Security Scan Report: marked-fuchsia-ba3l9uwm1x-6es3gpk3at.edgeone.app

Submitted: Jan 24, 2026, 5:03:59 PMCompleted: Jan 24, 2026, 5:05:07 PMpubliccompleted
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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 marked-fuchsia-ba3l9uwm1x-6es3gpk3at.edgeone.app and was registered NaN years ago.

Submitted URL: https://marked-fuchsia-ba3l9uwm1x-6es3gpk3at.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: 95%

0
Risk Score

No suspicious activity detected; site appears legitimate.

Safety Factors
Well‑established domain (> 2 years old)
No credential or payment forms present
No malicious Indicators of Compromise
No JavaScript malware detected
No external domains linked
Domain age information unavailable

Details

Page Title

Files Collection

Scan Type

public

Language

🇵🇭

TL

(50% confidence)

Category

cryptocurrency blockchain

(70%)

Domain Information

Within the application-focused generic top-level domain (.app), 'marked-fuchsia-ba3l9uwm1x-6es3gpk3at.edgeone.app' is registered and includes subdomain 'marked-fuchsia-ba3l9uwm1x-6es3gpk3at'. The second-level label 'edgeone' is 7 characters long containing four vowels alongside three consonants. It segments into 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://marked-fuchsia-ba3l9uwm1x-6es3gpk3at.edgeone.app/

Page Load Overview

0.60s
Total Load Time
2
HTTP Requests
1
Domains
7 KB
Total Size

Language Analysis

Primary Language

🇵🇭TL
Code: tl
Confidence:50%
Script:Unknown
Direction:ltr

Detection Details

Language Code:tl
Detection Confidence:50%
Script Type:Unknown
HTML Lang Attribute:zh
Text Length:8,192 chars
Detector Agreement:100%
Language mismatch: Declared as zh but detected as tl

Website Classification

Primary Category

cryptocurrency blockchain70% confidence
Type: static
Method: ml+structural

All Detected Categories

cryptocurrency blockchain
70%
technology software
62%
news media journalism
57%
finance banking
57%
documentation technical
56%

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

T1F2349D959FF82FDCA05E8588D77DBB3F2A255003B44D019CB4AE0EB0AF45C86E4B7169

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

6144:Kyc6GGgYqE+G6m2OG6QeuWeOGaIO8gmquiGmEuwiMeaqyQ+0qWiSamq0WoOayOGQ:Kyc6GGgYqE+G6m2OG6QeuCGaIO8gmquy

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:242558:0AlhQaSkIZBHGIyArSSCiAkWQQEMFjEACApMBQBuBmDS5YOkFVAQSkGxVbAUVJAMwQNxQkECBKWSwibobUMiiyEIAxNBBFkX

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:1c1c1c1c1c1c1c1c
Perceptual Hash:983c6c3c5471c7e3
Difference Hash:b030303030303030
Wavelet Hash:5c5cdcdcdc1c1c1c
Color Hash:#799ad2

Other Hashes

Crop Resistant:b030303030303030

Scan History

Scan history not available

Unable to load historical scan data