CVE-2026-25960

7.1 HIGH
Published: March 09, 2026 Modified: March 18, 2026
View on NVD

Description

vLLM is an inference and serving engine for large language models (LLMs). The SSRF protection fix for CVE-2026-24779 add in 0.15.1 can be bypassed in the load_from_url_async method due to inconsistent URL parsing behavior between the validation layer and the actual HTTP client. The SSRF fix uses urllib3.util.parse_url() to validate and extract the hostname from user-provided URLs. However, load_from_url_async uses aiohttp for making the actual HTTP requests, and aiohttp internally uses the yarl library for URL parsing. This vulnerability in 0.17.0.

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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:H/I:N/A:L

References to Advisories, Solutions, and Tools

Patch Vendor Advisory Exploit Third Party Advisory
https://github.com/vllm-project/vllm/pull/34743
Source: security-advisories@github.com
Issue Tracking Patch
https://github.com/vllm-project/vllm/security/advisories/GHSA-qh4c-xf7m-gxfc
Source: security-advisories@github.com
Not Applicable
https://github.com/vllm-project/vllm/security/advisories/GHSA-v359-jj2v-j536
Source: security-advisories@github.com
Exploit Patch Vendor Advisory

4 reference(s) from NVD

Quick Stats

CVSS v3 Score
7.1 / 10.0
EPSS (Exploit Probability)
0.0%
5th percentile
Exploitation Status
Not in CISA KEV

Weaknesses (CWE)

Affected Vendors

vllm