Security Scan Report: zygotic-coffee-zyouyw8sn8-g1hmomz4q0.edgeone.app

Submitted: May 4, 2026, 10:59:22 AMCompleted: May 4, 2026, 11:00:33 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 zygotic-coffee-zyouyw8sn8-g1hmomz4q0.edgeone.app and was registered NaN years ago.

Submitted URL: https://zygotic-coffee-zyouyw8sn8-g1hmomz4q0.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: 80%

2
Risk Score

Low risk site; no malicious activity detected.

Risk Factors
Low Cisco Umbrella ranking (rank #455,732)
Subdomain on a hosting platform with unknown age
Safety Factors
Absence of login or payment forms
No credential exfiltration or suspicious network activity
JavaScript obfuscation score low (standard minification)
Domain age information unavailable

Details

Page Title

Files Collection

Scan Type

public

Language

🇩🇰

Danish

(22% confidence)

Category

technology software

(73%)

Domain Information

The domain name 'zygotic-coffee-zyouyw8sn8-g1hmomz4q0.edgeone.app' uses the application-focused generic top-level domain (.app) with subdomain 'zygotic-coffee-zyouyw8sn8-g1hmomz4q0'. Count 7 characters in 'edgeone' with four vowels and 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://zygotic-coffee-zyouyw8sn8-g1hmomz4q0.edgeone.app/

Page Load Overview

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

Language Analysis

Primary Language

🇩🇰Danish
Code: da
Confidence:22%
Script:Latin
Direction:ltr

Detection Details

Language Code:da
Detection Confidence:22%
Script Type:Latin
HTML Lang Attribute:zh
Text Length:2,081 chars
Detector Agreement:100%
Language mismatch: Declared as zh but detected as da

Website Classification

Primary Category

technology software73% confidence
Type: static
Method: ml+structural

All Detected Categories

technology software
73%
documentation technical
70%
cryptocurrency blockchain
64%
finance banking
61%
healthcare medical
59%

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

T1B8A3AD409FFC2FEC741E8641977D7B3B2A266053A58D029CB6EE0EB0EF48945E4B7065

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:wSqstztrTRxzVrlfN793F7L5LVr5bN7pBnhbpHpzxnrp7V7pbNLpd7Nf17FHNbLH:FtztrTRxzVrlfN793F7L5LVr5bN7pBnf

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:105652:YRFQC6YYSBEKH4CCKACSCAMC4QCqDTFllMoMAAJLJqeEASGUt/SQQmCzRpRkeJAGiDaYxkMCAMMisA5OMQAiAC4ABTGABFEH

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:1c1c3c1c1c1c1c1c
Perceptual Hash:9a7c343850d5c7e3
Difference Hash:b03031303131b131
Wavelet Hash:dcfcbc3c1c1c1c1c
Color Hash:#3a7857

Other Hashes

Crop Resistant:b03031303131b131

Scan History

Scan history not available

Unable to load historical scan data