Summary
This website contacted 26 IPs in 2 countries across 6 domains to perform 32 HTTP transactions. The main domain is dinora93.github.io and was registered NaN years ago.
Submitted URL: https://dinora93.github.io/siman.github.io/
The Cisco Umbrella rank of the primary domain is #621,173 of the top 1 million websites
AI Security Verdict
High Risk
Confidence: 88%
High risk phishing site impersonating Siman; avoid and report.
Risk Factors
Details
Page Title
Tienda Online de Almacenes Siman | El Salvador | Siman.com
Scan Type
public
Language
Spanish
Category
unknown
(0%)Domain Information
The domain 'dinora93.github.io' uses the British Indian Ocean Territory country-code top-level domain (.io) with subdomain 'dinora93'. The core label 'github' covers 6 characters with two vowels and 4 consonants. Splitting it apart reveals 3 words: g, it, hub. Median word length is 2 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 |
|---|---|---|---|
| 22 | 104.16.79.6 | United States | AS13335CLOUDFLARENET |
| 7 | 104.16.78.6 | United States | AS13335CLOUDFLARENET |
| 3 | 104.17.25.14 | United States | AS13335CLOUDFLARENET |
| 3 | 185.199.108.153 | United States | AS54113FASTLY |
| 2 | 2.16.241.4 | Frankfurt am Main, Hesse, Germany | AS20940Akamai International B.V. |
| 1 | 185.199.109.153 | San Francisco, California, United States | AS54113FASTLY |
| 1 | 185.199.111.153 | United States | AS54113FASTLY |
| 1 | 142.250.185.206 | United States | AS15169GOOGLE |
| 1 | 17.253.57.206 | Frankfurt am Main, Hesse, Germany | AS6185APPLE-AUSTIN |
| 1 | 17.253.57.208 | Frankfurt am Main, Hesse, Germany | AS6185APPLE-AUSTIN |
| 32 | 26 | - | - |
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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