vLLM – Denial of Service via Unvalidated Multimodal Embeddings

8.7 / 10

HIGH

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

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.

Basic Information

ID CVE-2026-56340

Source VulnCheck

Published Jun 20, 2026 at 18:27

Affected Product

Vendor vLLM

Product vLLM

Version 0.10.2

Affected Versions vLLM vLLM 0.10.2

CWE Classification

CWE-20

References

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    "published": "2026-06-20T18:27:10.148Z",
    "modified": "2026-06-20T18:27:10.148Z",
    "type": "cve",
    "title": "vLLM - Denial of Service via Unvalidated Multimodal Embeddings",
    "source": "VulnCheck",
    "references": "https://github.com/vllm-project/vllm/security/advisories/GHSA-mcmc-2m55-j8jj\nhttps://www.vulncheck.com/advisories/vllm-denial-of-service-via-unvalidated-multimodal-embeddings",
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    "sourceData": "vLLM vLLM 0.10.2",
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vLLM – Denial of Service via Unvalidated Multimodal Embeddings_CVE-2026-56340