CVE-2026-34760

5.9 MEDIUM
Published: April 02, 2026 Modified: April 03, 2026
View on NVD

Description

vLLM is an inference and serving engine for large language models (LLMs). From version 0.5.5 to before version 0.18.0, Librosa defaults to using numpy.mean for mono downmixing (to_mono), while the international standard ITU-R BS.775-4 specifies a weighted downmixing algorithm. This discrepancy results in inconsistency between audio heard by humans (e.g., through headphones/regular speakers) and audio processed by AI models (Which infra via Librosa, such as vllm, transformer). This issue has been patched in version 0.18.0.

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CVSS v3.x Details

0.0 Low Medium High Critical 10.0
Vector String
CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:L

References to Advisories, Solutions, and Tools

Patch Vendor Advisory Exploit Third Party Advisory

4 reference(s) from NVD

Quick Stats

CVSS v3 Score
5.9 / 10.0
EPSS (Exploit Probability)
0.1%
20th percentile
Exploitation Status
Not in CISA KEV

Weaknesses (CWE)