Summary
This website contacted 29 IPs in 1 country across 7 domains to perform 143 HTTP transactions. The main domain is argylefiredistrictfl.gov and was registered NaN years ago.
Submitted URL: https://www.argylefiredistrictfl.gov/
AI Security Verdict
Safe Website
Confidence: 92%
Legitimate government website with no apparent security threats.
Safety Factors
Details
Page Title
Fire Department | Argyle Fire Department | Florida
Scan Type
public
Language
English
Category
government
(95%)Domain Information
Domain 'www.argylefiredistrictfl.gov' uses the United States government-restricted top-level domain (.gov) and includes subdomain 'www'. The registrable portion 'argylefiredistrictfl' spans 20 characters with six vowels and 14 consonants. Word splitting yields four words: argyle, fire, district, fl. Expect 5 characters per word on average. No strong language cues emerged from the frequency lists.
Screenshot

Page Load Overview
Language Analysis
Primary Language
Detection Details
Website Classification
Primary Category
All Detected Categories
Detected Features
Domain & IP Information
| Requests | IP Address | Location | AS Autonomous System |
|---|---|---|---|
| 31 | 34.149.206.255 | Kansas City, Missouri, United States | AS396982GOOGLE-CLOUD-PLATFORM |
| 4 | 65.8.131.77 | United States | AS16509AMAZON-02 |
| 4 | 65.8.131.55 | United States | AS16509AMAZON-02 |
| 4 | 151.101.130.217 | San Francisco, California, United States | AS54113FASTLY |
| 4 | 184.73.61.188 | Ashburn, Virginia, United States | AS14618AMAZON-AES |
| 4 | 3.217.154.72 | Ashburn, Virginia, United States | AS14618AMAZON-AES |
| 4 | 151.101.194.217 | San Francisco, California, United States | AS54113FASTLY |
| 4 | 34.235.107.93 | Ashburn, Virginia, United States | AS14618AMAZON-AES |
| 4 | 65.8.131.125 | United States | AS16509AMAZON-02 |
| 4 | 44.205.48.111 | Ashburn, Virginia, United States | AS14618AMAZON-AES |
| 143 | 29 | - | - |
Content Similarity HashesFor malware variant detection
TLSH (Trend Micro Locality Sensitive Hash)
Security-focusedSpecialized for malware detection and similarity analysis
ssdeep (Context Triggered Piecewise Hashing)
Context-awareDetects similar content even with modifications
sdhash (Similarity Digest Hashing)
High-precisionHigh-precision similarity detection for forensic analysis
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
Other Hashes
Scan History
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