6.5 MEDIUM
- CVSS version (CVSS): 3.1
- Attack Vector (AV): Network (N)
- Attack Complexity (AC): High (H)
- Privileges Required (PR): None (N)
- User Interaction (UI): None (N)
- Scope (S): Unchanged (U)
- Confidentiality (C): Low (L)
- Integrity (I): High (H)
- Availability (A): None (N)
- Modified Attack Vector (MAV): Network (N)
- Modified Attack Complexity (MAC): High (H)
- Modified Privileges Required (MPR): None (N)
- Modified User Interaction (MUI): None (N)
- Modified Confidentiality (MC): Low (L)
- Modified Scope (MS): Unchanged (U)
- Modified Integrity (MI): High (H)
- Modified Availability (MA): None (N)
Activity log
- Created suggestion
vLLM: Artifact Pin Decay in vLLM allows pinned deployments to load unpinned code, weights, and processors
vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.22.0, vLLM's revision pinning controls do not consistently apply to all artifacts loaded for a model. A deployment that supplies --revision or --code-revision can still load dynamic code, GGUF files, image processors, retrieval side weights, or same-repository subfolder weights/config from an unpinned/default revision. This is a supply-chain integrity issue for pinned vLLM deployments. Operators can believe they are serving a reviewed model revision while vLLM resolves behavior-affecting nested or sibling artifacts outside that reviewed revision. This vulnerability is fixed in 0.22.0.
References
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https://github.com/vllm-project/vllm/security/advisories/GHSA-3ww4-5jv9-j5gm x_refsource_CONFIRM
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https://github.com/vllm-project/vllm/pull/42616 x_refsource_MISC
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https://huntr.com/bounties/3f1e24c0-87d2-4f6c-a705-820f380879ac x_refsource_MISC
Affected products
- ==< 0.22.0
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
None
pkgs.python313Packages.vllm
High-throughput and memory-efficient inference and serving engine for LLMs
Package maintainers
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@happysalada Raphael Megzari <raphael@megzari.com>
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@CertainLach Yaroslav Bolyukin <iam@lach.pw>
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@LunNova Luna Nova <nixpkgs-maintainer@lunnova.dev>
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@daniel-fahey Daniel Fahey <daniel.fahey+nixpkgs@pm.me>