Summary
This website contacted 3 IPs in 1 country across 3 domains to perform 2 HTTP transactions. The main domain is med.nyu.edu and was registered NaN years ago.
Submitted URL: https://med.nyu.edu
The Cisco Umbrella rank of the primary domain is #64,668 of the top 1 million websites
AI Security Verdict
Safe Website
Confidence: 94%
The site is an official NYU medical school page with no malicious indicators.
Safety Factors
Details
Page Title
NYU Grossman School of Medicine
Scan Type
public
Language
English
Category
education learning
(78%)Domain Information
The domain name 'med.nyu.edu' uses the sponsored educational top-level domain (.edu), featuring subdomain 'med'. The registrable portion 'nyu' spans 3 characters with 1 vowel and 2 consonants. Tokenizing the label suggests 1 word: nyu. The median word length lands at 3 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 |
|---|---|---|---|
| 52 | 159.60.130.74 | United States | AS35280F5 Networks SARL |
| 52 | 54.192.35.67Cloudfront · CDN | United States | AS16509Amazon.com, Inc. |
| 52 | 216.120.157.27 | New York, New York, United States | AS394666NYU Langone Health |
| 156 | 3 | - | - |
Page Statistics
Detected Technologies4
Content Similarity HashesFor malware variant detection
TLSH (Trend Micro Locality Sensitive Hash)
Specialized for malware detection and similarity analysis
ssdeep (Context Triggered Piecewise Hashing)
Detects 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