Security Scan Report: knottcountyky.gov

Submitted: Oct 19, 2025, 7:04:32 AMCompleted: Oct 19, 2025, 7:05:48 AMpubliccompleted
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Summary

This website contacted 17 IPs in 2 countries across 4 domains to perform 10 HTTP transactions. The main domain is knottcountyky.gov and was registered NaN years ago.

Submitted URL: https://knottcountyky.gov/

AI Security Verdict

Safe Website

Confidence: 92%

2
Risk Score

Site appears legitimate; minor redirect issue but no malicious activity.

Risk Factors
Circular redirect detected (potentially suspicious configuration)
Safety Factors
Government (.gov) domain
Established domain age (>2 years)
No forms collecting credentials or payment information
Page returns 403 Forbidden, indicating restricted access
Domain age information unavailable

Details

Primary Scan Blocked — Fallback Capture Shown

The primary scanner could not load this page (possible bot protection). The screenshot and page details shown were captured by a fallback browser that loaded the page successfully.

Page Title

Knott County Fiscal Court

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

government

(48%)

Domain Information

The domain 'knottcountyky.gov' uses the United States government-restricted top-level domain (.gov) and has no subdomain. Its registrable label 'knottcountyky' stretches across 13 characters holding 3 vowels versus 10 consonants. Word splitting yields three words: knott, county, ky. Average segment length settles at five characters. The linguistic tilt is Vietnamese for 'knott'. You will also see it in Norwegian and English contexts. Net impression: Vietnamese phrase.

Screenshot

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

Page Load Overview

10.15s
Total Load Time
10
HTTP Requests
4
Domains
88 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:105 chars
Detector Agreement:100%

Website Classification

Primary Category

government48% confidence
Type: static
Method: ml+structural

All Detected Categories

government
48%
adult content
42%
documentation technical
37%
news media journalism
33%
blog personal website
30%

Detected Features

No structural features detected

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
0142.250.186.163United States
AS15169GOOGLE
0108.138.2.142United States
AS16509AMAZON-02
0142.250.185.170United States
AS15169GOOGLE
0108.138.2.71United States
AS16509AMAZON-02
035.212.76.217Washington, District of Columbia, United States
AS15169GOOGLE
02600:9000:2490:f400:5:acf3:db40:21United States
AS16509AMAZON-02
02a00:1450:4001:82a::2003Frankfurt am Main, Hesse, Germany
AS15169GOOGLE
02600:9000:2490:8e00:5:acf3:db40:21United States
AS16509AMAZON-02
02600:9000:2490:c000:5:acf3:db40:21United States
AS16509AMAZON-02
02600:9000:2490:1600:5:acf3:db40:21United States
AS16509AMAZON-02
1017--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T17E73E1DD37600ED8CC9687D2673821493487B4EDE4504951F29E2BE4FF8B69D4AE068F

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:9IQS0tz0jiTbitkDfLMerF89xSuvcOKNGYUxYo3myMRdQmy:9r/itkDfLKKW

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:80656:UgABACUEVARyooAEaoMDTQOIAAmvRiAfMFKgCkqFaCmuIqOIAEwYREhgAYQCVizUoCIQxWgkUqAwAgBICOgK9tAFiNAEFpsG

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:0000000000ffffff
Perceptual Hash:dd029bdd22b27d22
Difference Hash:11310a4d32320022
Wavelet Hash:081808009affffff
Color Hash:#87abc5

Other Hashes

Crop Resistant:11310a4d32320022

Scan History

Scan history not available

Unable to load historical scan data