Security Scan Report: calm-faun-867857.netlify.app

Redirected to:
https://calm-faun-867857.netlify.app/
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Submitted: Completed: publiccompleted
This website contacted 8 IPs in 3 countries across 8 domains to perform 176 HTTP transactions. The main domain is netlify.app and was registered 8 years ago.

Submitted URL: http://calm-faun-867857.netlify.app/

Effective URL:
https://calm-faun-867857.netlify.app/
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AI Security Verdict

High Risk

Confidence: 88%

8
Risk Score

Fake Roblox signup page on a netlify.app subdomain, complete with copied branding, meta tags and a username/password form; credentials entered here would go to the page operator, not Roblox.

Risk Factors (4)
Brand impersonation of Roblox on a non-official domain
Credential-harvesting form (username + password) on an unranked, instant-publish hosting subdomain
Unknown subdomain creation date behind the netlify.app apex; anyone can publish there instantly
Page text claims to be the official Roblox service ('©2026 Roblox Corporation', Roblox trademarks) without being on Roblox's domain
Domain age information unavailable

Details

Page Title

Roblox

Scan Type

public

Domain Name Analysis

You're looking at domain 'calm-faun-867857.netlify.app' on the application-focused generic top-level domain (.app); it also runs on subdomain 'calm-faun-867857'. Its registrable label 'netlify' stretches across 7 characters split between two vowels and five consonants. Word splitting yields 3 words: net, li, fy. The median word length lands at 2 characters. No strong language cues emerged from the frequency lists.

Screenshot

R&BLOX Create a new account Discover over 30 million experiences Birthday [Month v || Day v |) Year Username | Don't use your real name Password | Atleast 8 characters Gender (optional) © Mal...

Page Load Overview

7.04s
Total Load Time
3.3 MB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en
Text Length:1,438 chars
Detector Agreement:100%

Website Classification

Primary Category

corporate business72% confidence
Type: spa
Method: ml+structural

All Detected Categories

corporate business
72%
entertainment media
59%
technology software
42%
corporate
35%

Detected Features

Login Form
OG: website
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
14363.176.8.218Aws · CLOUDFrankfurt am Main, Hesse, Germany
AS16509Amazon.com, Inc.
22128.116.31.3Slough, England, United Kingdom
AS22697Roblox
2265.9.130.5Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
2254.192.35.108Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
2235.157.26.135Aws · CLOUDFrankfurt am Main, Hesse, Germany
AS16509Amazon.com, Inc.
2265.9.130.49Cloudfront · CDNUnited States
AS16509Amazon.com, Inc.
2223.207.210.91Akamai · CDNFrankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
2223.207.210.87Akamai · CDNFrankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
1768--

Detected Technologies3

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T13AA3C562FB01E836EC0B4AF55124A858C014B721DE1A84D8F4DCF3B52FDDBF7AA62552

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:vndXBK+ryfhWyaPF0uflOO23Y5bSw9d/oVuPQr3lswUH0kqp+Omr7yfp3zVY+g0x:vdXA1zRH

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:102223:IoPQEOFMA4BpAlcSBRIwArCIGWQ2RECF+xG4EkAEoAtzNSqonsIMUIQoENlBEqADRBoRALDDAMUGQaAIARYAE0SgQIskYMAg

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:938d073dcf710400
Perceptual Hash:aaad6decb40a24b5
Difference Hash:233a6f790ce35949
Wavelet Hash:9b9f073def610d00
Color Hash:30201008040

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data