Improper input validation in Vllm
CVE-2026-34760
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.
Vulnerability class: Drupalgeddon 2 (CVE-2018-7600)
Published · last modified .
CVSS v3 metric
CVSS v3 base score 5.9 (Medium). Vector: CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:L.
EPSS exploit prediction
EPSS: 0.005 (39.1th percentile), scored .
Very low probability of exploitation in the next 30 days; routine patching cadence is appropriate. 39th percentile — 39.1% of CVEs in the catalogue have a lower EPSS than this one. How to read EPSS.
EPSS over last 30 days · oldest: 0.003 · newest: 0.005 · change: +0.002
Affected products
- Vllm
- Vllm-Project Vllm — versions >= 0.5.5, < 0.18.0
Weakness classification (CWE)
References
- github.com/vllm-project/vllm/security/advisories/GHSA-6c4r-fmh3-7rh8 (Vendor Advisory)
- github.com/vllm-project/vllm/pull/37058 (Issue Tracking)
- github.com/vllm-project/vllm/commit/c7f98b4d0a63b32ed939e2b6dfaa8a626e9b46c4 (Patch)
- github.com/vllm-project/vllm/releases/tag/v0.18.0 (Release Notes)
Frequently asked questions
- What is CVE-2026-34760?
- CVE-2026-34760 is a medium-severity vulnerability in Vllm, classified under Improper Input Validation. CVSS score: 5.9/10. Published 2026-04-02.
- How severe is CVE-2026-34760?
- Medium severity. CVSS v3 base score is 5.9 out of 10.