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CVE-2026-5497 vLLM versions 0.8.0 and later are vulnerable to an Out-of-Memory (OOM) Denial of Service (DoS) attack due to unbounded…

Description

vLLM versions 0.8.0 and later are vulnerable to an Out-of-Memory (OOM) Denial of Service (DoS) attack due to unbounded frame count processing in the `VideoMediaIO.load_base64()` method. When processing `video/jpeg` data URLs, the method splits the base64 data string on commas to extract individual JPEG frames without enforcing a frame count limit. An attacker can exploit this by crafting a single API request containing thousands of comma-separated base64-encoded JPEG frames in a data URL, causing the server to decode all frames into memory and crash due to excessive memory consumption. This vulnerability is reachable via the OpenAI-compatible chat completions API and does not require authentication.

Produits et versions touchés

Produit Versions touchées Corrigé en
vllm-project/vllm 0.19 premières → < 0.19.0 0.19.0
Red Hat AI Inference Server Versions non publiées
Red Hat Enterprise Linux AI (RHEL AI) 3 Versions non publiées
Red Hat OpenShift AI (RHOAI) Versions non publiées
Red Hat Enterprise Linux AI 3.4 Versions non publiées

Références

Chronologie

  1. Publiée
  2. Dernière modification
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