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CVE

CWE

Training

CVE-2026-22778

Published: Feb 2, 2026

Modified: Feb 3, 2026

PUBLISHED

CVSS v3.1

9.8

CRITICAL

Description

vLLM is an inference and serving engine for large language models (LLMs). From 0.8.3 to before 0.14.1, when an invalid image is sent to vLLM's multimodal endpoint, PIL throws an error. vLLM returns this error to the client, leaking a heap address. With this leak, we reduce ASLR from 4 billion guesses to ~8 guesses. This vulnerability can be chained a heap overflow with JPEG2000 decoder in OpenCV/FFmpeg to achieve remote code execution. This vulnerability is fixed in 0.14.1.

Vendor	Product	Versions
vllm-project	vllm	affected `>= 0.8.3, < 0.14.1`

Weaknesses (CWE)

CVSS v3.1 Details

CVSS v3.1 Vector

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

Attack Vector

Network

Attack Complexity

Low

Privileges Required

None

User Interaction

None

Scope

Unchanged

Confidentiality

High

Integrity

High

Availability

High

References

https://github.com/vllm-project/vllm/security/advisories/GHSA-4r2x-xpjr-7cvv

x_refsource_CONFIRM

https://github.com/vllm-project/vllm/pull/31987

x_refsource_MISC

https://github.com/vllm-project/vllm/pull/32319

x_refsource_MISC

https://github.com/vllm-project/vllm/releases/tag/v0.14.1

x_refsource_MISC

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