Security Scan Report: macbahiahugo-zky39jw51p.edgeone.app

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Submitted: May 19, 2026, 4:30:03 AMCompleted: May 19, 2026, 4:31:26 AMpubliccompleted
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Summary

This website contacted 8 IPs in 2 countries across 8 domains to perform 15 HTTP transactions. The main domain is macbahiahugo-zky39jw51p.edgeone.app and was registered NaN years ago.

Submitted URL: https://macbahiahugo-zky39jw51p.edgeone.app/10920-22-astonishing-facts-about-lorel.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 to be a low‑risk article page; no phishing or malware indicators were found, but the subdomain is newly created and unranked.

Risk Factors
Unknown subdomain age (could be brand new)
Low Cisco Umbrella ranking for the domain
High JavaScript obfuscation score (common for minified code)
Presence of external analytics domains
Safety Factors
Page type is an article (og:type=article) with no brand impersonation claims
No forms or credential collection mechanisms
No malicious IoC or IDS alerts detected
No JavaScript malware signatures
Domain age information unavailable

Details

Page Title

22 Astonishing Facts About Lore'l

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

entertainment media

(87%)

Domain Information

The domain 'macbahiahugo-zky39jw51p.edgeone.app' uses the application-focused generic top-level domain (.app); it also runs on subdomain 'macbahiahugo-zky39jw51p'. The second-level label 'edgeone' is 7 characters long holding four vowels versus three consonants. It segments into 2 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://macbahiahugo-zky39jw51p.edgeone.app/10920-22-astonishing-facts-about-lorel.html

Page Load Overview

13.49s
Total Load Time
22
HTTP Requests
14
Domains
88 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:10,032 chars
Detector Agreement:100%

Website Classification

Primary Category

entertainment media87% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

entertainment media
87%
blog personal website
45%
government public service
45%
education learning
40%
corporate
35%

Detected Features

OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
8172.67.150.240United States
AS13335Cloudflare, Inc.
2142.251.13.95United States
AS15169Google LLC
2172.66.169.241United States
AS13335Cloudflare, Inc.
2172.240.108.76United States
AS7979Servers.com, Inc.
2188.114.97.3United States
AS13335Cloudflare, Inc.
243.152.26.58Singapore
2142.251.14.94United States
AS15169Google LLC
2104.20.7.223United States
AS13335Cloudflare, Inc.
228--

Detected Technologies3

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T15C922C23DF0712BC67A24254D24772AC7A6F883DE3464CF0A59FD3684B8A1D7613B69C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:jxhnYf8zX+PgJKJ8S8uzuU77EUkRiQ6EmufMY4KrWvhpdbYl4YYrWag4MDoqH:jxhnz+P6S8uzuU77dqp6EmufMphpdbYl

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:20400:OwFscFIPCSgOQdB4QEgEcAC9VkEAgBEzTCIkhADQIhAonEOaQDlFIuQZQNR6iKAiOaaGDNKrJHgAWuCkHgJAMIIi+4CQCuAk

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:3c00383c3c3c3c3c
Perceptual Hash:c267cd339cb29c32
Difference Hash:c9cbd1c1c9d1c9f1
Wavelet Hash:3d203c3c3c3c7c7c
Color Hash:#2da3d2

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data