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Advisory details: vulnrichment / CVE-2026-34760
Advisory ID vulnrichment/CVE-2026-34760
Aliases
Summary 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.
Status Published
Exploitability 0.5
Weighted Severity 0.0
Risk
Affected and Fixed Packages Package Details
Introduced and Fixed Package Commit Patches Package Commit Patches Details
Weaknesses (1)
System Score Found at
cvssv3.1 5.9
ssvc Track
No exploits are available.

No EPSS data available for this advisory.

Patch URL
There are no known patches.
Vector: CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:L Found at None
Attack Vector (AV) Attack Complexity (AC) Privileges Required (PR) User Interaction (UI) Scope (S) Confidentiality Impact (C) Integrity Impact (I) Availability Impact (A)

network

adjacent_network

local

physical

low

high

none

low

high

none

required

unchanged

changed

high

low

none

high

low

none

high

low

none


Vector: SSVCv2/E:N/A:N/T:P/P:M/B:A/M:M/D:T/2026-04-03T14:42:25Z/ Found at None

Vector: SSVCv2/E:N/A:N/T:P/P:M/B:A/M:M/D:T/2026-04-03T14:42:25Z/

Decision: Track

Source URL: https://github.com/cisagov/vulnrichment/blob/develop/2026/34xxx/CVE-2026-34760.json

Source Advisory: vulnrichment/CVE-2026-34760

View SSVC decision tree
[{'Exploitation': 'none'},
 {'Automatable': 'no'},
 {'Technical Impact': 'partial'},
 {'Mission Prevalence': 'minimal'},
 {'Public Well-being Impact': 'material'},
 {'Mission & Well-being': 'medium'}]