Security Scan Report: modelmathgurufave-p2mghysenw.edgeone.app

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Submitted: May 21, 2026, 8:07:41 PMCompleted: May 21, 2026, 8:10:21 PMpubliccompleted
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Summary

This website contacted 9 IPs in 2 countries across 9 domains to perform 13 HTTP transactions. The main domain is modelmathgurufave-p2mghysenw.edgeone.app and was registered NaN years ago.

Submitted URL: https://modelmathgurufave-p2mghysenw.edgeone.app/21009-10-times-asian-stars-won-halloween-with-iconic-costumes-from-blackpinks-lisa-as-the-squid-game-d.html

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

AI Security Verdict

High Risk

Confidence: 92%

7
Risk Score

The site reports on popular brands but lacks forms; unknown subdomain age and a malicious external link raise high risk.

Risk Factors
External malicious link (Indicators of Compromise)
Unranked/low‑rank domain claiming major brands
Unknown subdomain age on a hosting platform
High JS obfuscation without clear malicious behavior
Domain age information unavailable

Details

Page Title

10 times Asian stars won Halloween with iconic costumes, from Blackpinks Lisa as the Squid Game d

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

corporate

(35%)

Domain Information

The domain name 'modelmathgurufave-p2mghysenw.edgeone.app' uses the application-focused generic top-level domain (.app) and includes subdomain 'modelmathgurufave-p2mghysenw'. The second-level label 'edgeone' is 7 characters long containing four vowels alongside 3 consonants. Tokenizing the label 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://modelmathgurufave-p2mghysenw.edgeone.app/21009-10-times-asian-stars-won-halloween-with-iconic-costumes-from-blackpinks-lisa-as-the-squid-game-d.html

Page Load Overview

90.13s
Total Load Time
16
HTTP Requests
11
Domains
31 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:4,539 chars
Detector Agreement:100%

Website Classification

Primary Category

corporate35% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

corporate
35%
entertainment media
29%

Detected Features

OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
8104.18.11.207United States
AS13335Cloudflare, Inc.
1172.67.150.240United States
AS13335Cloudflare, Inc.
1172.240.108.76United States
AS7979Servers.com, Inc.
1104.20.7.223United States
AS13335Cloudflare, Inc.
1142.251.127.95United States
AS15169Google LLC
1101.33.10.10Frankfurt am Main, Hesse, Germany
1172.240.253.132United States
AS7979Servers.com, Inc.
1172.66.169.241United States
AS13335Cloudflare, Inc.
1142.251.110.94United States
AS15169Google LLC
169--

Detected Technologies4

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1237209ABEF81123817324395908973FC7A2D4821F7434BE5759CB72E6BC92E75932A24

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:brgqMThnYf8zX+EwiLTlMtESJ/cov17BWde4g9xV3aY5mag4gDw:bQThnz+weJUgpBWde4g/VqY5mag48w

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:16278:COAQCiC0GpaLDojIgjAYqICCyAxAiWgaIaECiGCC0H+T0QAwKQQiFwCko8wKkHwQQIj04XrhYBSQIQJiaPQsHhwA0QNhIFoJ

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:83c7c3c3c3c3c3ff
Perceptual Hash:b53b8b38cb6c43c8
Difference Hash:0b1e1616161e3612
Wavelet Hash:81c3c3c3c2c2c2ff
Color Hash:#573a78

Other Hashes

Crop Resistant:0b1e1616161e3612

Scan History

Scan history not available

Unable to load historical scan data