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CVE-2026-34760
MEDIUM5.9
Descricao
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.
Detalhes CVE
Pontuacao CVSS v3.15.9
SeveridadeMEDIUM
Vetor CVSSCVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:L
Vetor de ataqueNETWORK
ComplexidadeHIGH
Privilegios necessariosLOW
Interacao do usuarioNONE
Publicado4/2/2026
Ultima modificacao4/3/2026
Fontenvd
Avistamentos honeypot0
Fraquezas (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)
Correlacoes IOC
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