Summary
This website contacted 2 IPs in 1 country across 12 domains to perform 2 HTTP transactions. The main domain is artsci.unm.edu and was registered 40 years ago.
Submitted URL: https://artsci.unm.edu
The Cisco Umbrella rank of the primary domain is #60,226 of the top 1 million websites
AI Security Verdict
Safe Website
Confidence: 96%
The site is a legitimate university page with no malicious indicators.
Safety Factors
Details
Page Title
College of Arts & Sciences | The University of New Mexico
Scan Type
public
Language
English
Category
education
(90%)Domain Information
You're looking at domain 'artsci.unm.edu' on the sponsored educational top-level domain (.edu) and includes subdomain 'artsci'. Its registrable label 'unm' stretches across 3 characters split between one vowel and 2 consonants. It segments into two words: un, m. Average segment length settles at 1.5 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 |
|---|---|---|---|
| 27 | 129.24.172.164 | Albuquerque, New Mexico, United States | AS3388University of New Mexico |
| 26 | 64.106.65.197 | Albuquerque, New Mexico, United States | AS3388University of New Mexico |
| 53 | 2 | - | - |
Page Statistics
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
Scan History
Scan history not available
Unable to load historical scan data