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CVE-2026-69147

vLLM: Request-selected PyNvVideoCodec GPU decode bypasses static VRAM reservation

Published: Sep 16, 2026Updated: Sep 16, 2026 Sources: CVE List NVDCWE-400

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.

No summary for this CVE yet.

CVSS Vector Breakdown

AV:NAC:LPR:LUI:NS:UC:NI:NA:H
Exploitability
AV:NAttack Vector
Network
AC:LAttack Complexity
Low
PR:LPrivileges Required
Low
UI:NUser Interaction
None
Scope
S:UScope
Unchanged
Impact
C:NConfidentiality
None
I:NIntegrity
None
A:HAvailability
High

Weaknesses

Affected Products

vllm-project
oss-projectaka vllm-project/vllm, vllm

Exploitability

No known exploits, KEV entries, or remediation guidance available for this vulnerability yet.

Attack Graph

Products CVE Techniques Tactics

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MITRE ATT&CK

1 technique
Impact
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References

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