properly control the allocation and maintenance of a limited resource.

https://github.com/vllm-project/vllm/releases/tag/v0.30.0
https://github.com/vllm-project/vllm/security/advisories/GHSA-58v5-2m8f-94pr
https://github.com/vllm-project/vllm/pull/54935
https://github.com/vllm-project/vllm/commit/8b6de0eb9a09ef53f20cf06bd4d17ee264b9c2a7