Security Scan Report: sparkly-lily-ce95a1.netlify.app

Submitted: Sep 22, 2026, 1:45:21 PMCompleted: Sep 22, 2026, 1:47:13 PMpubliccompleted

AI Security Verdict

High Risk

Confidence: 82%

8
Risk Score

Fake Roblox login page on a netlify.app subdomain that impersonates Roblox branding and captures username/email and password. Do not enter credentials.

Risk Factors
Impersonation of Roblox brand on a non-official domain
Login form collecting password and email/username on impersonating page
Free hosting-platform subdomain with unknown page age and no domain reputation
Scraped/cloned UI text and self-referential dead links (# on Sign Up)
Domain age information unavailable

Details

Page Title

Roblox

Scan Type

public

Domain Name Analysis

You're looking at domain 'sparkly-lily-ce95a1.netlify.app' on the application-focused generic top-level domain (.app); it also runs on subdomain 'sparkly-lily-ce95a1'. The core label 'netlify' covers 7 characters split between 2 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

Security scan screenshot of https://sparkly-lily-ce95a1.netlify.app/

Page Load Overview

75.20s
Total Load Time
3 KB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en
Text Length:238 chars
Detector Agreement:100%

Website Classification

Primary Category

entertainment media67% confidence
Type: static
Method: ml+structural

All Detected Categories

entertainment media
67%
technology software
54%
social media network
26%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
263.176.8.218Aws · CLOUDFrankfurt am Main, Hesse, Germany
AS16509Amazon.com, Inc.
0195.154.239.25Paris, Île-de-France, France
AS12876Scaleway SAS
0195.154.239.26Paris, Île-de-France, France
AS12876Scaleway SAS
23--

Detected Technologies2

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T12B62456651A228162553D4B877E75B463655C003CA0ACD583FBC63E4CFCAB869EF338C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:SAIINmKiBGTi1QGnIFkmOL1Q9AEWP9dYBVkNa+lM+oh9sKKsyKQnmJS6ifHY65UD:UISIF7WX6cHhN1IOcHh/9lL

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:15206:hpBSOfmw9ICEUBDBgSBCECGAMIUOFyGeMTOiDQMBRiEBIQ/QoDQPAAEoI8DiEiAIcKxQhBUIIgoypTBQQemBCaAwggBChCjG

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:1800181818181881
Perceptual Hash:d8037399fb89d911
Difference Hash:2a0432323232b209
Wavelet Hash:3c001818181818ff
Color Hash:#d2797e

Other Hashes

Crop Resistant:2a0432323232b209

Scan History

Scan history not available

Unable to load historical scan data