Security Scan Report: cuddly-gray-upd1rhq23q-d3nzwy3nop.edgeone.app

Submitted: Mar 20, 2026, 12:34:50 AMCompleted: Mar 20, 2026, 12:36:10 AMpubliccompleted
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Summary

This website contacted 1 IP in 1 country across 1 domain to perform 1 HTTP transaction. The main domain is cuddly-gray-upd1rhq23q-d3nzwy3nop.edgeone.app and was registered NaN years ago.

Submitted URL: https://cuddly-gray-upd1rhq23q-d3nzwy3nop.edgeone.app/

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

AI Security Verdict

Low Risk

Confidence: 85%

2
Risk Score

Low‑risk site; no malicious activity detected, but the domain is brand‑new.

Risk Factors
New subdomain (age 0 days) on a free hosting platform
Safety Factors
Served over HTTPS
No forms or data collection elements
No external domains or redirects
No malicious JavaScript or obfuscation
No Indicators of Compromise detected
Domain age information unavailable

Details

Page Title

Kids Math Trainer

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

education learning

(80%)

Domain Information

The domain 'cuddly-gray-upd1rhq23q-d3nzwy3nop.edgeone.app' uses the application-focused generic top-level domain (.app); it also runs on subdomain 'cuddly-gray-upd1rhq23q-d3nzwy3nop'. The registrable portion 'edgeone' spans 7 characters split between four vowels and 3 consonants. Tokenizing the label suggests two 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://cuddly-gray-upd1rhq23q-d3nzwy3nop.edgeone.app/

Page Load Overview

0.38s
Total Load Time
2
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:166 chars
Detector Agreement:100%

Website Classification

Primary Category

education learning80% confidence
Type: static
Method: ml+structural

All Detected Categories

education learning
80%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
243.152.26.58Singapore
21--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T17F02FBAB72191D3292EB0BB21DD3D3867220C1027E0B562459DE14E4C1ECDAAD17F76A

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:cEsTYD4UuBb1WjrGhPrR4cFeYpy3Vi1LZT2vdd5ivdry5zG0Fopk3A:cERJf4rR4cXpy3Vi1LZT2vdd529y5LoV

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:8536:ACAiBQgEskCWMgINII5wBQJaICwDBgcACCMIABOQTDHnjNECAFBgIDBGOIkAB7AmvjVUSFDKHQRgRAiUEICBLAUBQkAM+asg

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:1d3d3d1d1f1f0101
Perceptual Hash:8cce33763118dd33
Difference Hash:ab6aebf3ebe3fffb
Wavelet Hash:1d1f1f1f1f1f0103
Color Hash:#6cd0e0

Other Hashes

Crop Resistant:ab6aebf3ebe3fffb

Scan History

Scan history not available

Unable to load historical scan data