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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History
Tue, 07 Apr 2026 00:00:00 +0000
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threat_severity
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Mon, 06 Apr 2026 16:45:00 +0000
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| 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. | |
| Title | vLLM affected by Server-Side Request Forgery (SSRF) in `download_bytes_from_url ` | |
| Weaknesses | CWE-918 | |
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cvssV3_1
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Status: PUBLISHED
Assigner: GitHub_M
Published: 2026-04-06T15:36:52.942Z
Updated: 2026-04-06T15:36:52.942Z
Reserved: 2026-03-30T19:17:10.225Z
Link: CVE-2026-34753
No data.
Status : Received
Published: 2026-04-06T16:16:36.307
Modified: 2026-04-06T16:16:36.307
Link: CVE-2026-34753