🛡️ CVE-2026-34760
🟡 CVSS 5.9 — Medium ✅ No Known Exploit NVD
5.9
CVSS Score
0 Low4 Medium7 High9 Critical10

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.

Details

Severity Medium
CVSS Score 5.9
CVSS Vector CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:L
CWE N/A
Public Exploit ✅ No
Source NVD
Published 2026-04-02
Updated 2026-06-02
Modified N/A

Affected Packages

Software From version Fixed in
unknown — —
vllm 0.5.5 0.18.0

References

N/A

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