Security Scan Report: register-areca-capital-d3n6dfafzm.edgeone.dev

Submitted: Apr 19, 2026, 1:15:55 AMCompleted: Apr 19, 2026, 1:17:06 AMpubliccompleted
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Summary

This website contacted 2 IPs in 1 country across 2 domains to perform 1 HTTP transaction. The main domain is register-areca-capital-d3n6dfafzm.edgeone.dev and was registered NaN years ago.

Submitted URL: https://register-areca-capital-d3n6dfafzm.edgeone.dev/

AI Security Verdict

High Risk

Confidence: 92%

8
Risk Score

The site impersonates Areca Capital, uses an unranked, newly created subdomain with an email collection form, indicating a high‑risk brand phishing attempt.

Risk Factors
Unknown subdomain age
Unranked domain reputation
Brand impersonation on non‑official domain
Credential‑type form (email) without legitimate purpose
Use of generic hosting platform subdomain
Domain age information unavailable

Details

Page Title

Daftar Areca Capital — Hantar ke WhatsApp

Scan Type

public

Language

🇮🇩

ID

(35% confidence)

Category

corporate business

(77%)

Domain Information

The domain name 'register-areca-capital-d3n6dfafzm.edgeone.dev' uses the developer-focused generic top-level domain (.dev) with subdomain 'register-areca-capital-d3n6dfafzm'. The registrable portion 'edgeone' spans 7 characters containing 4 vowels alongside three 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://register-areca-capital-d3n6dfafzm.edgeone.dev/

Page Load Overview

2.05s
Total Load Time
4
HTTP Requests
2
Domains
46 KB
Total Size

Language Analysis

Primary Language

🇮🇩Indonesian
Code: id
Confidence:35%
Script:Unknown
Direction:ltr

Detection Details

Language Code:id
Detection Confidence:35%
Script Type:Unknown
HTML Lang Attribute:ms
Text Length:507 chars
Detector Agreement:67%
Language mismatch: Declared as ms but detected as id

Website Classification

Primary Category

corporate business77% confidence
Type: static
Method: ml+structural

All Detected Categories

corporate business
77%
finance banking
68%
government public service
60%
news media journalism
49%
technology software
43%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
2142.250.154.132United States
243.174.247.29United States
42--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T142E1B56159F425759263C0942BE69F07EC60C213D60A9680B6CC3FF64FDBC85CA5B25C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

96:orXy68RcwgTGCPzs/P15+J838gmgn8mp/qqvWtcXZd3C96eC6pHt7qQ0KITVO:orXyHRvIzIH+J28gmW8mRqC+ftGkITs

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:7040:hCAlEkQDMIgC4gbBQYCJwEAcJKSCRHBhJAABIQBE1eQ0IEIg5CQITTgwlAECGA4IClGOQIgFwhhhSiCMFikAJcQ5goEAAoGA

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:e7e7e7efffffffff
Perceptual Hash:b33323cccc9963c6
Difference Hash:4c4c4c0820283871
Wavelet Hash:26262606bcbc9cbd
Color Hash:#86832d

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data