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Security Scan Report: net-fuchsia-xloydglv1n-7m4l61musz.edgeone.app

Submitted: Mar 1, 2026, 10:59:30 PMCompleted: Mar 1, 2026, 11:00:51 PMpubliccompleted
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Summary

This website contacted 1 IP in 1 country across 1 domain to perform 1 HTTP transaction. The main domain is net-fuchsia-xloydglv1n-7m4l61musz.edgeone.app and was registered NaN years ago.

Submitted URL: https://net-fuchsia-xloydglv1n-7m4l61musz.edgeone.app/

The Cisco Umbrella rank of the primary domain is #455,732 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 92%

0
Risk Score

No suspicious activity detected; the site appears to be a simple, harmless file collection.

Safety Factors
Hosted on a known platform (edgeone.app) with no suspicious activity
No credential or payment forms present
No brand impersonation or phishing content
No external links or redirects
Domain age information unavailable

Details

Page Title

Files Collection

Scan Type

public

Language

🇺🇸

English

(50% confidence)

Category

healthcare medical

(67%)

Domain Information

Domain 'net-fuchsia-xloydglv1n-7m4l61musz.edgeone.app' uses the application-focused generic top-level domain (.app); it also runs on subdomain 'net-fuchsia-xloydglv1n-7m4l61musz'. Its registrable label 'edgeone' stretches across 7 characters split between 4 vowels and three consonants. Tokenizing the label suggests two words: edge, one. The median word length lands at 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://net-fuchsia-xloydglv1n-7m4l61musz.edgeone.app/

Page Load Overview

0.74s
Total Load Time
2
HTTP Requests
1
Domains
7 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:50%
Script:Latin
Direction:ltr

Detection Details

Language Code:en
Detection Confidence:50%
Script Type:Latin
HTML Lang Attribute:zh
Text Length:842 chars
Detector Agreement:100%
Language mismatch: Declared as zh but detected as en

Website Classification

Primary Category

healthcare medical67% confidence
Type: static
Method: ml+structural

All Detected Categories

healthcare medical
67%
news media journalism
61%
adult content
52%
cryptocurrency blockchain
51%
documentation technical
51%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
243.152.26.58Singapore
AS139341ACE
21--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1C6F21080EFF82ADCA42FC164876D7B3B6A34A013A54D168D759E0EB0DF48589B0BF175

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:shNIMi+HK828icmc6eMeAWUmA+csqcGMScG8qd:wNIqHK828icmc6eMeAWUmA+csqcGMScI

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:35248:MEGhgkQEKdZSJAg4a2oqGCpiYCEKQhgwA1oCQQiqGDORIKGMqkmA2CQo/JOKANEcgARg3WEiIGGABgEqjEIsiQgQOlbQBDVU

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:9c1c1c1c1c1c1c1c
Perceptual Hash:da756c282879c3e3
Difference Hash:3030303031313171
Wavelet Hash:dcfcbc3c1c1c1c1c
Color Hash:#3e931f

Other Hashes

Crop Resistant:3030303031313171

Scan History

Scan history not available

Unable to load historical scan data