Summary
This website contacted 86 IPs in 3 countries across 19 domains to perform 107 HTTP transactions. The main domain is inafrica.travel and was registered NaN years ago.
Submitted URL: https://inafrica.travel/destination/malawi
Effective URL: https://inafrica.travel/destination/malawi?locale=enRedirected
AI Security Verdict
High Risk
Confidence: 80%
Site contains suspicious password fields; treat as high‑risk phishing.
Risk Factors
Details
Page Title
Malawi
Scan Type
public
Language
English
Category
government public service
(33%)Domain Information
Domain 'inafrica.travel' uses the .travel top-level domain while skipping any subdomain. The core label 'inafrica' covers 8 characters holding 4 vowels versus four consonants. It segments into two words: in, africa. Median word length comes out to 4 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 | 3.5.81.129 | Boardman, Oregon, United States | AS16509AMAZON-02 |
| 1 | 157.240.0.6 | Frankfurt am Main, Hesse, Germany | AS32934FACEBOOK |
| 1 | 3.5.86.159 | Boardman, Oregon, United States | AS16509AMAZON-02 |
| 1 | 142.250.185.202 | United States | AS15169GOOGLE |
| 1 | 52.92.152.50 | Boardman, Oregon, United States | AS16509AMAZON-02 |
| 1 | 13.32.121.123 | New York, New York, United States | AS16509AMAZON-02 |
| 1 | 142.250.184.195 | United States | AS15169GOOGLE |
| 1 | 142.250.185.78 | United States | AS15169GOOGLE |
| 1 | 54.148.93.126 | Boardman, Oregon, United States | AS16509AMAZON-02 |
| 1 | 13.32.121.50 | New York, New York, United States | AS16509AMAZON-02 |
| 107 | 86 | - | - |
Detected Technologies4
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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