CVE-2026-34753

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 downloadbytesfromurl allows any actor who can control batch input JSON to make the vLLM batch runner issue arbitrary HTTP/HTTPS requests from t...

CVE-2026-34753 vLLM affected by Server-Side Request Forgery (SSRF) in `download_bytes_from_url `

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 downloadbytesfromurl allows any actor who can control batch input JSON to make the vLLM batch runner issue arbitrary HTTP/HTTPS requests from t...

CVE-2026-34753 vLLM affected by Server-Side Request Forgery (SSRF) in `download_bytes_from_url `

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 downloadbytesfromurl allows any actor who can control batch input JSON to make the vLLM batch runner issue arbitrary HTTP/HTTPS requests from t...

vLLM: Server-Side Request Forgery (SSRF) in `download_bytes_from_url `

Summary A Server Side Request Forgery SSRF vulnerability in downloadbytesfromurl 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...

Server-side Request Forgery (SSRF)

Overview vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs Affected versions of this package are vulnerable to Server-side Request Forgery SSRF via the downloadbytesfromurl function. An attacker can cause the server to make arbitrary HTTP or HTTPS requests to...