CVE-2026-105754

medium

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.

References

https://github.com/vllm-project/vllm/security/advisories/GHSA-ph72-cqr5-qpp7

https://github.com/vllm-project/vllm/releases/tag/v0.30.0

https://github.com/vllm-project/vllm/pull/51898

https://github.com/vllm-project/vllm/commit/1970f3ed4be7fa8620e4ddc4a12c36a8384cfc27

https://euvd.enisa.europa.eu/vulnerability/EUVD-2026-92844

Details

Source: Mitre, NVD

Published: 2026-10-05

Updated: 2026-10-08

Named Vulnerability: GHSA-ph72-cqr5-qpp7

Risk Information

CVSS v2

Base Score: 6.8

Vector: CVSS2#AV:N/AC:L/Au:S/C:N/I:N/A:C

Severity: Medium

CVSS v3

Base Score: 6.5

Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

Severity: Medium

EPSS

EPSS: 0.00269