CVE-2026-34760

Katalog CVE

CVSS 7.1 · High EPSS 0,48%

Kerentanan Improper Input Validation pada vllm. Skor CVSS 3.1 7.1 (High) menurut NVD.

Deskripsi (NVD)

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.

Rincian

Terbit di NVD

2 April 2026

Terakhir diubah

24 Juli 2026

Status NVD

Analyzed

CVSS 3.1

7.1 (High), sumber NVD
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:L · uraikan di kalkulator

Jenis kelemahan (CWE)

CWE-20: Improper Input Validation

EPSS (30 hari)

0,48% peluang dieksploitasi; lebih tinggi dari 39,4% CVE lain

Produk dan versi terdampak

> Data dari konfigurasi CPE di NVD.

Referensi dan perbaikan

• https://github.com/vllm-project/vllm/security/advisories/GHSA-6c4r-fmh3-7rh8 advisory vendor
• https://github.com/vllm-project/vllm/commit/c7f98b4d0a63b32ed939e2b6dfaa8a626e9b46c4 patch
• https://github.com/vllm-project/vllm/pull/37058 issue tracking
• https://github.com/vllm-project/vllm/releases/tag/v0.18.0 release notes