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With package: vllm

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Permalink CVE-2026-55646
6.5 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): None (N)
  • Integrity (I): None (N)
  • Availability (A): High (H)
  • 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): None (N)
  • Modified Scope (MS): Unchanged (U)
  • Modified Integrity (MI): None (N)
  • Modified Availability (MA): High (H)
updated 1 month, 2 weeks ago by @LeSuisse Activity log
  • Created suggestion
  • @LeSuisse dismissed
vLLM speech-to-text endpoints allocate full upload before enforcing the audio file-size limit

vLLM is an inference and serving engine for large language models. From 0.22.0 to 0.23.0, the /v1/audio/transcriptions and /v1/audio/translations routes call request.file.read() to fully materialize an uploaded audio file into memory before vLLM checks the documented VLLM_MAX_AUDIO_CLIP_FILESIZE_MB compressed upload size limit (default 25 MB) later in the speech-to-text preprocessing step, so an API caller who can reach those routes can submit an oversized multipart upload and cause vLLM to allocate memory proportional to the uploaded file size before the request is rejected as too large, creating memory pressure or terminating the process depending on deployment resource limits. This issue is fixed in version 0.24.0.

Affected products

vllm
  • ==>= 0.22.0, < 0.24.0

Matching in nixpkgs

pkgs.vllm

High-throughput and memory-efficient inference and serving engine for LLMs

We are using an older version.