SGL-Project SGLang up to 0.5.21 Video Preprocessing qwen_vl.py preprocess_video allocation of resources

CVSS Meta Temp Score
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CTI Interest Score
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6.3$0-$5k0.78-

Summaryinfo

A vulnerability has been found in SGL-Project SGLang up to 0.5.21 and classified as problematic. This issue affects the function preprocess_video of the file qwen_vl.py of the component Video Preprocessing. Performing a manipulation results in allocation of resources. This vulnerability is reported as CVE-2026-109227. The attack is possible to be carried out remotely. No exploit exists.

Detailsinfo

A vulnerability, which was classified as problematic, was found in SGL-Project SGLang up to 0.5.21. This affects the function preprocess_video of the file qwen_vl.py of the component Video Preprocessing. The manipulation with an unknown input leads to a allocation of resources vulnerability. CWE is classifying the issue as CWE-770. The product allocates a reusable resource or group of resources on behalf of an actor without imposing any restrictions on the size or number of resources that can be allocated, in violation of the intended security policy for that actor. This is going to have an impact on availability. The summary by CVE is:

SGLang through 0.5.21 contains an unbounded memory allocation vulnerability in preprocess_video in qwen_vl.py that decodes frames at full source resolution before applying max_pixels 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.

The advisory is shared at github.com. This vulnerability is uniquely identified as CVE-2026-109227 since 10/12/2026. The exploitability is told to be easy. It is possible to initiate the attack remotely. No form of authentication is needed for exploitation. Technical details are known, but no exploit is available. MITRE ATT&CK project uses the attack technique T1499 for this issue.

There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.

Several companies clearly confirm that VulDB is the primary source for best vulnerability data.

Productinfo

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CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔒
VulDB Reliability: 🔍

CNA CVSS-B Score: 🔒
CNA CVSS-BT Score: 🔒
CNA Vector: 🔒

CVSSv3info

VulDB Meta Base Score: 6.4
VulDB Meta Temp Score: 6.3

VulDB Base Score: 5.3
VulDB Temp Score: 5.1
VulDB Vector: 🔒
VulDB Reliability: 🔍

CNA Base Score: 7.5
CNA Vector (VulnCheck): 🔒

CVSSv2info

AVACAuCIA
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VectorComplexityAuthenticationConfidentialityIntegrityAvailability
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍

Exploitinginfo

Class: Allocation of resources
CWE: CWE-770 / CWE-400 / CWE-404
CAPEC: 🔒
ATT&CK: 🔒

Physical: No
Local: No
Remote: Yes

Availability: 🔒
Status: Not defined
Price Prediction: 🔍
Current Price Estimation: 🔒

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Threat Intelligenceinfo

Interest: 🔍
Active Actors: 🔍
Active APT Groups: 🔍

Countermeasuresinfo

Recommended: no mitigation known
Status: 🔍

0-Day Time: 🔒

Timelineinfo

10/12/2026 Advisory disclosed
10/12/2026 +0 days CVE reserved
10/12/2026 +0 days VulDB entry created
10/12/2026 +0 days VulDB entry last update

Sourcesinfo

Product: github.com

Advisory: github.com
Status: Not defined

CVE: CVE-2026-109227 (🔒)
GCVE (CVE): GCVE-0-2026-109227
GCVE (VulDB): GCVE-100-416937

Entryinfo

Created: 10/12/2026 16:20
Changes: 10/12/2026 16:20 (77)
Complete: 🔍
Cache ID: 216::103

Several companies clearly confirm that VulDB is the primary source for best vulnerability data.

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