CVE-2026-34753

5.4 MEDIUM
Published: April 06, 2026 Modified: April 07, 2026
View on NVD

Description

vLLM is an inference and serving engine for large language models (LLMs). From 0.16.0 to before 0.19.0, a server-side request forgery (SSRF) vulnerability in download_bytes_from_url allows any actor who can control batch input JSON to make the vLLM batch runner issue arbitrary HTTP/HTTPS requests from the server, without any URL validation or domain restrictions. This can be used to target internal services (e.g. cloud metadata endpoints or internal HTTP APIs) reachable from the vLLM host. This vulnerability is fixed in 0.19.0.

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CVSS v3.x Details

0.0 Low Medium High Critical 10.0
Vector String
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:L

References to Advisories, Solutions, and Tools

Patch Vendor Advisory Exploit Third Party Advisory

1 reference(s) from NVD

Quick Stats

CVSS v3 Score
5.4 / 10.0
EPSS (Exploit Probability)
0.0%
11th percentile
Exploitation Status
Not in CISA KEV

Weaknesses (CWE)