vllm-project vLLM up to 0.30.x OpenCVDynamicOpenPanguVideoBackend num_frames resource consumption

Summaryinfo

A vulnerability classified as problematic was found in vllm-project vLLM up to 0.30.x. Affected by this issue is some unknown functionality of the component OpenCVDynamicOpenPanguVideoBackend. The manipulation of the argument num_frames results in resource consumption. This vulnerability is known as CVE-2026-126394. It is possible to launch the attack remotely. No exploit is available. Upgrading the affected component is advised.

Detailsinfo

A vulnerability, which was classified as problematic, was found in vllm-project vLLM up to 0.30.x. Affected is an unknown function of the component OpenCVDynamicOpenPanguVideoBackend. The manipulation of the argument num_frames with an unknown input leads to a resource consumption vulnerability. CWE is classifying the issue as CWE-400. The product does not properly control the allocation and maintenance of a limited resource. This is going to have an impact on availability. CVE summarizes:

vLLM 0.30.0 before 0.31.0 contains a resource exhaustion vulnerability in OpenCVDynamicOpenPanguVideoBackend, which uses request-controlled num_frames without an effective ceiling. Unauthenticated attackers can send /v1/chat/completions or /tokenize requests selecting the openpangu video_backend with a huge num_frames, forcing np.linspace allocations and CPU work that OOM-kill the API server.

The advisory is shared for download at github.com. This vulnerability is traded as CVE-2026-126394 since 11/10/2026. The exploitability is told to be easy. It is possible to launch the attack remotely. The exploitation doesn't require any form of authentication. There are known technical details, but no exploit is available. The MITRE ATT&CK project declares the attack technique as T1499.

Upgrading to version 0.31.0 eliminates this vulnerability.

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Productinfo

Type

• Project Management Software

Vendor

• vllm-project

Name

• vLLM

Version

• 0.1
• 0.2
• 0.3
• 0.4
• 0.5
• 0.6
• 0.7
• 0.8
• 0.9
• 0.10
• 0.11
• 0.12
• 0.13
• 0.14
• 0.15
• 0.16
• 0.17
• 0.18
• 0.19
• 0.20
• 0.21
• 0.22
• 0.23
• 0.24
• 0.25
• 0.26
• 0.27
• 0.28
• 0.29
• 0.30

Website

• Product: https://github.com/vllm-project/vllm/

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