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VULNERABILITIES

CVE-2026-105754 Details

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.

Metrics

CVSS 3.x Severity and Vector Strings:

References to Advisories, Solutions, and Tools

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Weakness Enumeration

CWE-IDCWE NameSource
CWE-1284Improper Validation of Specified Quantity in Input[email protected]
CWE-20Improper Input Validation[email protected]
CWE-617Reachable Assertion[email protected]
CWE-639Authorization Bypass Through User-Controlled Key[email protected]
CWE-668Exposure of Resource to Wrong Sphere[email protected]
CWE-704Incorrect Type Conversion or Cast[email protected]

Affected Products

No affected product data is available for this CVE.

Change History

1 change record found show changes


QUICK INFO

CVE Dictionary Entry:
CVE-2026-105754
NVD Published Date:
Oct 5, 2026
NVD Last Modified:
Oct 5, 2026
Source:
[email protected]
CVE-2026-105754 Details - Not Deferred