Security Scan Report: foolish-aquamarine-vqhay79vki-l49rmn9rgd.edgeone.app

Submitted: Jan 19, 2026, 7:31:34 PMCompleted: Jan 19, 2026, 7:32:51 PMpubliccompleted
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Summary

This website contacted 1 IP in 1 country across 1 domain to perform 3 HTTP transactions. The main domain is foolish-aquamarine-vqhay79vki-l49rmn9rgd.edgeone.app and was registered NaN years ago.

Submitted URL: https://foolish-aquamarine-vqhay79vki-l49rmn9rgd.edgeone.app/

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

AI Security Verdict

Safe Website

Confidence: 96%

0
Risk Score

Legitimate site with no apparent security concerns.

Safety Factors
Well‑established domain with minimal risk category
Absence of forms collecting sensitive data
No malicious Indicators of Compromise detected
No external domains or redirects
Content appears to be a simple file collection page
Domain age information unavailable

Details

Page Title

Files Collection

Scan Type

public

Language

🇺🇸

English

(70% confidence)

Category

education learning

(51%)

Domain Information

Domain 'foolish-aquamarine-vqhay79vki-l49rmn9rgd.edgeone.app' uses the application-focused generic top-level domain (.app) with subdomain 'foolish-aquamarine-vqhay79vki-l49rmn9rgd'. Its registrable label 'edgeone' stretches across 7 characters with 4 vowels and 3 consonants. Tokenizing the label suggests 2 words: edge, one. The median word length lands at 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://foolish-aquamarine-vqhay79vki-l49rmn9rgd.edgeone.app/

Page Load Overview

5.43s
Total Load Time
2
HTTP Requests
1
Domains
7 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:70%
Script:Latin
Direction:ltr

Detection Details

Language Code:en
Detection Confidence:70%
Script Type:Latin
HTML Lang Attribute:zh
Text Length:100 chars
Detector Agreement:100%
Language mismatch: Declared as zh but detected as en

Website Classification

Primary Category

education learning51% confidence
Type: static
Method: ml+structural

All Detected Categories

education learning
51%
government public service
32%

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

T12702C6CAEBA305C8A81BC0682FFB5724222DE057D448CD5DB96E1F548F0518875FB2B8

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:KrXrdEzawwpcoz5seK/ASMHmGgdkUfE0gB/mQh1RaXQl:KrzhNK/lMHmGgdkqwmQd

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:8816:ME1i1nBCJQMTPBVcBU2AlCAiWCCEDQQBMNAJAAADiDaQAIEIFMR0ywKACYeCgNaSmTjc1UAmSGHahAhBoEIGCjoCOC6WBCEB

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:dcfcfcc0e0e0c0c0
Perceptual Hash:da9a989c6c6561e3
Difference Hash:3038580000000000
Wavelet Hash:dcfcfcf0f0e0c0c0
Color Hash:#3a6d78

Other Hashes

Crop Resistant:3038580000000000

Scan History

Scan history not available

Unable to load historical scan data