vLLM: Request-selected PyNvVideoCodec GPU decode bypasses static VRAM reservation
Default status is the baseline for the product, each version can override it (e.g. patched versions marked unaffected).
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Github GHSA |
GHSA-8pw2-6jv3-mj5j | vLLM: Request-selected PyNvVideoCodec GPU decode bypasses static VRAM reservation |
No CVSS v4.0
No CVSS v3.0
No CVSS v2
This CVE is not in the KEV list.
Exploit prediction score: < 1% (0.583% probability within 30 days)
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Vllm
Vllm vllm |
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| CPEs | cpe:2.3:a:vllm:vllm:*:*:*:*:*:*:*:* | |
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Vllm
Vllm vllm |
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Vllm-project
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Vllm-project vllm |
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threat_severity
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ssvc
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| 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. | |
| Title | vLLM: Request-selected PyNvVideoCodec GPU decode bypasses static VRAM reservation | |
| Weaknesses | CWE-400 CWE-770 |
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cvssV3_1
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