CVE-2026-34760

취약점 유형

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.

영향받는 제품

• vllm vllm

참고 자료

• https://github.com/vllm-project/vllm/commit/c7f98b4d0a63b32ed939e2b6dfaa8a626e9b46c4
• https://github.com/vllm-project/vllm/pull/37058
• https://github.com/vllm-project/vllm/releases/tag/v0.18.0
• https://github.com/vllm-project/vllm/security/advisories/GHSA-6c4r-fmh3-7rh8