CVE Database · CVE-2026-34760
CVSS v3.1
5.9
EPSS
0.27%
Published
Apr 2, 2026
Modified
Jul 24, 2026
Public PoC / Exploit
All weaponized →No public PoC or exploit code indexed for this CVE.
Links to public security research (Exploit-DB, Nuclei, Trickest, GitHub) for defensive use only.
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.
CVSS Vector
CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:LWeaknesses (CWE)
Affected Products (1)
References (4)