Summary
This website contacted 12 IPs in 1 country across 12 domains to perform 88 HTTP transactions. The main domain is will.illinois.edu and was registered NaN years ago.
Submitted URL: https://will.illinois.edu/21stshow/story/best-of-ceo-damola-adamolekun-had-first-red-lobster-experience-in-springfield-illinois
The Cisco Umbrella rank of the primary domain is #53,607 of the top 1 million websites
AI Security Verdict
Safe Website
Confidence: 95%
Legitimate news article from Illinois Public Media with no security concerns.
Safety Factors
Details
Page Title
Best of: CEO Damola Adamolekun had first Red Lobster experience in Springfield, Illinois | The 21st Show | Illinois Public Media
Scan Type
public
Language
English
Category
education learning
(76%)Domain Information
Domain 'will.illinois.edu' uses the sponsored educational top-level domain (.edu); it also runs on subdomain 'will'. The second-level label 'illinois' is 8 characters long containing 4 vowels alongside 4 consonants. It segments into 1 word: illinois. 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 |
|---|---|---|---|
| 12 | 142.250.185.168 | United States | AS15169GOOGLE |
| 5 | 18.244.18.6 | United States | AS16509AMAZON-02 |
| 5 | 18.245.46.48 | United States | |
| 5 | 52.222.136.18 | United States | AS16509AMAZON-02 |
| 5 | 142.251.141.110 | United States | AS15169GOOGLE |
| 5 | 216.239.32.36 | United States | AS15169GOOGLE |
| 5 | 142.250.185.99 | United States | AS15169GOOGLE |
| 5 | 18.245.64.167 | United States | AS16509AMAZON-02 |
| 5 | 142.250.185.138 | United States | AS15169GOOGLE |
| 5 | 104.20.20.192 | United States | Unknown |
| 67 | 12 | - | - |
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
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