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Calculates how deceptive a domain name is. It is used to avoid phishing attacks.

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Deceptive Domain Score

coverage build

Features

Feature: Get the domain score
    As a domain analyst
    I want to know the deceptiveness score of a domain
    To decide whether or not it should be evaluated by a real person

Rules

  • The domain will be compared to a list of keywords
  • The input is a domain name
  • Natural language must be matched (vísa == visa)
  • The score is 100 if part of the domain that matches a keyword exactly and the keyword is a brand name
  • The score is 90 if part of the domain matches a keyword exactly and the keyword is a common word
  • The score is 80 if part of the domain is similar and the keyword is a brand name
  • The score is 70 if part of the domain is similar and the keyword is a common word
  • The score is 50 if the domain contains numbers
  • The score is 0 if the domain is not in any of the categories listed above

Scenario: testing a deceptive domain
    Given the domain "visa-card-help.com"
    When I run the script on it
    Then it should result in a score of 100

Scenario: testing a domain that contains a number
    Given the domain "nfl-mega-league2019.com"
    When I run the script on it
    Then it should result in a score of 50

Code

Business Logic

Entities

  • domain
  • keyword

Public

  • Domain
    • GetDeceptiveScore

Requirements

For the core business logic

  • Go 1.12.x
  • Remember to set export GO111MODULE=on;

For the AWS Serverless adapter

  • Serverless Framework >=1.28.0
  • An AWS account

Running tests

// In the root folder of the repository run
go test ./...

// To run tests showing the test coverage
go test ./... -cover

Building and deploying the AWS Serverless adapter

How to build

make build

How to deploy

make deploy or sls deploy

Deploying a single function

sls deploy -f clientget

TODO

  • Create an architecture diagram
  • Create a flow diagram for how the score is defined
  • Remove tld (cleanup)
  • Convert to lowercase (cleanup)
  • Convert from punycode (cleanup)
  • Different check for prefix/suffix (login, signin, verify...)
  • Artificial intelligence (Machine learning) detection
  • Create Go Benchmarks 💞
  • Create Go Examples
  • Run each algorithm in a separate Go Routine 😍 (based on Go Benchmarks, this is and slower option)

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Calculates how deceptive a domain name is. It is used to avoid phishing attacks.

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