Mend.io Vulnerability Database
The largest open source vulnerability database
What is a Vulnerability ID?
New vulnerability? Tell us about it!
CVE-2026-115912
Published:October 26, 2026
Updated:October 28, 2026
vLLM is an inference and serving engine for large language models. Prior to 0.32.0, an authenticated caller can place forged shared-memory address and monotonic_id values in public multimodal features.kwargs_data. In scale-out deployments with shared-memory multimodal caching enabled, workers trust those values and pass attacker-selected bytes to pickle.loads(), allowing arbitrary Python execution even when insecure serialization is disabled. This issue is fixed in version 0.32.0.
Affected Packages
https://github.com/vllm-project/vllm.git (GITHUB):
Affected version(s) >=v0.19.2rc0 <v0.32.0
Fix Suggestion:
Update to version v0.32.0
vllm (PYTHON):
Affected version(s) >=0.20.0 <0.32.0
Fix Suggestion:
Update to version 0.32.0
Do you need more information?
Contact Us
CVSS v4
Base Score:
7.7
Attack Vector
NETWORK
Attack Complexity
HIGH
Attack Requirements
NONE
Privileges Required
LOW
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:
7.5
Attack Vector
NETWORK
Attack Complexity
HIGH
Privileges Required
LOW
User Interaction
NONE
Scope
UNCHANGED
Confidentiality
HIGH
Integrity
HIGH
Availability
HIGH
Weakness Type (CWE)
Deserialization of Untrusted Data
EPSS
Base Score:
0.48