Security Scan Report: ill-coffee-mjkaxdsgqp-t1yunpp2oa.edgeone.app

Submitted: Feb 26, 2026, 9:11:15 AMCompleted: Feb 26, 2026, 9:12:30 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 ill-coffee-mjkaxdsgqp-t1yunpp2oa.edgeone.app and was registered NaN years ago.

Submitted URL: https://ill-coffee-mjkaxdsgqp-t1yunpp2oa.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: 92%

2
Risk Score

No malicious activity detected; appears to be a simple file collection page on a hosting platform.

Risk Factors
Subdomain on hosting platform with unknown creation date (moderate suspicion)
Safety Factors
No password, email, or payment fields
No external domains or cross‑origin requests
Low JavaScript obfuscation score
No redirect chains or URL manipulation
Domain age information unavailable

Details

Page Title

Files Collection

Scan Type

public

Language

🇫🇷

French

(50% confidence)

Category

government public service

(66%)

Domain Information

You're looking at domain 'ill-coffee-mjkaxdsgqp-t1yunpp2oa.edgeone.app' on the application-focused generic top-level domain (.app), featuring subdomain 'ill-coffee-mjkaxdsgqp-t1yunpp2oa'. Count 7 characters in 'edgeone' with 4 vowels and three consonants. Splitting it apart reveals 2 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://ill-coffee-mjkaxdsgqp-t1yunpp2oa.edgeone.app/

Page Load Overview

0.92s
Total Load Time
2
HTTP Requests
1
Domains
7 KB
Total Size

Language Analysis

Primary Language

🇫🇷French
Code: fr
Confidence:50%
Script:Latin
Direction:ltr

Detection Details

Language Code:fr
Detection Confidence:50%
Script Type:Latin
HTML Lang Attribute:zh
Text Length:65 chars
Detector Agreement:100%
Language mismatch: Declared as zh but detected as fr

Website Classification

Primary Category

government public service66% confidence
Type: static
Method: ml+structural

All Detected Categories

government public service
66%
education learning
61%
documentation technical
41%
healthcare medical
40%
news media journalism
39%

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

T16802C6CAEBA305C8A82BC0682FFF5324222DE027C449CD5DB99E1F548F0518875EA3B4

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:KrXrdEzawwpcoz5seK/ASMHmGgdkUfE0gB8H0/Qh1RaXQl:KrzhNK/lMHmGgdkqy/Qd

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:8728:MAUT13ACBQdQNBWcAc2AhAAiSBCkTQQEMFAJSEAKiDKwZ4EKgsR2wwKACYcGANeAgTi8VSAnSGBapgrDCAIOiCoCOieWAQEB

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:dcfcfce0e0e0c0c0
Perceptual Hash:d89a983c6c6567c3
Difference Hash:3030500000000000
Wavelet Hash:dcfcfcf0f0e0c0c0
Color Hash:#c5879e

Other Hashes

Crop Resistant:3030500000000000

Scan History

Scan history not available

Unable to load historical scan data