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 spec…
Vulnerability class: Drupalgeddon 2 (CVE-2018-7600)
EPSS: 0.001 (22.6th percentile) — read the EPSS interpretation.
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.
Affected products
- Vllm
- Vllm-project Vllm — versions >= 0.5.5, < 0.18.0
Weakness classification (CWE)
References
- security-advisories@github.com (x_refsource_CONFIRM, Vendor Advisory)
- security-advisories@github.com (x_refsource_MISC, Issue Tracking)
- security-advisories@github.com (Patch, x_refsource_MISC)
- security-advisories@github.com (x_refsource_MISC, 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.