CVE-2026-115912

Published: Ott 26, 2026 Last Modified: Ott 26, 2026
ExploitDB:
Other exploit source:
Google Dorks:
HIGH 7,5
Attack Vector: network
Attack Complexity: high
Privileges Required: low
User Interaction: none
Scope: unchanged
Confidentiality: high
Integrity: high
Availability: high

Description

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.

502

Deserialization of Untrusted Data

Draft
Common Consequences
Security Scopes Affected:
Integrity Availability Other
Potential Impacts:
Modify Application Data Unexpected State Dos: Resource Consumption (Cpu) Varies By Context
Applicable Platforms
Languages: Java, Ruby, PHP, Python, JavaScript
Technologies: Not Technology-Specific, ICS/OT, AI/ML
View CWE Details
https://github.com/vllm-project/vllm/commit/3d5625cc3c2474994107047d7a6ecb8e400…
https://github.com/vllm-project/vllm/pull/59357
https://github.com/vllm-project/vllm/releases/tag/v0.32.0
https://github.com/vllm-project/vllm/security/advisories/GHSA-6757-hggm-hp2w