CVE-2026-34760
7.1
Vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:L
Exploitability: 2.8 / Impact: 4.2
Source: 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.
Affected (1)
References (4)
Source: security-advisories@github.com
Patch
Source: security-advisories@github.com
Release Notes
Source: security-advisories@github.com
Vendor Advisory
Timeline
No history available yet.