Security Scan Report: fancy-coffee-3ppe71zczl-82einnz7jj.edgeone.app

Submitted: Mar 2, 2026, 12:50:13 AMCompleted: Mar 2, 2026, 12:51:26 AMpubliccompleted
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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 fancy-coffee-3ppe71zczl-82einnz7jj.edgeone.app and was registered NaN years ago.

Submitted URL: https://fancy-coffee-3ppe71zczl-82einnz7jj.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: 92%

0
Risk Score

No suspicious activity detected; site appears legitimate.

Safety Factors
No credential or payment collection forms
No malicious Indicators of Compromise
No JavaScript malware or suspicious behavior
No IDS alerts indicating phishing or malware
Hosting platform subdomain without any suspicious elements
Domain age information unavailable

Details

Page Title

Files Collection

Scan Type

public

Language

🇺🇸

English

(36% confidence)

Category

documentation technical

(69%)

Domain Information

Domain 'fancy-coffee-3ppe71zczl-82einnz7jj.edgeone.app' uses the application-focused generic top-level domain (.app), featuring subdomain 'fancy-coffee-3ppe71zczl-82einnz7jj'. The second-level label 'edgeone' is 7 characters long containing 4 vowels alongside 3 consonants. Splitting it apart reveals 2 words: edge, one. Average segment length settles at 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://fancy-coffee-3ppe71zczl-82einnz7jj.edgeone.app/

Page Load Overview

0.40s
Total Load Time
2
HTTP Requests
1
Domains
7 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:36%
Script:Latin
Direction:ltr

Detection Details

Language Code:en
Detection Confidence:36%
Script Type:Latin
HTML Lang Attribute:zh
Text Length:86 chars
Detector Agreement:100%
Language mismatch: Declared as zh but detected as en

Website Classification

Primary Category

documentation technical69% confidence
Type: static
Method: ml+structural

All Detected Categories

documentation technical
69%
technology software
60%
government public service
38%
news media journalism
34%
healthcare medical
26%

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

T1FF42B6C5EFE60ACCA81BC4685FBE67253629A013D44DC95CB59E0F648F49184B4FB2B4

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:KrXrdEzawwpcoz5seK/ASMHmGgdkUfE0gB+NChJNWhJNHhJNRhJNzh1RaXQl:KrzhNK/lMHmGgdkqwoNXpd

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:12242:Kg2i1HFIB/c4NBQUAWejgAgiAACEDUQhNJgpAAYqmHIUiIEIAKI0wxHwSSWCBOaCATyUVSEmbHRaRInDNAbuWS4EOGbGRhGR

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:dcfcfcfcbc800000
Perceptual Hash:da9a3869989a6567
Difference Hash:3030606060000000
Wavelet Hash:dcfcfcfcfcc08000
Color Hash:#623a78

Other Hashes

Crop Resistant:3030606060000000

Scan History

Scan history not available

Unable to load historical scan data