CVE-2026-109227: SGLang through 0.5.21 Memory Exhaustion DoS via Qwen-VL Video Preprocessing

Published Oct 12, 2026
·
Updated

SGLang through 0.5.21 contains an unbounded memory allocation vulnerability in preprocessvideo in qwenvl.py that decodes frames at full source resolution before applying maxpixels limits. Remote attackers can submit high-resolution videos to /v1/chat/completions on Qwen-VL deployments, and concurrent requests exhaust worker memory causing denial of service.

Affected Software

1 affected component
SGLang SGLang<=0.5.21

Event History

Oct 12, 2026
CVE Published
via MITRE·02:04 PM
Data Sourced
via MITRE·02:04 PM
DescriptionSeverityWeakness
Data Sourced
via NVD·02:17 PM
DescriptionSeverityWeakness

Frequently Asked Questions

1

Which deployments are exposed to this issue?

Deployments using Qwen-VL through the affected SGLang versions are exposed if their /v1/chat/completions endpoint accepts video inputs. The issue is in Qwen-VL video preprocessing.

2

What does an attacker need to exploit it?

An attacker only needs network access to submit high-resolution videos to /v1/chat/completions. No privileges or user interaction are required.

3

Does limiting max_pixels prevent exploitation?

No. Frames are decoded at their full source resolution before max_pixels limits are applied, so the limit does not prevent the vulnerable memory allocation.

4

What is the operational impact?

Concurrent malicious video requests can exhaust worker memory and cause a denial of service. The available information does not indicate confidentiality or integrity impact.

Contact

SecAlerts Pty Ltd.
132 Wickham Terrace
Fortitude Valley,
QLD 4006, Australia
info@secalerts.co
By using SecAlerts services, you agree to our services end-user license agreement. This website is safeguarded by reCAPTCHA and governed by the Google Privacy Policy and Terms of Service. All names, logos, and brands of products are owned by their respective owners, and any usage of these names, logos, and brands for identification purposes only does not imply endorsement. If you possess any content that requires removal, please get in touch with us.
© 2026 SecAlerts Pty Ltd.
ABN: 70 645 966 203, ACN: 645 966 203