CVE-2026-34760
HIGH EPSS 18.2%
Published Apr 2, 20262mo ago · Modified Jun 17, 20261w ago
7.1 CVSS 3.1
Published Apr 2, 2026 2mo ago
Last Modified Jun 17, 2026 1w ago
Description
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.
CVSS Details
Base Score
Exploitability
Impact
Vector string
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:L Attack Vector Network
Attack Complexity Low
Privileges Required Low
User Interaction None
Scope Unchanged
Confidentiality None
Integrity High
Availability Low
Threat Intelligence
EPSS Exploit Probability
18.2% percentile
Exploit & Patch Status
No Known Exploit
Patch Available
Weaknesses 1
CWE-20 Improper Input Validation Validation
Affected Products 1
| Vendor | Product | Version | Range |
|---|---|---|---|
| vllm | vllm | * | ≥0.5.5 – <0.18.0 |
References 4
- github.com https://github.com/vllm-project/vllm/commit/c7f98b4d0a63b32ed939e2b6dfaa8a626e9b46c4
- github.com https://github.com/vllm-project/vllm/pull/37058
- github.com https://github.com/vllm-project/vllm/releases/tag/v0.18.0
- github.com https://github.com/vllm-project/vllm/security/advisories/GHSA-6c4r-fmh3-7rh8
Remediation
- github.com https://github.com/vllm-project/vllm/commit/c7f98b4d0a63b32ed939e2b6dfaa8a626e9b46c4