vLLM: Downmix Implementation Differences as Attack Vectors Against Audio AI Models

MITRE NVD CVE.ORG Print: PDF PDF

Summary

CVECVE-2026-34760
StatePUBLISHED
AssignerGitHub_M
Source PriorityCVE Program / NVD first with legacy fallback
Published2026-04-02 20:16:25 UTC
Updated2026-04-02 20:16:25 UTC
DescriptionvLLM 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.

Risk And Classification

Primary CVSS: v3.1 5.9 MEDIUM from [email protected]

CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:L

Problem Types: CWE-20 | CWE-20 CWE-20: Improper Input Validation

VersionSourceTypeScoreSeverityVector
3.1[email protected]Secondary5.9MEDIUMCVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:L
3.1CNADECLARED5.9MEDIUMCVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:L

CVSS v3.1 Breakdown

Attack Vector
Network
Attack Complexity
High
Privileges Required
Low
User Interaction
None
Scope
Unchanged
Confidentiality
None
Integrity
High
Availability
Low

CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:L

Vendor Declared Affected Products

SourceVendorProductVersionPlatforms
CNA Vllm-project Vllm affected >= 0.5.5, < 0.18.0 Not specified

References

ReferenceSourceLinkTags
github.com/vllm-project/vllm/security/advisories/GHSA-6c4r-fmh3-7rh8 [email protected] github.com
github.com/vllm-project/vllm/pull/37058 [email protected] github.com
github.com/vllm-project/vllm/commit/c7f98b4d0a63b32ed939e2b6dfaa8a626e9b... [email protected] github.com
github.com/vllm-project/vllm/releases/tag/v0.18.0 [email protected] github.com
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