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Security Scan Report: ninininininini-0u2glvq8f1.edgeone.app

Submitted: Mar 25, 2026, 4:01:57 PMCompleted: Mar 25, 2026, 4:03:22 PMpubliccompleted
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Summary

This website contacted 6 IPs in 2 countries across 6 domains to perform 15 HTTP transactions. The main domain is ninininininini-0u2glvq8f1.edgeone.app and was registered NaN years ago.

Submitted URL: https://ninininininini-0u2glvq8f1.edgeone.app/SwitchtobeltraOS10.html

The Cisco Umbrella rank of the primary domain is #455,732 of the top 1 million websites

AI Security Verdict

Low Risk

Confidence: 78%

3
Risk Score

Site shows moderate suspicion due to unknown subdomain age and low ranking, but no malicious content or credential collection detected.

Risk Factors
Subdomain on hosting platform with unknown creation date
Low domain ranking indicating limited reputation
High JavaScript obfuscation score (potentially suspicious)
Safety Factors
No credential or payment collection forms
No malicious Indicators of Compromise matches
No network IDS alerts
Uses reputable CDN providers (tailwindcss.com, cloudflare.com, fonts.googleapis.com)
Served over HTTPS (implied by edgeone.app hosting)
Domain age information unavailable

Details

Page Title

BeltraOS 10 - Home Edition (Ultimate Terminal)

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

technology software

(83%)

Domain Information

Within the application-focused generic top-level domain (.app), 'ninininininini-0u2glvq8f1.edgeone.app' is registered; it also runs on subdomain 'ninininininini-0u2glvq8f1'. The core label 'edgeone' covers 7 characters split between 4 vowels and 3 consonants. Splitting it apart reveals 2 words: edge, one. The median word length lands at 3.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://ninininininini-0u2glvq8f1.edgeone.app/SwitchtobeltraOS10.html

Page Load Overview

1.34s
Total Load Time
13
HTTP Requests
6
Domains
3.6 MB
Total Size

Language Analysis

Primary Language

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

Detection Details

Language Code:en
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:en
Text Length:351 chars
Detector Agreement:100%

Website Classification

Primary Category

technology software83% confidence
Type: static
Method: ml+structural

All Detected Categories

technology software
83%
entertainment media
82%
documentation technical
57%
government public service
30%
adult content
29%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
3172.67.69.36Singapore
AS15169
2142.251.140.163United States
AS15169Google LLC
2104.17.25.14United States
AS13335Cloudflare, Inc.
2172.67.68.11United States
AS13335Cloudflare, Inc.
2172.217.16.170United States
AS15169Google LLC
243.152.26.58Singapore
AS139341ACE
136--

Detected Technologies4

Cloudflare
50%
Tailwind CSS
30%
cdnjs
20%
Three.js
20%

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1D7341A22B2622036957780EF649B834F74708107FA47DA0CBB7D51E0BFCADE6957668C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:k5trQzNjLM4I0hRNSYey67VNsccJaXVROCgTtj0j0MEDJ6JlhjcKSO0B3zuijlQg:uB2hFzcXP+CUwZeV

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:237989:AJAGgkaMiiIwOACAooewux7kuJeACUXBqSAMAgkbgCQCQ0KAICLArPISVAEgDAgDBpQIThjEEEAgBRaPEhVpYAAAABUfAGU3

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:7872738307373f3f
Perceptual Hash:b649c13638c9c73b
Difference Hash:c1c6c6362c6c7c7c
Wavelet Hash:7870730307273f1f
Color Hash:#87c5b5

Other Hashes

Crop Resistant:c1c6c6362c6c7c7c,3e3d1d3fcfe77338

Scan History

Scan history not available

Unable to load historical scan data