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CVE-2026-34760
MEDIUM5.9
Beschreibung
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.
CVE Details
CVSS v3.1 Bewertung5.9
SchweregradMEDIUM
CVSS VektorCVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:L
AngriffsvektorNETWORK
KomplexitatHIGH
Erforderliche PrivilegienLOW
BenutzerinteraktionNONE
Veroffentlicht4/2/2026
Zuletzt geandert4/3/2026
Quellenvd
Honeypot-Sichtungen0
Schwachen (CWE)
CWE-20
Referenzen
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)
IOC Korrelationen
Keine Korrelationen erfasst
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