Summary
This website contacted 12 IPs in 2 countries across 7 domains to perform 43 HTTP transactions. The main domain is comune.dicomano.fi.it.
Submitted URL: https://www.comune.dicomano.fi.it/
AI Security Verdict
Safe Website
Confidence: 92%
1
Risk Score
The site appears to be a legitimate municipal website with no phishing or malware indicators.
Safety Factors
Page displays legitimate municipal information
Only a simple search form without data collection
No hidden or disguised fields
Domain age information unavailable
Details
Page Title
| Comune di Dicomano
Scan Type
public
Language
🇮🇹
(80% confidence)Italian
Category
government public service
(50%)Screenshot
Page Load Overview
24.25s
Total Load Time
43
HTTP Requests
7
Domains
1.6 MB
Total Size
Language Analysis
Primary Language
🇮🇹Italian
Code: itConfidence:80%
Script:Latin
Direction:ltr
Detection Details
Language Code:it
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:it
Text Length:4,616 chars
Detector Agreement:100%
Website Classification
Primary Category
government public service50% confidence
Type: dynamic
Method: ml+structural
All Detected Categories
government public service
50%
real estate property
40%
Detected Features
Search
Domain & IP Information
| Requests | IP Address | Location | AS Autonomous System |
|---|---|---|---|
| 10 | 35.152.40.99 | Milan, Lombardy, Italy | AS16509AMAZON-02 |
| 3 | 159.213.247.22 | Florence, Tuscany, Italy | AS6882Regione Toscana |
| 3 | 159.213.236.37 | Florence, Tuscany, Italy | AS6882Regione Toscana |
| 3 | 172.67.71.156 | United States | AS13335CLOUDFLARENET |
| 3 | 159.213.236.230 | Florence, Tuscany, Italy | AS6882Regione Toscana |
| 3 | 159.213.236.43 | Florence, Tuscany, Italy | AS6882Regione Toscana |
| 3 | 2606:4700:20::681a:6e5 | United States | Unknown |
| 3 | 104.26.6.229 | United States | Unknown |
| 3 | 35.152.38.193 | United States | Unknown |
| 3 | 2606:4700:20::ac43:479c | United States | Unknown |
| 43 | 12 | - | - |
Detected Technologies3
Content Similarity HashesFor malware variant detection
TLSH (Trend Micro Locality Sensitive Hash)
Security-focusedSpecialized for malware detection and similarity analysis
T1BCD3531163D2205B21670EDF7069AB38761E7C9EE2430CCAEB7E3765CBC9DD20638599
ssdeep (Context Triggered Piecewise Hashing)
Context-awareDetects similar content even with modifications
1536:IvDvzvyDjZevlfIgFOoxygOfykxXHzyO5l+hR9CbVlQc9B6cDjIKqpDF09k3q/cn:IbbmUcCkV4eE
sdhash (Similarity Digest Hashing)
High-precisionHigh-precision similarity detection for forensic analysis
sdhash:3:135678:gBMgAihoDSNEEYkACQABkIQgE6A6qZAAFIzbQ4tCkmCiqJakIMcjszHkMJIlAAAMGAzOCQAhHBmnIAJS0DhGnCIUgRIAAgMr
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
Average Hash:0000f1fff1f39ff9
Perceptual Hash:ea07193443bce1fa
Difference Hash:9cc3232703232b2b
Wavelet Hash:0000f1f7f1f18df9
Color Hash:#931f4a
Other Hashes
Scan History
Scan history not available
Unable to load historical scan data