CVE-2026-105756
MEDIUM
6,5
Source: [email protected]
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
StableCommon 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
248
Uncaught Exception
DraftCommon Consequences
Security Scopes Affected:
Availability
Confidentiality
Potential Impacts:
Dos: Crash, Exit, Or Restart
Read Application Data
Applicable Platforms
Languages:
C++, Java, C#
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