Security Scan Report: www.royalpalmbeachfl.gov

Submitted: Oct 2, 2025, 3:43:08 PMCompleted: Oct 2, 2025, 3:44:48 PMpubliccompleted
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Summary

This website contacted 23 IPs in 1 country across 7 domains to perform 43 HTTP transactions. The main domain is royalpalmbeachfl.gov and was registered NaN years ago.

Submitted URL: https://www.royalpalmbeachfl.gov/

AI Security Verdict

Safe Website

Confidence: 95%

1
Risk Score

The site appears to be a legitimate government website with no signs of phishing or malware.

Safety Factors
Official government TLD (.gov)
Well‑established domain age
No malicious Indicators of Compromise
No credential‑collecting forms
Domain age information unavailable

Details

Page Title

Home Page | Village of Royal Palm Beach Florida

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

government public service

(91%)

Domain Information

The domain 'www.royalpalmbeachfl.gov' uses the United States government-restricted top-level domain (.gov) with subdomain 'www'. The registrable portion 'royalpalmbeachfl' spans 16 characters containing 5 vowels alongside 11 consonants. Tokenizing the label suggests four words: royal, palm, beach, fl. Median word length comes out to 4.5 characters. 'royal' most often appears in English. You may catch it in Chinese (Pinyin) and Vietnamese as well.

Screenshot

Security scan screenshot of https://www.royalpalmbeachfl.gov/

Page Load Overview

47.02s
Total Load Time
43
HTTP Requests
7
Domains
800 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
Text Length:4,961 chars
Detector Agreement:100%

Website Classification

Primary Category

government public service91% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

government public service
91%
documentation technical
82%
government
48%

Detected Features

Search

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
21162.221.183.17Buffalo, New York, United States
AS16509AMAZON-02
1142.250.186.99United States
AS15169GOOGLE
1142.250.184.238United States
AS15169GOOGLE
1216.239.32.36United States
AS15169GOOGLE
1172.66.171.172United States
AS13335CLOUDFLARENET
1142.250.186.104United States
AS15169GOOGLE
1142.250.181.234United States
AS15169GOOGLE
12a00:1450:4001:82f::200aUnited StatesUnknown
1142.250.185.202United StatesUnknown
1216.239.34.36United StatesUnknown
4323--

Detected Technologies5

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T13233B65368D55413022226C67865773FD65340BADA030B40BBDCCB867FCAE4698AF2FE

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:8Kw/UapWCK6QP68rMGS/MO/RlkRk4REqVof:jw/UapK6PGS/MO/RlkR5RBVof

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:51333:SI0vEADbaQgAEDkc6RLUEOUAcobTAUARMAABYEweJFAjIwDkEEOghEgxRLyEi5g0lgAiUGJgqdEDfDqAtiMQAGA6CEIHKCPK

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:c080003c3d0000ff
Perceptual Hash:ca7f7570cadd3020
Difference Hash:18108761699791e9
Wavelet Hash:efc0003d3d1858ff
Color Hash:#862d3e

Other Hashes

Scan History

Scan history not available

Unable to load historical scan data