Summary
This website contacted 29 IPs in 2 countries across 9 domains to perform 58 HTTP transactions. The main domain is uncleg.com and was registered NaN years ago.
Submitted URL: https://uncleg.com/circular/
The Cisco Umbrella rank of the primary domain is #632,592 of the top 1 million websites
AI Security Verdict
Safe Website
Confidence: 95%
The site shows no security concerns and appears legitimate.
Safety Factors
Details
Page Title
Weekly Circular - Uncle Giuseppe's Marketplace–Nationwide Shipping
Scan Type
public
Language
English
Category
technology software
(50%)Domain Information
Domain 'uncleg.com' uses the commercial generic top-level domain (.com). Count 6 characters in 'uncleg' containing two vowels alongside 4 consonants. Breaking it apart gives two words: uncle, g. Average segment length settles 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 |
|---|---|---|---|
| 43 | 104.154.239.213 | Council Bluffs, Iowa, United States | AS396982GOOGLE-CLOUD-PLATFORM |
| 3 | 157.240.0.35 | Frankfurt am Main, Hesse, Germany | AS32934FACEBOOK |
| 3 | 216.58.206.42 | United States | AS15169GOOGLE |
| 2 | 142.250.186.36 | United States | AS15169GOOGLE |
| 2 | 172.64.147.103 | United States | AS13335CLOUDFLARENET |
| 2 | 104.17.24.14 | United States | AS13335CLOUDFLARENET |
| 2 | 157.240.0.6 | Frankfurt am Main, Hesse, Germany | AS32934FACEBOOK |
| 2 | 142.250.186.74 | United States | AS15169GOOGLE |
| 2 | 54.161.58.211 | Ashburn, Virginia, United States | AS14618AMAZON-AES |
| 2 | 2600:1f10:47fd:dc06:3b36:1323:fb4c:8486 | Ashburn, Virginia, United States | AS14618AMAZON-AES |
| 58 | 29 | - | - |
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
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