Security Scan Report: foresttownrcwi.gov

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Submitted: Dec 6, 2025, 6:06:46 AMCompleted: Dec 6, 2025, 6:08:40 AMpubliccompleted
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Summary

This website contacted 94 IPs in 2 countries across 16 domains to perform 56 HTTP transactions. The main domain is foresttownrcwi.gov and was registered NaN years ago.

Submitted URL: https://foresttownrcwi.gov/

AI Security Verdict

Safe Website

Confidence: 96%

0
Risk Score

Legitimate government website with no security concerns.

Safety Factors
Government domain (.gov) indicates official status
Contact details and mailing address provided
Search and newsletter forms are standard and non‑sensitive
No redirects, no hidden fields collecting credentials
Domain age information unavailable

Details

Page Title

Town of Forest

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

government

(48%)

Domain Information

Domain 'foresttownrcwi.gov' uses the United States government-restricted top-level domain (.gov) with no subdomain. The second-level label 'foresttownrcwi' is 14 characters long split between four vowels and ten consonants. Segmentation suggests four words: forest, town, rc, wi. Median word length is 3 characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://foresttownrcwi.gov/

Page Load Overview

1.64s
Total Load Time
56
HTTP Requests
16
Domains
2.6 MB
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
Text Length:2,042 chars
Detector Agreement:100%

Website Classification

Primary Category

government48% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

government
48%
legitimate website
32%

Detected Features

Search

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
12104.17.24.14United States
AS13335CLOUDFLARENET
879.127.211.90Frankfurt am Main, Hesse, Germany
AS60068Datacamp Limited
8188.114.97.3United States
AS13335CLOUDFLARENET
6142.250.185.219United States
AS15169GOOGLE
4142.250.185.163United States
AS15169GOOGLE
4142.250.185.202United States
AS15169GOOGLE
3151.101.65.229San Francisco, California, United States
AS54113FASTLY
234.209.202.62Boardman, Oregon, United States
AS16509AMAZON-02
2216.239.34.36United States
AS15169GOOGLE
2142.250.74.211United States
AS15169GOOGLE
5694--

Detected Technologies7

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T18543E732A4F1013B145351CC36E67B0EAAA1D20FD75B1944BAFEA7484FD7DD24A6B22C

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:AMjzn1QFIsDcfIIybjOEhWqW8WqWqWwZ0k6tAN43U:MgFfFFnAN43U

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:59774:AaBJhG5cQiBASXQDOEZABM4XxQQERIoSIH6RPgwBfRKqgYUMwCENFHMnACiaGFloAgYABkgYACNA0sjRsjQCipLpBDBsAIm8

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:ff0000101000ffff
Perceptual Hash:cc42f1b68ca33ce3
Difference Hash:79c0e3e3e364d333
Wavelet Hash:ff2030191010ffff
Color Hash:#2d5b86

Scan History

Scan history not available

Unable to load historical scan data