Summary
This website contacted 7 IPs in 3 countries across 7 domains to perform 36 HTTP transactions. The main domain is login.microsoftonline.com and was registered NaN years ago.
Submitted URL: http://lotoboard.com/auth/microsoft
Effective URL: https://login.microsoftonline.com/b1f3dd71-d041-468d-b000-b008d3a7b0ac/oauth2/v2.0/authorize?client_id=7582c8b5-9640-4bae-a51d-c677542f86db&redirect_uri=https%3A%2F%2Flotoboard.com%2Fauth%2Fmicrosoft%2Fcallback&scope=User.Read&response_type=code&state=sFwq9uzNGoBAU4myg9dHwHWS3rMJV16XlbROjh4p&sso_reload=trueRedirected
AI Security Verdict
Safe Website
Confidence: 92%
Site appears legitimate; uses Microsoft OAuth for login with no malicious indicators.
Safety Factors
Details
Page Title
Sign in to your account
Scan Type
public
Language
English
Category
phishing scam
(69%)Domain Information
Within the commercial generic top-level domain (.com), 'lotoboard.com' is registered and has no subdomain. The second-level label 'lotoboard' is 9 characters long split between 4 vowels and 5 consonants. Breaking it apart gives three words: lo, to, board. The median word length lands at two 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 |
|---|---|---|---|
| 7 | 20.190.159.68 | Dublin, Leinster, Ireland | AS8075Microsoft Corporation |
| 2 | 40.126.31.73 | Germany | |
| 2 | 217.160.0.83 | Germany | AS8560IONOS SE |
| 2 | 23.207.210.137 | Frankfurt am Main, Hesse, Germany | AS20940Akamai International B.V. |
| 2 | 13.107.246.44 | United States | AS8075Microsoft Corporation |
| 2 | 52.178.17.3 | Unknown | Unknown |
| 2 | 13.107.246.45 | Unknown | Unknown |
| 19 | 7 | - | - |
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
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