CVE-2026-105754: CWE-20: Improper Input Validation in vllm-project vllm
Description
vLLM is an inference and serving engine for large language models. Prior to 0.30.0, the /inference/v1/generate endpoint in the disaggregated scale-out path accepts caller-supplied tensors in the features.kwargs_data field, cache identifiers in the features.mm_hashes field, ranges in the features.mm_placeholders field, and wire-selected multimodal field processors without rebinding them to the active model renderer contract. Forged grid geometry, field types, or non-positive placeholder lengths can terminate the shared EngineCore; when an attacker knows or can induce a victim's content hash, forged cache hashes can poison or retrieve cross-request encoder-cache state; and dropped sparse placeholder masks can alter replayed transport semantics. This issue is fixed in version 0.30.0.
CVSS v3.1
Score 6.5medium
Affected software
vllm-project
vllm
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- GitHub_M
- Date Reserved
- 2026-10-05T19:11:07.947Z
- Cvss Version
- 3.1
- State
- PUBLISHED
Threat ID: 6ac42ce12cdf04f656446bf2
Added to database: 10/05/2026, 23:04:01 UTC
Last updated: 10/05/2026, 23:04:01 UTC
Views: 1
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