CVE-2026-22778

CRITICAL EPSS 88.3%
Published Feb 2, 20264mo ago · Modified Jun 17, 20261w ago
9.8 CVSS 3.1
Critical
Find Similar
Published Feb 2, 2026 4mo ago
Last Modified Jun 17, 2026 1w ago

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.

CVSS Details

Base Score
9.8
Exploitability
3.9
Impact
5.9
Vector string
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

Threat Intelligence

EPSS Exploit Probability
88.3% percentile
Exploit & Patch Status
No Known Exploit
Patch Available

Weaknesses 1

CWE-532

Affected Products 1

VendorProductVersionRange
vllmvllm*≥0.8.3  –  <0.14.1

References 4

  • github.com https://github.com/vllm-project/vllm/pull/31987
    Issue TrackingPatch
  • github.com https://github.com/vllm-project/vllm/pull/32319
    Issue TrackingPatch
  • github.com https://github.com/vllm-project/vllm/releases/tag/v0.14.1
    Release Notes
  • github.com https://github.com/vllm-project/vllm/security/advisories/GHSA-4r2x-xpjr-7cvv
    Vendor Advisory

Remediation

  • github.com https://github.com/vllm-project/vllm/pull/31987
    Issue TrackingPatch
  • github.com https://github.com/vllm-project/vllm/pull/32319
    Issue TrackingPatch