Summary
This website contacted 4 IPs in 2 countries across 4 domains to perform 17 HTTP transactions. The main domain is login.microsoftonline.com and was registered NaN years ago.
Submitted URL: https://marketplace-develop.app.goziro.com/oauth2/authorization/azure
Effective URL: https://login.microsoftonline.com/organizations/oauth2/v2.0/authorize?response_type=code&client_id=4b04fede-70dd-4f00-ac70-36d907bd6e69&scope=openid%20profile%20offline_access%20https://graph.microsoft.com/User.Read&state=gGp_wmizzyHDFUvErfwOMAA6lANhk1P0MTp9eLNX2A8%3D&redirect_uri=https://marketplace-develop.app.goziro.com/login/oauth2/code/&nonce=vnKfIf7Ikf6Lvq7GXD5BKh0lE85GiUKe-4yM4ycDXIU&sso_reload=trueRedirected
AI Security Verdict
Safe Website
Confidence: 92%
Legitimate OAuth login page; no phishing or scam indicators.
Safety Factors
Details
Page Title
Sign in to your account
Scan Type
public
Language
English
Category
unknown
(0%)Domain Information
The domain name 'marketplace-develop.app.goziro.com' uses the commercial generic top-level domain (.com) with subdomain 'marketplace-develop.app'. Count 6 characters in 'goziro' with three vowels and 3 consonants. Tokenizing the label suggests three words: go, zi, ro. Median word length comes out to 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 |
|---|---|---|---|
| 5 | 13.107.246.44 | United States | AS8075MICROSOFT-CORP-MSN-AS-BLOCK |
| 4 | 20.232.195.32 | Washington, Virginia, United States | AS8075MICROSOFT-CORP-MSN-AS-BLOCK |
| 4 | 40.126.31.73 | Dublin, Leinster, Ireland | AS8075MICROSOFT-CORP-MSN-AS-BLOCK |
| 4 | 20.190.159.71 | Unknown | Unknown |
| 17 | 4 | - | - |
Detected Technologies5
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