CVE-2026-105760
vLLM: GLMGA video sampling permits request-driven CPU and memory exhaustion
CVSS Score
5.3
EPSS Score
0.0%
EPSS Percentile
0th
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.
| CWE | CWE-400 |
| Vendor | vllm-project |
| Product | vllm |
| Published | Oct 5, 2026 |
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CVSS v3 Breakdown
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L Attack Vector
Network
Attack Complexity
Low
Privileges Required
None
User Interaction
None
Scope
Unchanged
Confidentiality
None
Integrity
None
Availability
Low
Affected Versions
vllm-project / vllm
>= 0.23.0rc2, < 0.30.0
References
github.com: https://github.com/vllm-project/vllm/security/advisories/GHSA-58v5-2m8f-94pr github.com: https://github.com/vllm-project/vllm/pull/54935 github.com: https://github.com/vllm-project/vllm/commit/8b6de0eb9a09ef53f20cf06bd4d17ee264b9c2a7 github.com: https://github.com/vllm-project/vllm/releases/tag/v0.30.0