CVE-2026-34753
Published: Apr 6, 2026
Modified: Apr 7, 2026
CVSS v3.1
5.4
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.
| Vendor | Product | Versions |
|---|---|---|
vllm-project | vllm | affected >= 0.16.0, < 0.19.0 |
Weaknesses (CWE)
CVSS v3.1 Details
CVSS v3.1 Vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:L
Attack Vector
Attack Complexity
Privileges Required
User Interaction
Scope
Confidentiality
Integrity
Availability
References
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