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CVE-2026-105754

nvd nist
Published: Oct 5, 2026Modified: Oct 8, 2026

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6.5
Vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Exploitability: 2.8 / Impact: 3.6
Source: security-advisories@github.com (Secondary)

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.

Affected (1)

Products: Vllm: Vllm
1 product
Vllm
Configuration A
1 vulnerable
Vulnerable SoftwareAffected Versions
Before 0.30.0

References (4)

Source: security-advisories@github.com
Issue TrackingPatch
Source: security-advisories@github.com
Release Notes
Source: security-advisories@github.com
MitigationVendor Advisory

Timeline

No history available yet.