CVE-2026-105756

Published: Ott 06, 2026 Last Modified: Ott 06, 2026
ExploitDB:
Other exploit source:
Google Dorks:
MEDIUM 6,5
Attack Vector: network
Attack Complexity: low
Privileges Required: low
User Interaction: none
Scope: unchanged
Confidentiality: none
Integrity: none
Availability: high

Description

AI Translation Available

vLLM is an inference and serving engine for large language models. Prior to 0.30.0, OpenAI-compatible request models accept a non-empty cache_salt value without enforcing the character and length restrictions required by the IPCCacheServerKey consumer in LMCache-MP. On deployments using the LMCache-MP connector, a salt that contains a forbidden character or exceeds the permitted length can raise an uncaught ValueError during scheduler cache lookup, causing EngineCore to terminate and denying service to all concurrent users. This issue is fixed in version 0.30.0.

20

Improper Input Validation

Stable
Common Consequences
Security Scopes Affected:
Availability Confidentiality Integrity
Potential Impacts:
Dos: Crash, Exit, Or Restart Dos: Resource Consumption (Cpu) Dos: Resource Consumption (Memory) Read Memory Read Files Or Directories Modify Memory Execute Unauthorized Code Or Commands
Applicable Platforms
Technologies: AI/ML
View CWE Details
248

Uncaught Exception

Draft
Common Consequences
Security Scopes Affected:
Availability Confidentiality
Potential Impacts:
Dos: Crash, Exit, Or Restart Read Application Data
Applicable Platforms
Languages: C++, Java, C#
View CWE Details
https://github.com/vllm-project/vllm/commit/e962733e08d10f7ca65dac4df99e116460b…
https://github.com/vllm-project/vllm/pull/51444
https://github.com/vllm-project/vllm/releases/tag/v0.30.0
https://github.com/vllm-project/vllm/security/advisories/GHSA-2823-qmq8-rwvj