Security Scan Report: www.kbc.co.ke

Redirected to:
https://www.kbc.co.ke/chris-brown-must-pay-housekeeper-13m-dollars-jur...
Submitted: Oct 2, 2026, 2:35:57 AMCompleted: Oct 2, 2026, 2:37:31 AMpubliccompleted

This website contacted 47 IPs in 4 countries across 28 domains to perform 211 HTTP transactions. The main domain is kbc.co.ke and was registered 22 years ago.

Submitted URL: https://www.kbc.co.ke/chris-brown-must-pay-housekeeper-13m-dollars-jury-rules/

Effective URL:

https://www.kbc.co.ke/chris-brown-must-pay-housekeeper-13m-dollars-jur...
Redirected

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

Official KBC news article on a long-established domain. No phishing, malware, or credential-harvesting signals; standard WordPress login form is benign.

Safety Factors (5)
Established official broadcaster domain (registered 2003)
Self-branded as KBC Digital on its own domain
Article content about a third-party entertainment story, not brand impersonation
No threat-intelligence, YARA, IDS, or Safe Browsing hits
Standard WordPress admin login only; no credential or payment collection targeting users
Domain age information unavailable

Details

Page Title

Chris Brown must pay housekeeper 13M dollars, jury rules | KBC Digital

Scan Type

public

Domain Name Analysis

Within the Kenyan country-code top-level domain (.co.ke), 'www.kbc.co.ke' is registered, featuring subdomain 'www'. The second-level label 'kbc' is 3 characters long split between zero vowels and three consonants. Segmentation suggests 1 word: kbc. The median word length lands at three characters. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://www.kbc.co.ke/chris-brown-must-pay-housekeeper-13m-dollars-jury-rules/

Page Load Overview

25.71s
Total Load Time
3.6 MB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

HTML Lang Attribute:en-US
Text Length:5,455 chars
Detector Agreement:100%

Website Classification

Primary Category

news/blog50% confidence
Type: spa
Method: ml+structural

All Detected Categories

news/blog
50%
corporate
35%
entertainment media
33%
adult content
29%
government public service
26%

Detected Features

Articles
OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
2768.183.13.249Amsterdam, North Holland, Netherlands
AS14061DigitalOcean, LLC
4142.251.14.95Google · CDNUnited States
AS15169Google LLC
4142.251.20.97Google · CDNUnited States
AS15169Google LLC
4192.178.183.155Google · CDNUnited States
AS15169Google LLC
4142.251.20.113Google · CDNUnited States
AS15169Google LLC
462.115.253.137France
AS1299Arelion Sweden AB
4192.0.73.2San Francisco, California, United States
AS2635Automattic, Inc
4157.240.0.6Facebook · CDNFrankfurt am Main, Hesse, Germany
AS32934Facebook, Inc.
4188.114.97.9Cloudflare · WAFUnited States
AS13335Cloudflare, Inc.
4142.251.20.94Google · CDNUnited States
AS15169Google LLC
21147--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T15AF4E932F840182FA77B45C4E649D70A72D6A31FF4D54460E5EA036887E5EB8B42F3A7

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

3072:Sd0HG/WCVFdhXER95C7j5VjmBu8O6RygzpevJBgePmS8ueZOdqmQsFBiaFdnp:StdhXERr8j5Vjm+FQoD

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:723102:EFmOohysGQAFiQjIYIIAygElAS8yc1JQIxgFIQgFQAByJHGECUISUAEGhohpYEjFUQgQEWEMACS6XEUAeBNJkzcR0MEkoZAD

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:0018383818180000
Perceptual Hash:884d373e1d4f191d
Difference Hash:6d31b3b33333290d
Wavelet Hash:00193939b9b99987
Color Hash:#e06cd6

Scan History

Scan history not available

Unable to load historical scan data