vllm-project vLLM up to 0.31.x Image Input Validation sanity_check_mm_encoder_outputs assertion

Summaryinfo

A vulnerability, which was classified as problematic, was found in vllm-project vLLM up to 0.31.x. The impacted element is the function sanity_check_mm_encoder_outputs of the component Image Input Validation. Such manipulation leads to assertion. This vulnerability is traded as CVE-2026-115914. The attack may be launched remotely. There is no exploit available. You should upgrade the affected component.

Detailsinfo

A vulnerability was found in vllm-project vLLM up to 0.31.x. It has been rated as problematic. Affected by this issue is the function sanity_check_mm_encoder_outputs of the component Image Input Validation. The manipulation with an unknown input leads to a assertion vulnerability. Using CWE to declare the problem leads to CWE-617. The product contains an assert() or similar statement that can be triggered by an attacker, which leads to an application exit or other behavior that is more severe than necessary. Impacted is availability. CVE summarizes:

vLLM is an inference and serving engine for large language models. From 0.11.1 until 0.32.0, the DeepSeek-OCR, DeepSeek-OCR-2, and Unlimited-OCR image path allows a remote client that can reach the OpenAI-compatible API to submit a legal image whose normalized pixels sum to zero when that image is alone in its per-step encoder batch. _parse_and_validate_image_input returns no embedding, embed_multimodal propagates that value, and sanity_check_mm_encoder_outputs triggers a fatal assertion that shuts down the engine for all users. This issue is fixed in version 0.32.0.

The advisory is available at github.com. This vulnerability is handled as CVE-2026-115914 since 10/23/2026. The exploitation is known to be easy. The attack may be launched remotely. Technical details are known, but there is no available exploit.

Upgrading to version 0.32.0 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
• 0.31

Website

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

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