Security Scan Report: andoidmarketsitus-cv0nwlbgwj.edgeone.app

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Submitted: May 22, 2026, 9:35:44 PMCompleted: May 22, 2026, 9:38:21 PMpubliccompleted
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Summary

This website contacted 8 IPs in 2 countries across 8 domains to perform 12 HTTP transactions. The main domain is andoidmarketsitus-cv0nwlbgwj.edgeone.app and was registered NaN years ago.

Submitted URL: https://andoidmarketsitus-cv0nwlbgwj.edgeone.app/16661-19-best-royal-christmas-gifts-what-to-buy-fans-of-queen-elizabeth-kate-middleton-meghan-markle.html

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

AI Security Verdict

Low Risk

Confidence: 78%

2
Risk Score

The site appears low risk with no malicious forms or IoCs, but its unknown subdomain age and low ranking suggest cautious browsing.

Risk Factors
Low domain reputation (rank > 100K)
Unknown subdomain age on a hosting platform
Safety Factors
No credential or payment collection forms
Page marked as an article (og:type="article") – no brand impersonation
No malicious JavaScript patterns detected
Domain age information unavailable

Details

Page Title

19 best royal Christmas gifts: What to buy fans of Queen Elizabeth, Kate Middleton & Meghan Markle

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

corporate

(35%)

Domain Information

You're looking at domain 'andoidmarketsitus-cv0nwlbgwj.edgeone.app' on the application-focused generic top-level domain (.app); it also runs on subdomain 'andoidmarketsitus-cv0nwlbgwj'. Count 7 characters in 'edgeone' containing 4 vowels alongside 3 consonants. Segmentation suggests two words: edge, one. Average segment length settles at 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://andoidmarketsitus-cv0nwlbgwj.edgeone.app/16661-19-best-royal-christmas-gifts-what-to-buy-fans-of-queen-elizabeth-kate-middleton-meghan-markle.html

Page Load Overview

90.14s
Total Load Time
15
HTTP Requests
11
Domains
33 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-US
Text Length:7,296 chars
Detector Agreement:100%

Website Classification

Primary Category

corporate35% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

corporate
35%
e-commerce shopping
29%

Detected Features

OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
8101.33.10.10Frankfurt am Main, Hesse, Germany
1142.251.110.94United States
AS15169Google LLC
1142.250.154.95United States
AS15169Google LLC
1104.21.0.120United States
AS13335Cloudflare, Inc.
1104.20.23.96United States
AS13335Cloudflare, Inc.
1172.240.108.84United States
AS7979Servers.com, Inc.
1104.18.11.207United States
AS13335Cloudflare, Inc.
1104.20.7.223United States
AS13335Cloudflare, Inc.
158--

Detected Technologies4

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1DB822B27E640133C167343D274CEB7BC793AC43AA362C891A6E993784BC26DB5975BC4

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:brgqM0rhnYf8zX+a/Z06ZyXAJ/cB5dyc6IiuowdNakOxZlY5cLY1zYTdag4lDw:bQ0rhnz+a/Z06ZyXAJUB5dyAPtiAYTdd

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:18908:SWhCwgoSIIkLRcRhAZAVP9CcViTlGgiKCQWEALSKxIAFMBAICoCKQmilGfnYngMQAqAyaTH4QYCQhKAVJAASFAgKS4Iha34A

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:c3cfc3c3c3c3c3c7
Perceptual Hash:b5198a2a4f6ecf0a
Difference Hash:371e16161e161616
Wavelet Hash:81c3c3c3c3c3c3cf
Color Hash:#7ad22d

Other Hashes

Crop Resistant:371e16161e161616

Scan History

Scan history not available

Unable to load historical scan data