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Security Scan Report: learn-desktop-en.wixstudio.com

Submitted: Apr 18, 2026, 7:29:43 PMCompleted: Apr 18, 2026, 7:30:59 PMpubliccompleted
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Summary

This website contacted 7 IPs in 1 country across 9 domains to perform 22 HTTP transactions. The main domain is learn-desktop-en.wixstudio.com and was registered NaN years ago.

Submitted URL: https://learn-desktop-en.wixstudio.com/en-desktop

AI Security Verdict

Moderate Risk

Confidence: 88%

5
Risk Score

The site impersonates Ledger's official download page on an unranked Wix subdomain, showing strong brand impersonation signs and suspicious JavaScript, indicating a high‑risk phishing/malware threat.

Risk Factors
Brand impersonation on unrelated, unranked domain
Suspicious JavaScript (eval and Function constructors)
Fake software download page without legitimate source
Unranked domain reputation
Safety Factors
No malicious Indicators of Compromise detected
No JavaScript malware YARA matches
No network IDS alerts
No credential or payment forms
Established domain (3409 days old) with no strong malicious indicators — risk clamped from 7 to 5
Domain age information unavailable

Details

Page Title

Ledger Live Desktop® — Starting Up Your Device® | Ledger™

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

documentation technical

(62%)

Domain Information

Domain 'learn-desktop-en.wixstudio.com' uses the commercial generic top-level domain (.com); it also runs on subdomain 'learn-desktop-en'. Its registrable label 'wixstudio' stretches across 9 characters with 4 vowels and five consonants. Word splitting yields three words: wi, x, studio. Expect two characters per word on average. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://learn-desktop-en.wixstudio.com/en-desktop

Page Load Overview

5.34s
Total Load Time
84
HTTP Requests
8
Domains
562 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

Language Code:en
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:en
Text Length:98 chars
Detector Agreement:67%

Website Classification

Primary Category

documentation technical62% confidence
Type: spa
Method: ml+structural

All Detected Categories

documentation technical
62%
technology software
35%
corporate
25%

Detected Features

OG: website

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
1265.8.131.125United States
AS16509Amazon.com, Inc.
1234.160.37.117Kansas City, Missouri, United States
AS396982Google LLC
1234.144.206.118Kansas City, Missouri, United States
AS396982Google LLC
12151.101.130.217United States
AS396982
1234.149.206.255Kansas City, Missouri, United States
AS396982Google LLC
1234.49.229.81Kansas City, Missouri, United States
AS396982Google LLC
1234.195.135.110Ashburn, Virginia, United States
AS14618Amazon.com, Inc.
847--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1A7648E74E301B57A4D6732AF6389B70C512DA0515D420B2EFAEC916406D7FE622F3B3A

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:Udz76TQ8IIxl8uZuHuftVcoskdBZVavKiWjebmlTK4weiwi+n4780IEWk12YcwC5:Udz7P8IYlvROhi+4we54A

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:333331:BHgggKAG1QwDahGAgphNyDFEDkQQBghYiAIqxBBtUAoUZHhaYBsBwluCIg0CEFgMFBUC1hGTHDiwgmBRCaARElU7ZgUgk5Tp

These hashes enable detection of similar websites and malware variants by comparing content similarity even when exact matches aren't found.

Image Hashes

Perceptual Hashes

Average Hash:81818f8b8f8181ff
Perceptual Hash:bb39e66a956cd011
Difference Hash:25595b5b5b594917
Wavelet Hash:95818f8b8f8181ff
Color Hash:#c5b587

Other Hashes

Crop Resistant:25595b5b5b594917,fef9e9e1e2e6e4e9,7430383c3cbc9cad,259a9a9a9adaca1b

Scan History

Scan history not available

Unable to load historical scan data