Webkul QloApps up to 1.7.0 Hotel Reservation System child_features cross site scripting
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 4.4 | $0-$5k | 0.00 |
Summary
A vulnerability marked as problematic has been reported in Webkul QloApps up to 1.7.0. Affected by this issue is some unknown functionality of the component Hotel Reservation System. This manipulation of the argument child_features causes cross site scripting. The identification of this vulnerability is CVE-2026-92234. It is possible to initiate the attack remotely. There is no exploit available.
Details
A vulnerability has been found in Webkul QloApps up to 1.7.0 and classified as problematic. Affected by this vulnerability is an unknown code of the component Hotel Reservation System. The manipulation of the argument child_features with an unknown input leads to a cross site scripting vulnerability. The CWE definition for the vulnerability is CWE-79. The product does not neutralize or incorrectly neutralizes user-controllable input before it is placed in output that is used as a web page that is served to other users. As an impact it is known to affect integrity. The summary by CVE is:
QloApps through 1.7.0 reflects unescaped child feature names into back-office validation error messages in the Hotel Reservation System feature management page. Authenticated back-office users who follow a crafted link can execute injected JavaScript in their administrative session via the child_features parameter.
It is possible to read the advisory at github.com. This vulnerability is known as CVE-2026-92234 since 09/15/2026. The exploitation appears to be easy. The attack can be launched remotely. It demands that the victim is doing some kind of user interaction. Technical details of the vulnerability are known, but there is no available exploit. The attack technique deployed by this issue is T1059.007 according to MITRE ATT&CK.
There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
Product
Vendor
Name
Version
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔒VulDB Reliability: 🔍
CNA CVSS-B Score: 🔒
CNA CVSS-BT Score: 🔒
CNA Vector: 🔒
CVSSv3
VulDB Meta Base Score: 4.4VulDB Meta Temp Score: 4.4
VulDB Base Score: 3.5
VulDB Temp Score: 3.4
VulDB Vector: 🔒
VulDB Reliability: 🔍
CNA Base Score: 5.4
CNA Vector (VulnCheck): 🔒
CVSSv2
| AV | AC | Au | C | I | A |
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| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍
Exploiting
Class: Cross site scriptingCWE: CWE-79 / CWE-94 / CWE-74
CAPEC: 🔒
ATT&CK: 🔒
Physical: No
Local: No
Remote: Yes
Availability: 🔒
Status: Not defined
Price Prediction: 🔍
Current Price Estimation: 🔒
| 0-Day | Unlock | Unlock | Unlock | Unlock |
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| Today | Unlock | Unlock | Unlock | Unlock |
Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: no mitigation knownStatus: 🔍
0-Day Time: 🔒
Timeline
09/15/2026 Advisory disclosed09/15/2026 CVE reserved
09/15/2026 VulDB entry created
09/15/2026 VulDB entry last update
Sources
Advisory: github.comStatus: Not defined
CVE: CVE-2026-92234 (🔒)
GCVE (CVE): GCVE-0-2026-92234
GCVE (VulDB): GCVE-100-404779
Entry
Created: 09/15/2026 23:15Changes: 09/15/2026 23:15 (75)
Complete: 🔍
Cache ID: 216::103
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
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