Security Scan Report: oldtowntownship-il.gov

Submitted: Dec 21, 2025, 1:03:51 AMCompleted: Dec 21, 2025, 1:04:31 AMpubliccompleted
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Summary

This website contacted 2 IPs in 2 countries across 2 domains to perform 31 HTTP transactions. The main domain is oldtowntownship-il.gov and was registered NaN years ago.

Submitted URL: https://oldtowntownship-il.gov/

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

Site appears legitimate with no security concerns.

Safety Factors
Government TLD (.gov) indicates official authority
Established domain age reduces suspicion
Clean content with no credential‑harvesting elements
Domain age information unavailable

Details

Page Title

Old Town Township - Welcome to Old Town Township, Illinois

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

government

(48%)

Domain Information

Domain 'oldtowntownship-il.gov' uses the United States government-restricted top-level domain (.gov) and has no subdomain. Count 18 characters in 'oldtowntownship-il' split between five vowels and twelve consonants; bonus characters include one hyphen. Segmentation suggests 3 words: oldtown, township, il. The median word length lands at 7 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://oldtowntownship-il.gov/

Page Load Overview

7.25s
Total Load Time
31
HTTP Requests
2
Domains
431 KB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

Language Code:en
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:en-US
Text Length:1,714 chars
Detector Agreement:100%

Website Classification

Primary Category

government48% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

government
48%
technology software
26%

Detected Features

Search

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
1513.89.172.17Des Moines, Iowa, United States
AS8075MICROSOFT-CORP-MSN-AS-BLOCK
152.23.7.25Frankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
312--

Detected Technologies4

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T137932915617628374257019ABEBF7A8E25B88047E1899C24FD6CCF085FC2ED81EF179E

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:C3ifmTuq4/MFTmQUh0PFVDrkig2aVVYr65WYgwoIUSX8xPmV+iaPvjG8uPX8:AUneDryHVVYiFOPv28

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:93804:mWCIERwkAhCSSKQggBu0ppCwRIhsiBEEQoYRBeFgELFHAjJYxEDhIsS9YkQIEHhMsoCWBhhAATPFOSMoQA4hRgFMQaAmSEkE

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:008324e70000ffff
Perceptual Hash:b637ad4d298342da
Difference Hash:170e4d8e79c12816
Wavelet Hash:0083e7e70800ffff
Color Hash:#c59887

Scan History

Scan history not available

Unable to load historical scan data