Summary
This website contacted 48 IPs in 2 countries across 18 domains to perform 194 HTTP transactions. The main domain is bullheadcityaz.gov and was registered NaN years ago.
Submitted URL: https://www.bullheadcityaz.gov/
AI Security Verdict
Safe Website
Confidence: 95%
Legitimate government website with no detected threats.
Safety Factors
Details
Page Title
Home | Bullhead City
Scan Type
public
Language
English
Category
government public service
(79%)Domain Information
You're looking at domain 'www.bullheadcityaz.gov' on the United States government-restricted top-level domain (.gov), featuring subdomain 'www'. The second-level label 'bullheadcityaz' is 14 characters long with 5 vowels and nine consonants. Splitting it apart reveals 4 words: bull, head, city, az. Median word length is four characters. 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 |
|---|---|---|---|
| 121 | 13.107.213.45 | United States | AS8075MICROSOFT-CORP-MSN-AS-BLOCK |
| 6 | 142.250.185.131 | United States | AS15169GOOGLE |
| 6 | 142.250.184.228 | United States | AS15169GOOGLE |
| 4 | 2.19.126.198 | Frankfurt am Main, Hesse, Germany | AS20940Akamai International B.V. |
| 4 | 142.250.186.131 | United States | AS15169GOOGLE |
| 4 | 13.107.213.44 | United States | AS8075MICROSOFT-CORP-MSN-AS-BLOCK |
| 4 | 184.24.77.146 | Frankfurt am Main, Hesse, Germany | AS20940Akamai International B.V. |
| 4 | 104.17.25.14 | United States | AS13335CLOUDFLARENET |
| 4 | 2a00:1450:4001:82b::2002 | Frankfurt am Main, Hesse, Germany | AS15169GOOGLE |
| 4 | 2a00:1450:4001:81c::200e | Frankfurt am Main, Hesse, Germany | AS15169GOOGLE |
| 194 | 48 | - | - |
Detected Technologies2
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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