8.3

CVE-2025-62372

vLLM is an inference and serving engine for large language models (LLMs). From version 0.5.5 to before 0.11.1, users can crash the vLLM engine serving multimodal models by passing multimodal embedding inputs with correct ndim but incorrect shape (e.g. hidden dimension is wrong), regardless of whether the model is intended to support such inputs (as defined in the Supported Models page). This issue has been patched in version 0.11.1.
Verknüpft mit AI von unstrukturierten Daten zu bestehenden CPE der NVD
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Daten sind bereitgestellt durch National Vulnerability Database (NVD)
VllmVllm Version >= 0.5.5 < 0.11.1
VllmVllm Version0.11.1 Updaterc0
VllmVllm Version0.11.1 Updaterc1
Zu dieser CVE wurde keine CISA KEV oder CERT.AT-Warnung gefunden.
EPSS Metriken
Typ Quelle Score Percentile
EPSS FIRST.org 0.05% 0.147
CVSS Metriken
Quelle Base Score Exploit Score Impact Score Vector String
nvd@nist.gov 6.5 2.8 3.6
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
security-advisories@github.com 8.3 0 0
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:H/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
CWE-129 Improper Validation of Array Index

The product uses untrusted input when calculating or using an array index, but the product does not validate or incorrectly validates the index to ensure the index references a valid position within the array.