๐Ÿ” CVE Alert

CVE-2026-105754

MEDIUM 6.5

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

CVSS Score
6.5
EPSS Score
0.0%
EPSS Percentile
0th

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.

CWE CWE-20 CWE-617 CWE-639 CWE-668 CWE-704 CWE-1284
Vendor vllm-project
Product vllm
Published Oct 5, 2026
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CVSS v3 Breakdown

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Attack Vector
Network
Attack Complexity
Low
Privileges Required
Low
User Interaction
None
Scope
Unchanged
Confidentiality
None
Integrity
None
Availability
High

Affected Versions

vllm-project / vllm
< 0.30.0

References

NVD โ†— CVE.org โ†— EPSS Data โ†—
github.com: https://github.com/vllm-project/vllm/security/advisories/GHSA-ph72-cqr5-qpp7 github.com: https://github.com/vllm-project/vllm/pull/51898 github.com: https://github.com/vllm-project/vllm/commit/1970f3ed4be7fa8620e4ddc4a12c36a8384cfc27 github.com: https://github.com/vllm-project/vllm/releases/tag/v0.30.0