Nixpkgs security tracker
5.4 MEDIUM
- CVSS version (CVSS): 3.1
- Attack Vector (AV): Network (N)
- Attack Complexity (AC): Low (L)
- Privileges Required (PR): Low (L)
- User Interaction (UI): None (N)
- Scope (S): Unchanged (U)
- Confidentiality (C): Low (L)
- Integrity (I): None (N)
- Availability (A): Low (L)
- Modified Attack Vector (MAV): Network (N)
- Modified Attack Complexity (MAC): Low (L)
- Modified Privileges Required (MPR): Low (L)
- Modified User Interaction (MUI): None (N)
- Modified Confidentiality (MC): Low (L)
- Modified Scope (MS): Unchanged (U)
- Modified Integrity (MI): None (N)
- Modified Availability (MA): Low (L)
Activity log
- Created suggestion
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 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.
References
-
https://github.com/vllm-project/vllm/security/advisories/GHSA-pf3h-qjgv-vcpr x_refsource_CONFIRM
Affected products
- ==>= 0.16.0, < 0.19.0
Matching in nixpkgs
pkgs.vllm
High-throughput and memory-efficient inference and serving engine for LLMs
pkgs.pkgsRocm.vllm
High-throughput and memory-efficient inference and serving engine for LLMs
pkgs.python312Packages.vllm
High-throughput and memory-efficient inference and serving engine for LLMs
pkgs.python313Packages.vllm
High-throughput and memory-efficient inference and serving engine for LLMs
Package maintainers
-
@CertainLach Yaroslav Bolyukin <iam@lach.pw>
-
@happysalada Raphael Megzari <raphael@megzari.com>
-
@daniel-fahey Daniel Fahey <daniel.fahey+nixpkgs@pm.me>