VYPR
Medium severity5.9NVD Advisory· Published Apr 2, 2026· Updated May 11, 2026

CVE-2026-34760

CVE-2026-34760

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.

AI Insight

LLM-synthesized narrative grounded in this CVE's description and references.

Affected products

3
  • Vllm/Vllmreferences3 versions
    (expand)+ 2 more
    • (no CPE)
    • cpe:2.3:a:vllm:vllm:*:*:*:*:*:*:*:*range: >=0.5.5,<0.18.0
    • (no CPE)range: >=0.5.5, <0.18.0

Patches

Vulnerability mechanics

References

4

News mentions

0

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