SA-26-681 Medium

vLLM: Scale-out disaggregated multimodal transport trusts caller-supplied features

vLLM

Severity
Medium, CVSS 6.5
CVSS vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Record
CVE-2026-105754
Affects
vLLM
Known exploited
Not listed in the CISA Known Exploited Vulnerabilities catalog
Published
Record first published by the source
October 5, 2026
Source last modified
October 8, 2026

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.

Description quoted from the NVD record.

Sources

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