CVE-2026-56340

high

Description

vLLM versions >= 0.10.2 and < 0.13.0 are missing sparse tensor validation in multimodal embeddings processing. Because PyTorch disables sparse tensor invariant checks by default, an attacker can submit crafted embedding requests with malformed (negative or out-of-bounds) tensor indices, when the prompt-embeds feature is enabled, to trigger crashes or resource exhaustion (denial of service), with potential for out-of-bounds/write-what-where memory corruption. This continues CVE-2025-62164, whose prior fix only disabled the feature by default rather than addressing the root cause.

References

https://www.vulncheck.com/advisories/vllm-denial-of-service-via-unvalidated-multimodal-embeddings

https://github.com/vllm-project/vllm/security/advisories/GHSA-mcmc-2m55-j8jj

Details

Source: Mitre, NVD

Published: 2026-06-20

Updated: 2026-06-20

Risk Information

CVSS v2

Base Score: 9

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

Severity: High

CVSS v3

Base Score: 8.8

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

Severity: High

CVSS v4

Base Score: 8.7

Vector: CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

Severity: High