HIGH · 7.1

CVE-2026-25960

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...

Vulnerability 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.

CVSS Score

7.1

HIGH

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:L
Attack Vector
NETWORK
Attack Complexity
LOW
Privileges Required
LOW
User Interaction
NONE
Scope
UNCHANGED
Confidentiality
HIGH
Integrity
NONE
Availability
LOW

Affected Products

VendorProductVersions
VllmVllm>= 0.15.1, < 0.17.0

Related Weaknesses (CWE)

References

FAQ

What is CVE-2026-25960?

CVE-2026-25960 is a vulnerability with a CVSS score of 7.1 (HIGH). 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...

How severe is CVE-2026-25960?

CVE-2026-25960 has been rated HIGH with a CVSS base score of 7.1/10. Review the CVSS metrics above for detailed severity breakdown.

Is there a patch for CVE-2026-25960?

Check the references section above for vendor advisories and patch information. Affected products include: Vllm Vllm.