CVE-2026-34760
Published: Apr 2, 2026
Modified: Apr 3, 2026
CVSS v3.1
5.9
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.
| Vendor | Product | Versions |
|---|---|---|
vllm-project | vllm | affected >= 0.5.5, < 0.18.0 |
Weaknesses (CWE)
CVSS v3.1 Details
CVSS v3.1 Vector
CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:L
Attack Vector
Attack Complexity
Privileges Required
User Interaction
Scope
Confidentiality
Integrity
Availability
References
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