CVE-2026-105758
MEDIUM
5,3
Source: [email protected]
Attack Vector: network
Attack Complexity: low
Privileges Required: none
User Interaction: none
Scope: unchanged
Confidentiality: none
Integrity: none
Availability: low
Description
AI Translation Available
vLLM is an inference and serving engine for large language models. From 0.24.0 until 0.30.0, the Qwen2VLVideoBackend and Qwen3VLVideoBackend classes accept request-level values for the media_io_kwargs.video.max_frames and media_io_kwargs.video.fps fields without enforcing server-side ceilings. An unauthenticated caller can submit these values to the /tokenize endpoint, causing the sampler to decode every frame selected from attacker-controlled video input, consume disproportionate frontend memory, and potentially terminate the API process before scheduling or admission control. The Rust frontend is not affected because it rejects the media_io_kwargs field. This issue is fixed in version 0.30.0.
770
Allocation of Resources Without Limits or Throttling
IncompleteCommon Consequences
Security Scopes Affected:
Availability
Potential Impacts:
Dos: Resource Consumption (Cpu)
Dos: Resource Consumption (Memory)
Dos: Resource Consumption (Other)
Applicable Platforms
All platforms may be affected
https://github.com/vllm-project/vllm/commit/ea723c81c3ea26425cb69503a5d5e90822a…
https://github.com/vllm-project/vllm/pull/56729
https://github.com/vllm-project/vllm/releases/tag/v0.30.0
https://github.com/vllm-project/vllm/security/advisories/GHSA-x6mc-67gf-chw4