7.5
High
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.
Affected products and versions
| Product | Affected versions | Fixed in |
|---|---|---|
| vllm-project/vllm 0.19 | earliest → < 0.19.0 | 0.19.0 |
| Red Hat AI Inference Server | Versions not published | |
| Red Hat Enterprise Linux AI (RHEL AI) 3 | Versions not published | |
| Red Hat OpenShift AI (RHOAI) | Versions not published | |
| Red Hat Enterprise Linux AI 3.4 | Versions not published |
References
- huntr.com huntr.com
- github.com github.com
Timeline
- Published
- Last modified
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