Security Scan Report: www.sibfl.gov

Redirected to: https://www.sibfl.gov/Home

Submitted: Nov 20, 2025, 5:34:42 PMCompleted: Nov 20, 2025, 5:38:50 PMpubliccompleted
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Summary

This website contacted 109 IPs in 3 countries across 19 domains to perform 85 HTTP transactions. The main domain is sibfl.gov and was registered NaN years ago.

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

Effective URL: https://www.sibfl.gov/HomeRedirected

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

Legitimate municipal website with no detected threats.

Safety Factors
Established municipal domain (sibfl.gov)
Minimal risk category from domain age analysis
No credential or payment collection forms
Domain age information unavailable

Details

Page Title

Home - Sunny Isles Beach, FL

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

government

(48%)

Domain Information

You're looking at domain 'www.sibfl.gov' on the United States government-restricted top-level domain (.gov) and includes subdomain 'www'. The registrable portion 'sibfl' spans 5 characters with 1 vowel and 4 consonants. Tokenizing the label suggests two words: sib, fl. Average segment length settles at 2.5 characters. No strong language cues emerged from the frequency lists.

Screenshot

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

Page Load Overview

2.58s
Total Load Time
85
HTTP Requests
19
Domains
2.9 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-US
Text Length:8,625 chars
Detector Agreement:75%

Website Classification

Primary Category

government48% confidence
Type: spa
Method: ml+structural

All Detected Categories

government
48%
adult content
29%
news/blog
20%
forum
20%

Detected Features

Search
OG: article

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
432.21.239.30Frankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
11142.250.186.142United States
AS15169GOOGLE
423.32.238.192Frankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
32.16.168.11Frankfurt am Main, Hesse, Germany
AS20940Akamai International B.V.
3142.250.185.234United States
AS15169GOOGLE
2108.138.7.107United States
AS16509AMAZON-02
2216.239.34.36United States
AS15169GOOGLE
2142.250.186.131United States
AS15169GOOGLE
2216.58.206.42United States
AS15169GOOGLE
2142.250.185.238United States
AS15169GOOGLE
85109--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1C0F36D738582207E0123A2EA36B1FB1CB0A3954FE62B5D42F6ED03196FD5E465D0768F

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:2a417DhX9kc87vOgove4JEFIEurI0RBNxvEg6rBv32jNBEmNBEpPCz:2avc8bOgove4WyBxvEg6rBv32jNBEmNF

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:172172:AgUmXEEM8AyQIsQTmupcoCZpRyTQAKFgeFDAAXAGYBAYRd1AEFl4CgB0JApBEAkpQBUmgiggWAQKzCgDOPxRAECKIjRR+UgN

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:00000307040cffff
Perceptual Hash:9e0ac15bf4ae2ce4
Difference Hash:79592f2d3438280c
Wavelet Hash:0000179f868cffff
Color Hash:#862d4f

Scan History

Scan history not available

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