Security Scan Report: arencia-vitaminc-booster-amazon.netlify.app

Redirected to:
https://arencia-vitaminc-booster-amazon.netlify.app/
Submitted: Completed: publiccompleted
This website contacted 6 IPs in 2 countries across 5 domains to perform 17 HTTP transactions. The main domain is netlify.app and was registered 8 years ago.

Submitted URL: http://arencia-vitaminc-booster-amazon.netlify.app/

Effective URL:
https://arencia-vitaminc-booster-amazon.netlify.app/
Redirected

AI Security Verdict

Moderate Risk

Confidence: 72%

5
Risk Score

The site impersonates the Arencia brand and collects personal data on an unranked Netlify subdomain, indicating moderate risk of phishing or scam.

Risk Factors (2)
Brand impersonation on an unranked hosting subdomain
Personal data collection form without clear legitimate purpose
Safety Factors (3)
No malicious scripts or external IoC matches
No credential or payment fields present
Storefront content with a same-origin account form — the password field belongs to the shop's own account flow and no credential leaves the apex; scam_type corrected from 'Brand Impersonation' to 'Fake Shopping'. Risk unchanged: a fresh storefront is still judged on its own merits.
Domain age information unavailable

Details

Page Title

Arencia

Scan Type

public

Domain Name Analysis

The domain 'arencia-vitaminc-booster-amazon.netlify.app' uses the application-focused generic top-level domain (.app), featuring subdomain 'arencia-vitaminc-booster-amazon'. Its registrable label 'netlify' stretches across 7 characters holding 2 vowels versus 5 consonants. It segments into three words: net, li, fy. Median word length comes out to 2 characters. No strong language cues emerged from the frequency lists.

Screenshot

Defivering to New Cairo City = Update locationt) Visit the ARENCIA Store 4.4.00 (1,867) Arencia Vitamin C Booster Shot Serum with Glutathione, Niacinamide and Vitamin E for Dark Spot Care, Fine Line...

Page Load Overview

1.85s
Total Load Time
1.1 MB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en
Text Length:8,574 chars
Detector Agreement:100%

Website Classification

Primary Category

e-commerce shopping73% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

e-commerce shopping
73%
healthcare medical
70%
documentation technical
61%
government public service
55%
education learning
55%

Detected Features

Products

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
7157.240.0.6Frankfurt am Main, Hesse, Germany
AS32934Facebook, Inc.
2104.18.33.206Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
263.176.8.218Aws · CLOUDFrankfurt am Main, Hesse, Germany
AS16509Amazon.com, Inc.
235.157.26.135Aws · CLOUDFrankfurt am Main, Hesse, Germany
AS16509Amazon.com, Inc.
2157.240.0.35Frankfurt am Main, Hesse, Germany
AS32934Facebook, Inc.
254.69.27.192Aws · CLOUDBoardman, Oregon, United States
AS16509Amazon.com, Inc.
176--

Detected Technologies1

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1EC340A9171B10031506345E96A93B7A9BF749403A70ADD203ADC127C1FCAFB796BB7AC

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:i1OmsLDGsEa4NbfgCE4rnB83tT5Mxo07V:i1OmsDqaebfEkW3tT5Mxo07V

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:230455:AwRCwAYBA8TiYYQRDMoKxBjaGYUEAYBkkApEp9BA8SDSjEhjCBwKZQAkIYY4wLjC2dBVRIAYAAZMxgAJAkYAxUMIAx2TEaAR

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:c7e7efffffffffef
Perceptual Hash:b376336633223333
Difference Hash:4c4c180c00000c18
Wavelet Hash:e6e6e6fe0e0e0606
Color Hash:N/A

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data