id: PYSEC-2026-2299
published: "2026-04-02T20:16:25.437Z"
modified: "2026-07-13T05:52:25.186969Z"
aliases:
- CVE-2026-34760
- GHSA-6c4r-fmh3-7rh8
details: 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.
affected:
- package:
    name: vllm
    ecosystem: PyPI
    purl: pkg:pypi/vllm
  ranges:
  - type: ECOSYSTEM
    events:
    - introduced: 0.5.5
    - fixed: 0.18.0
  versions:
  - 0.10.0
  - 0.10.1
  - 0.10.1.1
  - 0.10.2
  - 0.11.0
  - 0.11.1
  - 0.11.2
  - 0.12.0
  - 0.13.0
  - 0.14.0
  - 0.14.1
  - 0.15.0
  - 0.15.1
  - 0.16.0
  - 0.17.0
  - 0.17.1
  - 0.5.5
  - 0.6.0
  - 0.6.1
  - 0.6.1.post1
  - 0.6.1.post2
  - 0.6.2
  - 0.6.3
  - 0.6.3.post1
  - 0.6.4
  - 0.6.4.post1
  - 0.6.5
  - 0.6.6
  - 0.6.6.post1
  - 0.7.0
  - 0.7.1
  - 0.7.2
  - 0.7.3
  - 0.8.0
  - 0.8.1
  - 0.8.2
  - 0.8.3
  - 0.8.4
  - 0.8.5
  - 0.8.5.post1
  - 0.9.0
  - 0.9.0.1
  - 0.9.1
  - 0.9.2
  ecosystem_specific: {}
references:
- type: ADVISORY
  url: https://github.com/vllm-project/vllm/releases/tag/v0.18.0
- type: ADVISORY
  url: https://github.com/vllm-project/vllm/security/advisories/GHSA-6c4r-fmh3-7rh8
- type: REPORT
  url: https://github.com/vllm-project/vllm/pull/37058
- type: FIX
  url: https://github.com/vllm-project/vllm/commit/c7f98b4d0a63b32ed939e2b6dfaa8a626e9b46c4
severity:
- type: CVSS_V3
  score: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:L