Summary
This website contacted 55 IPs in 4 countries across 16 domains to perform 68 HTTP transactions. The main domain is umassmed.edu and was registered NaN years ago.
Submitted URL: https://www.umassmed.edu/dcoe/diabetes-care/success-stories/2020/09/mark-andrews/
The Cisco Umbrella rank of the primary domain is #216,745 of the top 1 million websites
AI Security Verdict
Safe Website
Confidence: 96%
Legitimate page with no security concerns.
Safety Factors
Details
Page Title
Mark Andrews | Type 1 Diabetes Success Story
Scan Type
public
Language
English
Category
healthcare medical
(51%)Domain Information
You're looking at domain 'www.umassmed.edu' on the sponsored educational top-level domain (.edu), featuring subdomain 'www'. Its registrable label 'umassmed' stretches across 8 characters holding three vowels versus 5 consonants. It segments into 2 words: umass, med. Expect four 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 |
|---|---|---|---|
| 30 | 172.64.149.121 | United States | AS13335CLOUDFLARENET |
| 4 | 172.67.139.119 | United States | AS13335CLOUDFLARENET |
| 4 | 216.239.32.36 | United States | AS15169GOOGLE |
| 4 | 142.250.184.195 | United States | AS15169GOOGLE |
| 3 | 151.101.130.137 | San Francisco, California, United States | AS54113FASTLY |
| 3 | 142.250.185.142 | United States | AS15169GOOGLE |
| 3 | 142.250.185.232 | United States | AS15169GOOGLE |
| 3 | 142.250.185.234 | United States | AS15169GOOGLE |
| 2 | 20.50.88.245 | Amsterdam, North Holland, Netherlands | AS8075MICROSOFT-CORP-MSN-AS-BLOCK |
| 2 | 54.158.196.145 | Ashburn, Virginia, United States | AS14618AMAZON-AES |
| 68 | 55 | - | - |
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
Scan History
Scan history not available
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