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phishingapi

Project description

cloudmersive_phishing_api_client

Easily and directly scan and block phishing security threats in input.

This Python package provides a native API client for Cloudmersive Phishing Detection API

  • API version: v1
  • Package version: 3.0.0
  • Build package: io.swagger.codegen.languages.PythonClientCodegen

Requirements.

Python 2.7 and 3.4+

Installation & Usage

pip install

If the python package is hosted on Github, you can install directly from Github

pip install git+https://github.com/GIT_USER_ID/GIT_REPO_ID.git

(you may need to run pip with root permission: sudo pip install git+https://github.com/GIT_USER_ID/GIT_REPO_ID.git)

Then import the package:

import cloudmersive_phishing_api_client 

Setuptools

Install via Setuptools.

python setup.py install --user

(or sudo python setup.py install to install the package for all users)

Then import the package:

import cloudmersive_phishing_api_client

Getting Started

Please follow the installation procedure and then run the following:

from __future__ import print_function
import time
import cloudmersive_phishing_api_client
from cloudmersive_phishing_api_client.rest import ApiException
from pprint import pprint

# Configure API key authorization: Apikey
configuration = cloudmersive_phishing_api_client.Configuration()
configuration.api_key['Apikey'] = 'YOUR_API_KEY'
# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['Apikey'] = 'Bearer'

# create an instance of the API class
api_instance = cloudmersive_phishing_api_client.PhishingDetectionApi(cloudmersive_phishing_api_client.ApiClient(configuration))
body = cloudmersive_phishing_api_client.AdvancedEmailDetectionRequest() # AdvancedEmailDetectionRequest | Phishing detection request (optional)

try:
    # 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.
    api_response = api_instance.phishing_detect_email_advanced_post(body=body)
    pprint(api_response)
except ApiException as e:
    print("Exception when calling PhishingDetectionApi->phishing_detect_email_advanced_post: %s\n" % e)

Documentation for API Endpoints

All URIs are relative to https://localhost

Class Method HTTP request Description
PhishingDetectionApi phishing_detect_email_advanced_post 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.
PhishingDetectionApi phishing_detect_file_advanced_post 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.
PhishingDetectionApi phishing_detect_file_post 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.
PhishingDetectionApi phishing_detect_text_string_advanced_post 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.

Documentation For Models

Documentation For Authorization

Apikey

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

Author

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