Summary
This website contacted 6 IPs in 3 countries across 6 domains to perform 1 HTTP transaction. The main domain is login.microsoftonline.com and was registered NaN years ago.
Submitted URL: http://energyharvesting.neo-apps.org/
Effective URL: https://login.microsoftonline.com/e95ee888-ca71-4956-b19c-2dade1a55938/oauth2/v2.0/authorize?response_type=id_token&redirect_uri=https%3A%2F%2Fenergyharvesting.neo-apps.org%2F.auth%2Flogin%2Faad%2Fcallback&client_id=19021802-14fc-4c1a-8020-5bba50bb7be7&scope=openid+profile+email&response_mode=form_post&nonce=165256692887466f9a1c421221ae287e_20260228124812&state=redir%3D%252F&sso_reload=trueRedirected
AI Security Verdict
High Risk
Confidence: 88%
Phishing page impersonating Microsoft login; do not enter credentials.
Risk Factors
Details
Page Title
Sign in to your account
Scan Type
public
Language
English
Category
unknown
(0%)Domain Information
The domain 'energyharvesting.neo-apps.org' uses the non-profit oriented generic top-level domain (.org), featuring subdomain 'energyharvesting'. The second-level label 'neo-apps' is 8 characters long holding three vowels versus four consonants, plus one hyphen. Segmentation suggests two words: neo, apps. The median word length lands at 3.5 characters. No strong language cues emerged from the frequency lists.
Screenshot
Page Load Overview
Language Analysis
Primary Language
Detection Details
Website Classification
Primary Category
All Detected Categories
Detected Features
Domain & IP Information
| Requests | IP Address | Location | AS Autonomous System |
|---|---|---|---|
| 4 | 20.105.232.10 | Amsterdam, North Holland, Netherlands | AS8075Microsoft Corporation |
| 3 | 13.107.246.44 | United States | AS8075Microsoft Corporation |
| 3 | 20.190.160.64 | Germany | Unknown |
| 3 | 23.207.210.132 | Frankfurt am Main, Hesse, Germany | AS20940Akamai International B.V. |
| 3 | 20.190.159.2 | Unknown | Unknown |
| 3 | 20.190.159.130 | Unknown | Unknown |
| 19 | 6 | - | - |
Detected Technologies4
Content Similarity HashesFor malware variant detection
TLSH (Trend Micro Locality Sensitive Hash)
Security-focusedSpecialized for malware detection and similarity analysis
ssdeep (Context Triggered Piecewise Hashing)
Context-awareDetects similar content even with modifications
sdhash (Similarity Digest Hashing)
High-precisionHigh-precision similarity detection for forensic analysis
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
Other Hashes
Scan History
Scan history not available
Unable to load historical scan data