Summary
This website contacted 11 IPs in 2 countries across 7 domains to perform 38 HTTP transactions. The main domain is gurnee.il.us and was registered NaN years ago.
Submitted URL: https://www.gurnee.il.us/
AI Security Verdict
Safe Website
Confidence: 95%
0
Risk Score
Legitimate municipal website with no security concerns
Safety Factors
Established government domain
Transparent contact and address information
Regularly updated public service content
Domain age information unavailable
Details
Page Title
Village of Gurnee
Scan Type
public
Language
🇺🇸
(80% confidence)English
Category
government public service
(72%)Screenshot

Page Load Overview
3.21s
Total Load Time
38
HTTP Requests
7
Domains
5.4 MB
Total Size
Language Analysis
Primary Language
🇺🇸English
Code: enConfidence:80%
Script:Latin
Direction:ltr
Detection Details
Language Code:en
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:en
Text Length:10,626 chars
Detector Agreement:100%
Website Classification
Primary Category
government public service72% confidence
Type: dynamic
Method: ml+structural
All Detected Categories
government public service
72%
documentation technical
32%
corporate
25%
Detected Features
OG: website
Domain & IP Information
| Requests | IP Address | Location | AS Autonomous System |
|---|---|---|---|
| 27 | 12.53.28.118 | United States | AS27482AECP-AS |
| 4 | 172.217.18.3 | United States | AS15169GOOGLE |
| 3 | 2a00:1450:4001:82b::2003 | Frankfurt am Main, Hesse, Germany | AS15169GOOGLE |
| 3 | 2a03:2880:f084:105:face:b00c:0:3 | Frankfurt am Main, Hesse, Germany | AS32934FACEBOOK |
| 3 | 2a00:1450:4001:81d::2008 | Frankfurt am Main, Hesse, Germany | AS15169GOOGLE |
| 3 | 2a00:1450:4001:830::200a | Frankfurt am Main, Hesse, Germany | AS15169GOOGLE |
| 2 | 172.217.18.8 | United States | AS15169GOOGLE |
| 2 | 157.240.0.6 | Frankfurt am Main, Hesse, Germany | AS32934FACEBOOK |
| 1 | 12.133.121.27 | Gallipolis, Ohio, United States | AS27482AECP-AS |
| 1 | 142.251.140.202 | United States | AS15169GOOGLE |
| 38 | 11 | - | - |
Detected Technologies4
Content Similarity HashesFor malware variant detection
TLSH (Trend Micro Locality Sensitive Hash)
Security-focusedSpecialized for malware detection and similarity analysis
T18EC3934289F42179215B96C17D70AB2ABA83815FDD0F1501BD6CAB4A9FF1E72AD0F34C
ssdeep (Context Triggered Piecewise Hashing)
Context-awareDetects similar content even with modifications
1536:z7tvEqkolYiLygJmEIbD09n3Z6TQxmYD+vQierzRi2I+TB3RD80AWJ++4L9Qjusy:/6olDnhsHF2ho9Yqj
sdhash (Similarity Digest Hashing)
High-precisionHigh-precision similarity detection for forensic analysis
sdhash:3:129208:AGAyohnQpugQ5oAAPJUQiCc5oUEqABgIhQS083DMIdBkEIQrnBQAYmBRBDSEEwEjcosBRAAoKwjE5E0TgEXYIUISAXQqYSBP
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:ffffc1e078000103
Perceptual Hash:a9fbbc81c24e7528
Difference Hash:791b03c1d1caf7ff
Wavelet Hash:ffffc1f07008010f
Color Hash:#1f933e
Other Hashes
Scan History
Scan history not available
Unable to load historical scan data