Nixpkgs security tracker
6.5 MEDIUM
- CVSS version: 3.1
- Attack vector (AV): NETWORK
- Attack complexity (AC): LOW
- Privileges required (PR): LOW
- User interaction (UI): NONE
- Scope (S): UNCHANGED
- Confidentiality impact (C): NONE
- Integrity impact (I): NONE
- Availability impact (A): HIGH
vLLM Affected by Denial of Service via Unbounded Frame Count in video/jpeg Base64 Processing
vLLM is an inference and serving engine for large language models (LLMs). From 0.7.0 to before 0.19.0, the VideoMediaIO.load_base64() method at vllm/multimodal/media/video.py splits video/jpeg data URLs by comma to extract individual JPEG frames, but does not enforce a frame count limit. The num_frames parameter (default: 32), which is enforced by the load_bytes() code path, is completely bypassed in the video/jpeg base64 path. An attacker can send a single API request containing thousands of comma-separated base64-encoded JPEG frames, causing the server to decode all frames into memory and crash with OOM. This vulnerability is fixed in 0.19.0.
References
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https://github.com/vllm-project/vllm/security/advisories/GHSA-pq5c-rjhq-qp7p x_refsource_CONFIRM
Affected products
- ==>= 0.7.0, < 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
-
@happysalada Raphael Megzari <raphael@megzari.com>
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@CertainLach Yaroslav Bolyukin <iam@lach.pw>
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@daniel-fahey Daniel Fahey <daniel.fahey+nixpkgs@pm.me>