Summary
This website contacted 1 IP in 1 country across 1 domain to perform 2 HTTP transactions. The main domain is ordinealessandria.conaf.it and was registered NaN years ago.
Submitted URL: http://ordinealessandria.conaf.it/
Effective URL: https://ordinealessandria.conaf.it/Redirected
AI Security Verdict
Low Risk
Confidence: 78%
Site appears legitimate and long‑standing, but the lone password field without a username is unusual; proceed cautiously.
Risk Factors
Safety Factors
Details
Page Title
Ordine dei Dottori Agronomi e dei Dottori Forestali della Provincia di Alessandria
Scan Type
public
Language
Italian
Category
government public service
(55%)Domain Information
The domain 'ordinealessandria.conaf.it' uses the Italian country-code top-level domain (.it); it also runs on subdomain 'ordinealessandria'. Its registrable label 'conaf' stretches across 5 characters containing two vowels alongside 3 consonants. Breaking it apart gives two words: co, naf. Average segment length settles at 2.5 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 |
|---|---|---|---|
| 49 | 178.32.142.143 | France | AS16276OVH SAS |
| 49 | 1 | - | - |
Detected Technologies4
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
Other Hashes
Scan History
Scan history not available
Unable to load historical scan data