A AegiFlow
MEDIUMCVSS 5.3EPSS 0.3%

CVE-2026-105758

CVE-2026-105758 updated by NVD

Published
2026-10-05
Modified
2026-10-09
EPSS percentile
22%
Sources
github-advisory, nvd

Summary

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.

Affected packages

EcosystemPackageAffected versionsFixed versions
PyPIvllm—0.30.0

Remediation: Upgrade to 0.30.0 or later.

References

Includes data from the GitHub Advisory Database, licensed under CC-BY 4.0.

Includes data from the National Vulnerability Database (NIST). NVD data is in the public domain; this page is not endorsed by NIST.

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EPSS scores provided by the FIRST.org Exploit Prediction Scoring System.