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Security Scan Report: www.cobrief.app

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Submitted: Completed: publiccompleted

Summary

API
This view is built from:
Scan result: counts, verdicts, details, IPs, technologies, hashes/api/v1/result/5263d1e8-8cb1-4c2c-bcbe-e5a0cea3cbd8Domain and IP registration (RDAP)/api/v1/rdap/5263d1e8-8cb1-4c2c-bcbe-e5a0cea3cbd8How often this domain was scanned/api/v1/domain/stats/cobrief.appScan history for this domain/api/v1/domain/history/cobrief.app?limit=15
This website contacted 29 IPs in 2 countries across 9 domains to perform 35 HTTP transactions. The main domain is cobrief.app and was registered 2 years 4 months ago.

Submitted URL: https://www.cobrief.app/resources/legal-glossary/nepotism-overview-definition-and-example/

AI Security Verdict

AI analysis unavailable for this scan

Details

Page Title

Nepotism: Overview, definition, and example

Scan Type

public

Domain Name Analysis

The domain name 'www.cobrief.app' uses the application-focused generic top-level domain (.app) and includes subdomain 'www'. The registrable portion 'cobrief' spans 7 characters containing three vowels alongside 4 consonants. Breaking it apart gives 2 words: co, brief. Average segment length settles at 3.5 characters. 'co' most often appears in Czech. You may catch it in Polish and Afrikaans as well. Overall, 'www.cobrief.app' reads as Czech.

Screenshot

cobrief How it works Pricing Resourcesv Blog About us e Return to Legal glossary Start anew document with this content. Open the editor to build from scratch — paste in what you need and keep w...

Page Load Overview

0.69s
Total Load Time
813 KB
Total Size

Language Analysis

Primary Language

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

Detection Details

HTML Lang Attribute:en
Text Length:6,193 chars
Detector Agreement:100%

Website Classification

Primary Category

news/blog45% confidence
Type: dynamic
Method: ml+structural

All Detected Categories

news/blog
45%
corporate
35%
adult content
25%

Detected Features

Articles
OG: article
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
12188.114.97.3United States
AS13335CLOUDFLARENET
11104.21.81.33United States
AS13335CLOUDFLARENET
3146.75.123.7Frankfurt am Main, Hesse, Germany
AS54113FASTLY
2216.239.32.36United States
AS15169GOOGLE
2104.16.175.226United States
AS13335CLOUDFLARENET
1151.101.2.137San Francisco, California, United States
AS54113FASTLY
1142.250.185.232United States
AS15169GOOGLE
1172.67.137.209United States
AS13335CLOUDFLARENET
1188.114.96.3United States
AS13335CLOUDFLARENET
1104.16.174.226United States
AS13335CLOUDFLARENET
3529--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1A65319A765F611354323A169BBDB7709BA33D00BAA44CE40BAEC474C5FD2E9184733DA

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

768:Z1q+BjoqxCtGO9Ei+G+yCO0hQ18m7yPQ+3ZA+DWn1bPxJyvwAuFlH0VssjQH:j3aoOkM8m7yj3ZA+qn1VJHAurH0Vss0H

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:62913:kUA0kSJDjdBaUoFhoJjRWiYTsaBlSMZkDMLpQAQMFR5goQnAEaCYaTIHcqiRJUAI0oBRhOEjyQKBaCJUpgqIt6UKEkExMqcU

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:fec38f8387e3e3e3
Perceptual Hash:bd5cc3c75e1cd110
Difference Hash:a0163e272e1b0f0f
Wavelet Hash:1ec38f8383c3e3c3
Color Hash:N/A

Other Hashes

Crop Resistant:a0163e272e1b0f0f

Scan History

Scan history not available

Unable to load historical scan data