Security Scan Report: sweetmusicgearsitus-raly23vq74.edgeone.app

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Submitted: May 23, 2026, 9:39:13 AMCompleted: May 23, 2026, 9:40:31 AMpubliccompleted
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Summary

This website contacted 8 IPs in 2 countries across 8 domains to perform 11 HTTP transactions. The main domain is sweetmusicgearsitus-raly23vq74.edgeone.app and was registered NaN years ago.

Submitted URL: https://sweetmusicgearsitus-raly23vq74.edgeone.app/23633-who-was-ahoufe-tiktok-star-known-as-ghanaian-tupac-dies-hours-after-16-hour-livestreaming.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

Moderate risk due to unknown subdomain age, low ranking, and brand mentions; no malicious activity detected.

Risk Factors
Unknown subdomain age
Low domain ranking
Brand mentions without matching domain
High JavaScript obfuscation score
Safety Factors
No forms collecting credentials or payments
No malicious Indicators of Compromise
No network IDS alerts
Page marked as an article (og:type) indicating informational content
Domain age information unavailable

Details

Page Title

Who was Ahoufe? TikTok star known as Ghanaian Tupac dies hours after 16-hour livestreaming

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

social media network

(57%)

Domain Information

Domain 'sweetmusicgearsitus-raly23vq74.edgeone.app' uses the application-focused generic top-level domain (.app); it also runs on subdomain 'sweetmusicgearsitus-raly23vq74'. The second-level label 'edgeone' is 7 characters long split between 4 vowels and three consonants. Segmentation suggests 2 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://sweetmusicgearsitus-raly23vq74.edgeone.app/23633-who-was-ahoufe-tiktok-star-known-as-ghanaian-tupac-dies-hours-after-16-hour-livestreaming.html

Page Load Overview

11.23s
Total Load Time
18
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:3,370 chars
Detector Agreement:100%

Website Classification

Primary Category

social media network57% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

social media network
57%
corporate
35%

Detected Features

OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
4192.178.183.94United States
AS15169Google LLC
2142.251.13.95United States
AS15169Google LLC
2104.21.0.120United States
AS13335Cloudflare, Inc.
243.152.26.58Singapore
2104.20.8.223United States
AS13335Cloudflare, Inc.
2172.240.108.76United States
AS7979Servers.com, Inc.
2104.20.23.96United States
AS13335Cloudflare, Inc.
2104.18.11.207United States
AS13335Cloudflare, Inc.
188--

Detected Technologies4

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1D462F973F984013C1722838565DAB3BCF9B98027D741CAF57899AB394BC76CB493A684

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:brgqMLhnYf8zX+6MJ/cHyh5UkrmrzYTdag4lDw:bQLhnz+6MJUHyuYTdag4xw

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:14816:IoKZAMCQQdYZLAcwMgkAIqCheRoIwjwSWAQJxVAIVLpDEDTJIQUMMgk9AYoJgCCQi0zqZRwQDkQAMACAMQGsOlmGAOQTAEZQ

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:81c7c3c3c3c7ffff
Perceptual Hash:b438cb2a6ecf034e
Difference Hash:07161e16161e0002
Wavelet Hash:00c2c2c2c3c3fefe
Color Hash:#3a5f78

Other Hashes

Crop Resistant:07161e16161e0002

Scan History

Scan history not available

Unable to load historical scan data