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Security Scan Report: toxic-azure-sc0rtymqfq-rkqqsb7pep.edgeone.app

Submitted: Feb 25, 2026, 9:34:24 PMCompleted: Feb 25, 2026, 9:35:50 PMpubliccompleted
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Summary

This website contacted 3 IPs in 1 country across 3 domains to perform 1 HTTP transaction. The main domain is toxic-azure-sc0rtymqfq-rkqqsb7pep.edgeone.app and was registered NaN years ago.

Submitted URL: https://toxic-azure-sc0rtymqfq-rkqqsb7pep.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: 85%

2
Risk Score

Low‑risk marketing page; no malicious activity detected.

Safety Factors
No credential or payment collection forms
No malicious Indicators of Compromise
No JavaScript malware or suspicious behavior
Hosted on a known development/hosting platform (edgeone.app)
Brand mentioned (CiGo) is not a well‑known high‑profile brand
Domain age information unavailable

Details

Page Title

CiGo – Cilor Gokil

Scan Type

public

Language

🇮🇩

ID

(80% confidence)

Category

social media network

(83%)

Domain Information

The domain 'toxic-azure-sc0rtymqfq-rkqqsb7pep.edgeone.app' uses the application-focused generic top-level domain (.app), featuring subdomain 'toxic-azure-sc0rtymqfq-rkqqsb7pep'. Its registrable label 'edgeone' stretches across 7 characters containing four vowels alongside three consonants. Splitting it apart reveals two 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://toxic-azure-sc0rtymqfq-rkqqsb7pep.edgeone.app/

Page Load Overview

6.27s
Total Load Time
8
HTTP Requests
3
Domains
176 KB
Total Size

Language Analysis

Primary Language

🇮🇩Indonesian
Code: id
Confidence:80%
Script:Unknown
Direction:ltr

Detection Details

Language Code:id
Detection Confidence:80%
Script Type:Unknown
HTML Lang Attribute:id
Text Length:2,648 chars
Detector Agreement:100%

Website Classification

Primary Category

social media network83% confidence
Type: static
Method: ml+structural

All Detected Categories

social media network
83%
entertainment media
63%
e-commerce shopping
56%
education learning
47%
technology software
43%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
4172.217.20.138Singapore
AS15169
243.152.26.58Singapore
AS139341ACE
2142.251.127.94SingaporeUnknown
83--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T11862A69565B711236053A1B537E31B1F2AB4E003CA0AC62A37EC5794CFC6BE99E5364C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:WP9IyVrXYvno7u/tkgZ+jBozzGTreCifalPTrK7suaKtDMp9NPDcphulNjybuG16:4IVz88+wsAM/lAvulNjybuG16h

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:14970:QI4DEw2ADEjAAgCAAIB4Y7J4wAoQ5vEOAJE7AHmEGBac5ARCQ7UPKSCJxskFmFAkCAaHATB0qIgcF4QaECuAgAUACCAQ8EJA

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:80181818181800ff
Perceptual Hash:cc5ff74c9932b900
Difference Hash:3161b131b3312c10
Wavelet Hash:99bd3d19191900ff
Color Hash:#40bf84

Other Hashes

Crop Resistant:3161b131b3312c10,c44d3e0992261649

Scan History

Scan history not available

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