Security Scan Report: appsecuritypatch.netlify.app

Redirected to:
https://appsecuritypatch.netlify.app/
Site favicon
Submitted: Completed: publiccompleted
This website contacted 6 IPs in 3 countries across 4 domains to perform 26 HTTP transactions. The main domain is netlify.app and was registered 8 years ago.

Submitted URL: http://appsecuritypatch.netlify.app/

Effective URL:
https://appsecuritypatch.netlify.app/
Redirected

AI Security Verdict

Confirmed Scam

Confidence: 93%

9
Risk Score

Fake 'Official Apple' support page on a netlify.app subdomain using a locked-iPhone scare alert to push victims into calling +1 (877) 374-2183 — a classic Apple tech support scam.

Risk Factors (5)
Brand impersonation of Apple on a mismatched, unranked netlify.app subdomain
Fabricated device-lock and fraudulent-transaction alerts designed to induce panic
Callback phone number used as the scam conversion channel (tech support fraud)
Copied Apple branding, meta description and copyright notice
No verifiable ownership or legitimacy (legitimacy score 13/100, unranked domain)
Domain age information unavailable

Details

Page Title

Contact - Official Apple

Scan Type

public

Domain Name Analysis

Within the application-focused generic top-level domain (.app), 'appsecuritypatch.netlify.app' is registered with subdomain 'appsecuritypatch'. The second-level label 'netlify' is 7 characters long split between two vowels and five consonants. Word splitting yields 3 words: net, li, fy. Average segment length settles at 2 characters. No strong language cues emerged from the frequency lists.

Screenshot

6 w [vse (Supsort HelpLine +1 (877) 374-2183 commurties _ Contact Support Your iPhone has been locked due to detected illegal activity! Immediately call Apple Support +1 (877) 374-2183 to unlock it!...

Page Load Overview

1.79s
Total Load Time
293 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:1,000 chars
Detector Agreement:100%

Website Classification

Primary Category

e-commerce shopping36% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

e-commerce shopping
36%
technology software
33%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
663.176.8.218Aws · CLOUDFrankfurt am Main, Hesse, Germany
AS16509Amazon.com, Inc.
420.250.198.32Azure · CLOUDZurich, Zurich, Switzerland
AS8075Microsoft Corporation
4150.171.110.56Azure · CLOUDUnited States
AS8075Microsoft Corporation
452.159.82.83Azure · CLOUDChicago, Illinois, United States
AS8075Microsoft Corporation
435.157.26.135Aws · CLOUDFrankfurt am Main, Hesse, Germany
AS16509Amazon.com, Inc.
451.8.71.184Azure · CLOUDDulles, Virginia, United States
AS8075Microsoft Corporation
266--

Detected Technologies3

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T169929780B2CF483B11B3038822EA7F8D72B4892EEBC5C851F5BF42375F95D09655B964

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

384:jt1CAc/brr+iHPi6mO6OBzzzzzErTf29tlEwmc:jt1CzTj6O6OBzzzzzcEQc

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:20726:YhEMi4cRLBgCSEUFhFBIkkwm6MSQYCAwSgQAgDLbHhQDQjoAoQAhAuk6IBR8qjhh0GYEJMCIkFAiCRQJI1gwBBCLDiuxmESb

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:00fff7e7e78383df
Perceptual Hash:e6d31c2e532c5974
Difference Hash:b1054d4d4d2726a6
Wavelet Hash:00f7e7e7e50103d3
Color Hash:N/A

Scan History

Scan history not available

Unable to load historical scan data