Security Scan Report: sweet-coffee-eq0hw3ucef-nyawi7slaq.edgeone.app

Submitted: Mar 14, 2026, 3:32:22 AMCompleted: Mar 14, 2026, 3:33:41 AMpubliccompleted
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Summary

This website contacted 1 IP in 1 country across 1 domain to perform 2 HTTP transactions. The main domain is sweet-coffee-eq0hw3ucef-nyawi7slaq.edgeone.app and was registered NaN years ago.

Submitted URL: https://sweet-coffee-eq0hw3ucef-nyawi7slaq.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%

1
Risk Score

No malicious activity detected; site appears legitimate and safe.

Safety Factors
No credential or payment collection forms
No malicious Indicators of Compromise
No JavaScript malware or credential exfiltration
Brand mention used as a reference, not impersonation
Standard hosting platform subdomain without malicious activity
Domain age information unavailable

Details

Page Title

MarketJo Creator Network

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

social media network

(94%)

Domain Information

Within the application-focused generic top-level domain (.app), 'sweet-coffee-eq0hw3ucef-nyawi7slaq.edgeone.app' is registered; it also runs on subdomain 'sweet-coffee-eq0hw3ucef-nyawi7slaq'. The registrable portion 'edgeone' spans 7 characters containing four vowels alongside 3 consonants. Segmentation suggests two 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://sweet-coffee-eq0hw3ucef-nyawi7slaq.edgeone.app/

Page Load Overview

0.31s
Total Load Time
2
HTTP Requests
1
Domains
1 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:429 chars
Detector Agreement:100%

Website Classification

Primary Category

social media network94% confidence
Type: static
Method: ml+structural

All Detected Categories

social media network
94%
entertainment media
41%

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

T100611367B152187CE1FBE67A74B4DB9DB88C81474E4748E0A8DD4A248070D5AC33DD2C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

96:TvNF+lxb2GRIZxXSrk6RD5d8jNiXgRkWZxNLpd55DDrm:ilxbvRIF0gJivW5V1/m

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:3304:FDgWEQhAAEAAAEAACIAgAhAAQEAAAAAiAAIAAAIACEQgJIANAgAAAAAUQQpKAQAQAVQwAACQgAhgKCBAgAAEIACQAhACQRAA

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:003cff7dfdfdfdfd
Perceptual Hash:9a6d282c2c6f1e6d
Difference Hash:b379616979616979
Wavelet Hash:003c3c3c3d3d3d3d
Color Hash:#741f93

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data