CVE-2026-105760

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.

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

• HIGHCVE-2026-100137
• HIGHCVE-2026-100138
• HIGHCVE-2026-100139
• HIGHCVE-2026-100242PoC
• MEDIUMCVE-2026-100350PoC
• MEDIUMCVE-2026-100527PoC
• LOWCVE-2026-100542PoC
• HIGHCVE-2026-100558PoC

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