Security Scan Report: bouncehousediscordgg.netlify.app

Submitted: Sep 22, 2026, 1:45:37 PMCompleted: Sep 22, 2026, 1:46:35 PMpubliccompleted

AI Security Verdict

High Risk

Confidence: 82%

8
Risk Score

Fake Discord login page on a free netlify.app subdomain, brand impersonating Discord and capturing email/phone plus password. Classic credential phishing — do not enter credentials.

Risk Factors (5)
Discord brand impersonation on a non-Discord domain
Login form collecting email/phone and password
Instant free-hosting subdomain (netlify.app) with unknown creation date
Unranked domain posing as a major consumer brand
Fake 'Invalid login. Please try again.' error text mimics a real auth page to coax repeated credential entry
Domain age information unavailable

Details

Page Title

Discord

Scan Type

public

Domain Name Analysis

Within the application-focused generic top-level domain (.app), 'bouncehousediscordgg.netlify.app' is registered, featuring subdomain 'bouncehousediscordgg'. Count 7 characters in 'netlify' containing 2 vowels alongside five consonants. Breaking it apart gives 3 words: net, li, fy. Average segment length settles at two characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://bouncehousediscordgg.netlify.app/

Page Load Overview

0.94s
Total Load Time
5 KB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en
Text Length:201 chars
Detector Agreement:100%

Website Classification

Primary Category

social media network60% confidence
Type: static
Method: ml+structural

All Detected Categories

social media network
60%
forum community discussion
48%
adult content
28%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
163.176.8.218Aws · CLOUDFrankfurt am Main, Hesse, Germany
AS16509Amazon.com, Inc.
135.157.26.135Aws · CLOUDFrankfurt am Main, Hesse, Germany
AS16509Amazon.com, Inc.
22--

Detected Technologies2

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1C3F2DCF0491730A6996B62F271291F0F58F6D287F7070D25B7FC285AEF85D608A870E6

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:7+oEh5oMM0fnfs7JO+wzJszUbvIhjE18C66hqcuL8+1ek/fcLcbdc7mSXEhmJLvp:7+oEh5oMM0fnfs7JO+wzJszUbvIhjE1F

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:34968:SJgZpkRy5EIBZgoEQjgKBbAGNCAVTAhKDIQMsiAQgazAR6JABoaAFBENAAbEb7QACDwyIIIwJBAYeg6B5IAFCsQUCYAwDgpB

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:00181818183cffff
Perceptual Hash:cc4c33336666e699
Difference Hash:0c32b2b2b232300d
Wavelet Hash:0018181818ffffff
Color Hash:#40931f

Other Hashes

Crop Resistant:0c32b2b2b232300d

Scan History

Scan history not available

Unable to load historical scan data