cloudmersive-phishingapi-client

CloudmersivePhishingapiClient - JavaScript client for cloudmersive-phishingapi-client Easily and directly scan and block phishing security threats in input. Cloudmersive Phishing Detection API provides advanced AI phishing detection capabilities.

• API version: v1
• Package version: 2.0.2

Installation

For Node.js

npm

To publish the library as a npm, please follow the procedure in "Publishing npm packages".

Then install it via:

npm install cloudmersive-phishingapi-client --save

Local development

To use the library locally without publishing to a remote npm registry, first install the dependencies by changing into the directory containing package.json (and this README). Let's call this JAVASCRIPT_CLIENT_DIR. Then run:

npm install

Next, link it globally in npm with the following, also from JAVASCRIPT_CLIENT_DIR:

npm link

Finally, switch to the directory you want to use your cloudmersive-phishingapi-client from, and run:

npm link /path/to/<JAVASCRIPT_CLIENT_DIR>

You should now be able to require('cloudmersive-phishingapi-client') in javascript files from the directory you ran the last command above from.

git

If the library is hosted at a git repository, e.g. https://github.com/GIT_USER_ID/GIT_REPO_ID then install it via:

    npm install GIT_USER_ID/GIT_REPO_ID --save

For browser

The library also works in the browser environment via npm and browserify. After following the above steps with Node.js and installing browserify with npm install -g browserify, perform the following (assuming main.js is your entry file, that's to say your javascript file where you actually use this library):

browserify main.js > bundle.js

Then include bundle.js in the HTML pages.

Webpack Configuration

Using Webpack you may encounter the following error: "Module not found: Error: Cannot resolve module", most certainly you should disable AMD loader. Add/merge the following section to your webpack config:

module: {
  rules: [
    {
      parser: {
        amd: false
      }
    }
  ]
}

Getting Started

Please follow the installation instruction and execute the following JS code:

var CloudmersivePhishingapiClient = require('cloudmersive-phishingapi-client');

var defaultClient = CloudmersivePhishingapiClient.ApiClient.instance;

// Configure API key authorization: Apikey
var Apikey = defaultClient.authentications['Apikey'];
Apikey.apiKey = "YOUR API KEY"
// Uncomment the following line to set a prefix for the API key, e.g. "Token" (defaults to null)
//Apikey.apiKeyPrefix['Apikey'] = "Token"

var api = new CloudmersivePhishingapiClient.PhishingDetectionApi()

var opts = { 
  'body': new CloudmersivePhishingapiClient.AdvancedEmailDetectionRequest() // {AdvancedEmailDetectionRequest} Phishing detection request
};

var callback = function(error, data, response) {
  if (error) {
    console.error(error);
  } else {
    console.log('API called successfully. Returned data: ' + data);
  }
};
api.phishingDetectEmailAdvancedPost(opts, callback);

Documentation for API Endpoints

All URIs are relative to https://localhost

Class | Method | HTTP request | Description ------------ | ------------- | ------------- | ------------- CloudmersivePhishingapiClient.PhishingDetectionApi | phishingDetectEmailAdvancedPost | POST /phishing/detect/email/advanced | Perform advanced AI phishing detection and classification against input email. Analyzes input email as well as embedded URLs with AI deep learning to detect phishing, phishing and other unsafe content. Uses 25-100 API calls depending on model selected. CloudmersivePhishingapiClient.PhishingDetectionApi | phishingDetectFileAdvancedPost | POST /phishing/detect/file/advanced | Perform advanced AI phishing detection and classification against input text string. Analyzes input content as well as embedded URLs with AI deep learning to detect phishing, phishing and other unsafe content. Uses 25-100 API calls depending on model selected. CloudmersivePhishingapiClient.PhishingDetectionApi | phishingDetectFilePost | POST /phishing/detect/file | Perform AI phishing detection and classification on an input image or document (PDF or DOCX). Analyzes input content as well as embedded URLs with AI deep learnign to detect phishing and other unsafe content. Uses 100-125 API calls depending on model selected. CloudmersivePhishingapiClient.PhishingDetectionApi | phishingDetectTextStringAdvancedPost | POST /phishing/detect/text-string/advanced | Perform advanced AI phishing detection and classification against input text string. Analyzes input content as well as embedded URLs with AI deep learnign to detect spam, phishing and other unsafe content. Uses 25-100 API calls depending on model selected. CloudmersivePhishingapiClient.PhishingDetectionApi | phishingDetectUrlAdvancedPost | POST /phishing/detect/url/advanced | Perform advanced AI phishing detection and classification against an input URL. Retrieves the URL content, checks for SSRF threats, and analyzes the page with AI deep learning to detect phishing and other unsafe content. Uses 100-125 API calls.

Documentation for Models

• CloudmersivePhishingapiClient.AdvancedEmailDetectionRequest
• CloudmersivePhishingapiClient.AdvancedUrlDetectionRequest
• CloudmersivePhishingapiClient.PhishingDetectionAdvancedRequest
• CloudmersivePhishingapiClient.PhishingDetectionAdvancedResponse
• CloudmersivePhishingapiClient.PhishingDetectionEmailAdvancedResponse
• CloudmersivePhishingapiClient.PhishingDetectionResponse
• CloudmersivePhishingapiClient.PhishingDetectionUrlAdvancedResponse

Documentation for Authorization

Apikey

• Type: API key
• API key parameter name: Apikey
• Location: HTTP header