Security Scan Report: typhoonhubsitus-oxahyjfjak.edgeone.app

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Submitted: May 22, 2026, 11:35:47 AMCompleted: May 22, 2026, 11:38:30 AMpubliccompleted
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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 typhoonhubsitus-oxahyjfjak.edgeone.app and was registered NaN years ago.

Submitted URL: https://typhoonhubsitus-oxahyjfjak.edgeone.app/11308-who-is-rhoc-noella-bergeners-husband-sweet-james-bergener-thu-9-december-2021-1429.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 shows moderate risk due to unknown subdomain age, low reputation, and obfuscated JavaScript, but lacks malicious payloads or credential harvesting.

Risk Factors
Unknown subdomain age
Low domain reputation
High JS obfuscation without clear purpose
Safety Factors
No malicious Indicators of Compromise detected
No forms or credential collection
No JavaScript malware patterns
No network IDS alerts
Domain age information unavailable

Details

Page Title

Who is RHOC Noella Bergeners husband, Sweet James Bergener? Thu 9 December 2021 14:29

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

entertainment media

(52%)

Domain Information

The domain name 'typhoonhubsitus-oxahyjfjak.edgeone.app' uses the application-focused generic top-level domain (.app), featuring subdomain 'typhoonhubsitus-oxahyjfjak'. Count 7 characters in 'edgeone' with 4 vowels and three consonants. It segments into two words: edge, one. Expect 3.5 characters per word on average. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://typhoonhubsitus-oxahyjfjak.edgeone.app/11308-who-is-rhoc-noella-bergeners-husband-sweet-james-bergener-thu-9-december-2021-1429.html

Page Load Overview

90.16s
Total Load Time
17
HTTP Requests
13
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:3,039 chars
Detector Agreement:60%

Website Classification

Primary Category

entertainment media52% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

entertainment media
52%
adult content
35%
corporate
35%
documentation technical
25%

Detected Features

OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
3142.251.110.94United States
AS15169Google LLC
2104.21.0.120United States
AS13335Cloudflare, Inc.
2101.33.10.10Frankfurt am Main, Hesse, Germany
2104.20.8.223United States
AS13335Cloudflare, Inc.
2172.66.169.241United States
AS13335Cloudflare, Inc.
2104.18.10.207United States
AS13335Cloudflare, Inc.
2172.240.253.132United States
AS7979Servers.com, Inc.
274.125.29.95United States
AS15169Google LLC
178--

Detected Technologies4

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T154521A33AA81103CEA1212A594C1B3BC7D39D836E345CCFA79DDF32687C6AC799655C8

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:brgqMzuhnYf8zX+jUmrCJ/ctPlrNye9PpCsPRaSZ2zYTdag4lDw:bQyhnz+jOJU5yQPpCVYTdag4xw

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:14468:AFggECSQwtMLJEEiQWAAJxCCQqVinIuSAEUAzlVZWSJTE8gZuD2gFmgiCwmNoDAYREAYwR6JCACwASBIIIGmM0hCAIKAAE4l

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:c3c3c3c3c3ffffff
Perceptual Hash:b430cbc764c7c366
Difference Hash:96161e1616160002
Wavelet Hash:c282c282c2cefefe
Color Hash:#5540bf

Other Hashes

Crop Resistant:96161e1616160002

Scan History

Scan history not available

Unable to load historical scan data