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CVE-2026-34760
MEDIUM5.9
Descripcion
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.
Detalles CVE
Puntuacion CVSS v3.15.9
SeveridadMEDIUM
Vector CVSSCVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:L
Vector de ataqueNETWORK
ComplejidadHIGH
Privilegios requeridosLOW
Interaccion usuarioNONE
Publicado4/2/2026
Ultima modificacion4/3/2026
Fuentenvd
Avistamientos honeypot0
Debilidades (CWE)
CWE-20
Referencias
https://github.com/vllm-project/vllm/commit/c7f98b4d0a63b32ed939e2b6dfaa8a626e9b46c4(security-advisories@github.com)
https://github.com/vllm-project/vllm/pull/37058(security-advisories@github.com)
https://github.com/vllm-project/vllm/releases/tag/v0.18.0(security-advisories@github.com)
https://github.com/vllm-project/vllm/security/advisories/GHSA-6c4r-fmh3-7rh8(security-advisories@github.com)
Correlaciones IOC
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