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Security Scan Report: app-alrt-swdojvirpwcpjo-dp222hguhdl0.edgeone.dev

Submitted: Completed: publiccompleted

Summary

API
This view is built from:
Scan result: counts, verdicts, details, IPs, technologies, hashes/api/v1/result/1798e9fb-17f1-4236-940d-f3cff0bce51fDomain and IP registration (RDAP)/api/v1/rdap/1798e9fb-17f1-4236-940d-f3cff0bce51fHow often this domain was scanned/api/v1/domain/stats/app-alrt-swdojvirpwcpjo-dp222hguhdl0.edgeone.devScan history for this domain/api/v1/domain/history/app-alrt-swdojvirpwcpjo-dp222hguhdl0.edgeone.dev?limit=15
This website contacted 2 IPs in 1 country across 1 domain to perform 20 HTTP transactions. The main domain is edgeone.dev and was registered 1 year 5 months ago.

Submitted URL: https://app-alrt-swdojvirpwcpjo-dp222hguhdl0.edgeone.dev/

AI Security Verdict

High Risk

Confidence: 80%

8
Risk Score

Fake "Official Apple" support page on a random edgeone.dev subdomain using device-locked/payment scareware to push calls to +1-810-666-0572. No credential form found, but clear Apple impersonation and tech-support scam content.

Risk Factors (4)
Impersonation of Apple's brand and support identity on a non-Apple domain
Fake device-lock / illegal-transaction scareware with an urgent premium-style callback number
Unsolicited fake payment notification text ($309.99 to gambling/adult sites)
Unranked host on a free instant-subdomain platform with unknown page age
Domain age information unavailable

Details

Page Title

Contact - Official Apple

Scan Type

public

Domain Name Analysis

Domain 'app-alrt-swdojvirpwcpjo-dp222hguhdl0.edgeone.dev' uses the developer-focused generic top-level domain (.dev) and includes subdomain 'app-alrt-swdojvirpwcpjo-dp222hguhdl0'. Its registrable label 'edgeone' stretches across 7 characters holding 4 vowels versus three 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

Omessaces Payment Successful ‘Sent $ 309.99 via Online Transaction to Betonline.net & pombub,net . Not you? Call +1-810-666-0572 Apple Support +1-810-666. Communities Apple Support Your Phone ha...

Page Load Overview

20.64s
Total Load Time
211 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

HTML Lang Attribute:en-US
Text Length:1,110 chars
Detector Agreement:100%

Website Classification

Primary Category

adult content61% confidence
Type: static
Method: ml+structural

All Detected Categories

adult content
61%
e-commerce shopping
46%
technology software
36%
documentation technical
26%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
1043.174.247.29Singapore
AS139341ACE
1043.174.246.29Singapore
AS139341ACE
202--

Detected Technologies3

X-UA-Compatible
100%
jQuery CDN
20%
jQuery
20%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T15AD2D94570F3007A267351A93BEB3F197BA1940FC78AC9013ADC83A64F87D45995B7AC

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:YjJ0Mgd/Z4n3N2lbiRif2/tC1F6DKLfZZZZZQ:Yt07/ZC3NS+Yf2lC1F6DKLfZZZZZQ

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:30419:GAXgkjTQisqgMkQegOhEFUC4OlVQMIRgIBEYAOAbkRkAoC0kAGJQRgWFA4QFRKgIIAkSUjsllDAIRCVJsg2VYwSJLgDAmRiQ

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:1819001919190101
Perceptual Hash:885d33cdcc73334c
Difference Hash:b3314d33b3310d11
Wavelet Hash:1899c1f91f070f0f
Color Hash:N/A

Other Hashes

Crop Resistant:b3b3b3b3b3b3b3b3,01e0e20150b4b040,a6397927808c88b2,b3314d33b3310d11

Scan History

Scan history not available

Unable to load historical scan data