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CVE-2026-22778
February 02, 2026
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.
Affected Packages
https://github.com/vllm-project/vllm.git (GITHUB):
Affected version(s) >=v0.8.3 <v0.15.0
Fix Suggestion:
Update to version v0.15.0
vllm (PYTHON):
Affected version(s) >=0.8.3 <0.14.1
Fix Suggestion:
Update to version 0.14.1
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CVSS v4
Base Score:
9.3
Attack Vector
NETWORK
Attack Complexity
LOW
Attack Requirements
NONE
Privileges Required
NONE
User Interaction
NONE
Vulnerable System Confidentiality
HIGH
Vulnerable System Integrity
HIGH
Vulnerable System Availability
HIGH
Subsequent System Confidentiality
NONE
Subsequent System Integrity
NONE
Subsequent System Availability
NONE
CVSS v3
Base Score:
9.8
Attack Vector
NETWORK
Attack Complexity
LOW
Privileges Required
NONE
User Interaction
NONE
Scope
UNCHANGED
Confidentiality
HIGH
Integrity
HIGH
Availability
HIGH
Weakness Type (CWE)
Insertion of Sensitive Information into Log File
Heap-based Buffer Overflow
EPSS
Base Score:
0.06