Auth bypass in Vllm-Project Vllm

CVE-2026-105754

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.

Vulnerability class: Drupalgeddon 2 (CVE-2018-7600)

Published · last modified .

CVSS v3 metric

CVSS v3 base score 6.5 (Medium). Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H.

EPSS exploit prediction

No EPSS score from FIRST.org yet. New CVEs usually get one within a few days; no score means no signal yet, not low risk. How EPSS works.

Affected products

Weakness classification (CWE)

References

Frequently asked questions

What is CVE-2026-105754?
CVE-2026-105754 is a medium-severity vulnerability in Vllm-Project Vllm, classified under Improper Input Validation. CVSS score: 6.5/10. Published 2026-10-05.
How severe is CVE-2026-105754?
Medium severity. CVSS v3 base score is 6.5 out of 10.