Security Scan Report: hurt-green-mk22pucutk-wd331i7k7x.edgeone.app

Submitted: Feb 23, 2026, 7:39:55 AMCompleted: Feb 23, 2026, 7:41:24 AMpubliccompleted
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Summary

This website contacted 1 IP in 1 country across 1 domain to perform 4 HTTP transactions. The main domain is hurt-green-mk22pucutk-wd331i7k7x.edgeone.app and was registered NaN years ago.

Submitted URL: https://hurt-green-mk22pucutk-wd331i7k7x.edgeone.app/

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

AI Security Verdict

AI analysis unavailable for this scan

Details

Page Title

Sonolus Chart Copier

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

technology software

(32%)

Domain Information

Within the application-focused generic top-level domain (.app), 'hurt-green-mk22pucutk-wd331i7k7x.edgeone.app' is registered, featuring subdomain 'hurt-green-mk22pucutk-wd331i7k7x'. The core label 'edgeone' covers 7 characters split between four vowels and three consonants. Tokenizing the label suggests two words: edge, one. Median word length is 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://hurt-green-mk22pucutk-wd331i7k7x.edgeone.app/

Page Load Overview

0.60s
Total Load Time
4
HTTP Requests
1
Domains
7 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
Text Length:312 chars
Detector Agreement:100%

Website Classification

Primary Category

technology software32% confidence
Type: static
Method: ml+structural

All Detected Categories

technology software
32%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
443.152.26.58Singapore
41--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T121315377C4F031AF8A16219951C3F118FE84440B9315180076AC7EF46F95DD7A6A7ABF

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

24:hRjCjLm7EF8IlrDccSIvKSxm2whTjqbwaVuh0J0cuAVN/m7HTB4CVg:T4m7ozZ4QmVhTjqbH0h0J0cuAVN+mN

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:1681:gIAUAAAIQAAgIAAAAAgAAECAAEEAAAAAAgIAAAAAAAAAAAAQgAAAEAAQEAEAAAAAAUCAYgADgAABKQAAkQgAQABAAAQAAACA

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:303c3c3c3c3c0000
Perceptual Hash:cfce30cece642331
Difference Hash:6469696169690800
Wavelet Hash:3c3c3c3c3c3c0000
Color Hash:#2dd29e

Other Hashes

Crop Resistant:6469696169690800

Scan History

Scan history not available

Unable to load historical scan data