Security Scan Report: ordinegrosseto.conaf.it

Redirected to:
https://ordinegrosseto.conaf.it/
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Submitted: May 30, 2026, 7:32:02 AMCompleted: May 30, 2026, 7:33:09 AMpubliccompleted
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Summary

This website contacted 1 IP in 1 country across 1 domain to perform 4 HTTP transactions. The main domain is ordinegrosseto.conaf.it and was registered NaN years ago.

Submitted URL: http://ordinegrosseto.conaf.it/

Effective URL: https://ordinegrosseto.conaf.it/Redirected

AI Security Verdict

Low Risk

Confidence: 78%

2
Risk Score

Low risk – old, unranked domain with a password‑only field; no malicious indicators detected.

Risk Factors
Unranked domain despite claiming official professional organization
Password‑only form may confuse users
Safety Factors
Very old domain registration (20+ years)
No malicious signatures or network alerts
No external links to known malicious sites
No JavaScript malware patterns detected
No credential exfiltration observed
Domain age information unavailable

Details

Page Title

Ordine dei Dottori Agronomi e dei Dottori Forestali della Provincia di Grosseto

Scan Type

public

Language

🇮🇹

Italian

(80% confidence)

Category

government public service

(65%)

Domain Information

The domain name 'ordinegrosseto.conaf.it' uses the Italian country-code top-level domain (.it); it also runs on subdomain 'ordinegrosseto'. Count 5 characters in 'conaf' containing 2 vowels alongside 3 consonants. It segments into two words: co, naf. Median word length comes out to 2.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of http://ordinegrosseto.conaf.it/

Page Load Overview

1.23s
Total Load Time
47
HTTP Requests
2
Domains
94 KB
Total Size

Language Analysis

Primary Language

🇮🇹Italian
Code: it
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

Language Code:it
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:it
Text Length:1,495 chars
Detector Agreement:100%

Website Classification

Primary Category

government public service65% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

government public service
65%
documentation technical
33%

Detected Features

Search

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
47178.32.142.143France
AS16276OVH SAS
471--

Detected Technologies3

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T15B8267209CF67022015684C4B9B4A71B6BA5E32BCF4B1F04B3AD866F1BCBF44ED56716

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

192:OLoL/4zKXa5cgxbJRSZ4gR9OR9YCpg2EGt5rh8sY9emvp0Jdvdz:R4zKXANxPK4gitgWt5F8wK05

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:18467:dBkTAAWBwhAIkAB4AoBIp4Qig51iEAAFIAQgICGw7jSoRgyEhxKCkEACCABESIuuKTgNRYpYFKAjJEAIAoUBASKD8AYQEGYM

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:ffc7c7c3d3ffffff
Perceptual Hash:b1339acccc93b364
Difference Hash:0018181616000000
Wavelet Hash:3f1f0707003c3c3c
Color Hash:#79d288

Other Hashes

Crop Resistant:0018181616000000

Scan History

Scan history not available

Unable to load historical scan data