Security Scan Report: louaymardambekhugo-bgd6u9643s.edgeone.app

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Submitted: Completed: publiccompleted
This website contacted 7 IPs in 2 countries across 12 domains to perform 20 HTTP transactions. The main domain is edgeone.app and was registered 3 years 5 months ago.

Submitted URL: https://louaymardambekhugo-bgd6u9643s.edgeone.app/17615-how-to-clear-your-whatsapp-cache-to-keep-the-app-running-efficiently.html

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

AI Security Verdict

Moderate Risk

Confidence: 78%

5
Risk Score

The site is a low‑quality article about WhatsApp hosted on a newly created subdomain; no malicious activity is evident, but unknown age and low reputation warrant caution.

Risk Factors (4)
Unknown subdomain age (potentially brand new)
Low domain ranking in Cisco Umbrella
High JavaScript obfuscation score (indicative of heavy minification)
Brand name appears on a low‑reputation, non‑official domain
Safety Factors (5)
Page type is article (og:type="article"), not an impersonation login page
No credential or payment forms detected
No Indicators of Compromise matched in threat intel
No JavaScript malware YARA patterns
No network IDS alerts
Domain age information unavailable

Details

Page Title

How to clear your WhatsApp cache to keep the app running efficiently

Scan Type

public

Domain Name Analysis

The domain 'louaymardambekhugo-bgd6u9643s.edgeone.app' uses the application-focused generic top-level domain (.app) and includes subdomain 'louaymardambekhugo-bgd6u9643s'. The second-level label 'edgeone' is 7 characters long containing 4 vowels alongside 3 consonants. Word splitting yields two words: edge, one. Median word length comes out to 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://louaymardambekhugo-bgd6u9643s.edgeone.app/17615-how-to-clear-your-whatsapp-cache-to-keep-the-app-running-efficiently.html

Page Load Overview

11.97s
Total Load Time
128 KB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en-US
Text Length:3,644 chars
Detector Agreement:100%

Website Classification

Primary Category

social media network63% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

social media network
63%
technology software
62%
news media journalism
52%
corporate business
48%
adult content
39%

Detected Features

OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
8172.67.150.240United States
AS13335Cloudflare, Inc.
2104.20.23.96United States
AS13335Cloudflare, Inc.
2104.20.7.223United States
AS13335Cloudflare, Inc.
2101.33.10.57Frankfurt am Main, Hesse, Germany
2172.240.253.132United States
AS7979Servers.com, Inc.
2142.250.154.94United States
AS15169Google LLC
2142.251.127.95United States
AS15169Google LLC
207--

Detected Technologies3

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1D162A727F690113D3673135DB48DF2FC6A19806ED7078CF94499E32A96823EF29B55C4

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:XJ/hnYf8zX+TT03tJKJmJ/c2QfHMyVwPwDLkIM1SiM1LYYrWag4MDw:XJ/hnz+TT03HJU2QfHnVwPwDIIM1SiqZ

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:14647:A1DAhUTpEQxgg88FInQLoWYW9EAUYRAMAEqJJIEYVAgSiQSJAAAsD5CAIQQNEELAQzQQJDgRkgagAhkIViMIwCZOCwDMBkyr

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:e387838383c7ffff
Perceptual Hash:bc38c36665c3e949
Difference Hash:0f3c331f3f0fc802
Wavelet Hash:c38381818183ffff
Color Hash:#862d83

Other Hashes

Crop Resistant:0f3c331f3f0fc802

Scan History

Scan history not available

Unable to load historical scan data