Upstream information
Description
vLLM is an inference and serving engine for large language models. Prior to 0.28.0, request bodies for Chat Completions and Responses can set media_io_kwargs.video.video_backend to pynvvideocodec, and MediaConnector.fetch_video forwards that choice to VideoMediaIO even when startup configuration selected a software decoder. The engine's _reserve_mm_ipc_gpu_memory logic budgets decoder memory only from static configuration, so the request-selected VIDEO_LOADER_REGISTRY backend can create a CUDA context, decoder surfaces, and decoded-frame allocations that were not removed from the engine's KV-cache budget. An attacker able to submit video requests to a video-capable GPU deployment with PyNvVideoCodec installed can exhaust shared GPU memory, causing request failures, worker crashes, or denial of service. The first release containing the fix is version 0.28.0.SUSE information
Overall state of this security issue: Does not affect SUSE products
This issue is currently rated as having moderate severity.
| CVSS detail | CNA (GitHub) |
|---|---|
| Base Score | 6.5 |
| Vector | CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H |
| Attack Vector | Network |
| Attack Complexity | Low |
| Privileges Required | Low |
| User Interaction | None |
| Scope | Unchanged |
| Confidentiality Impact | None |
| Integrity Impact | None |
| Availability Impact | High |
| CVSSv3 Version | 3.1 |
SUSE Timeline for this CVE
CVE page created: Thu Sep 17 16:05:30 2026CVE page last modified: Fri Sep 18 13:43:46 2026