Summary
This website contacted 5 IPs in 2 countries across 5 domains to perform 35 HTTP transactions. The main domain is login.microsoftonline.com and was registered NaN years ago.
Submitted URL: https://appleton.historicnewengland.org/
Effective URL: https://login.microsoftonline.com/common/oauth2/authorize?response_type=code&scope=openid&domain_hint=&client_id=485f4095-d656-4b10-b195-4b6af3b2affb&resource=https%3A%2F%2Fgraph.microsoft.com&redirect_uri=https%3A%2F%2Fappleton.historicnewengland.org%2Fwp-login.php&state=%7B21D15E02-BB0C-B4AF-EF8C-11F4BBECDF24%7D&nonce=%7B21D15E02-BB0C-B4AF-EF8C-11F4BBECDF24%7D&sso_reload=trueRedirected
The Cisco Umbrella rank of the primary domain is #990,606 of the top 1 million websites
AI Security Verdict
Low Risk
Confidence: 92%
Legitimate site using Microsoft OAuth for authentication; no phishing or malware indicators detected.
Safety Factors
Details
Page Title
Sign in to your account
Scan Type
public
Language
English
Category
unknown
(0%)Domain Information
Within the non-profit oriented generic top-level domain (.org), 'appleton.historicnewengland.org' is registered with subdomain 'appleton'. The registrable portion 'historicnewengland' spans 18 characters split between 6 vowels and 12 consonants. Word splitting yields 3 words: historic, new, england. Expect seven characters per word on average. 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 |
|---|---|---|---|
| 6 | 13.107.246.44 | United States | AS8075Microsoft Corporation |
| 3 | 20.190.159.71 | Germany | |
| 3 | 23.207.210.132 | Frankfurt am Main, Hesse, Germany | AS20940Akamai International B.V. |
| 3 | 52.202.193.32 | Ashburn, Virginia, United States | AS14618Amazon.com, Inc. |
| 3 | 20.190.159.129 | Unknown | Unknown |
| 18 | 5 | - | - |
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