abuseipdb-wrapper 0.2.0

Info

• python wrapper for abuseipdb API (https://docs.abuseipdb.com/#introduction)

• gives you informations about abuse level of specified IP addresses

• focuses on caching results in local db

Install

stable version from pypi

pip install abuseipdb-wrapper

or newest version from github

pip install git+https://github.com/streanger/abuseipdb-wrapper.git

Command-line usage

abuse

or as module

python -m abuseipdb_wrapper

Python usage

• init `AbuseIPDB` object

  Init AbuseIPDB object using API KEY created on https://www.abuseipdb.com/. Optionally you can provide db_file for your local database. It is recommended because this project focuses on storing data for further quick access without need of another requests.

  from abuseipdb_wrapper import AbuseIPDB
  API_KEY = 'YOUR_API_KEY'
  abuse = AbuseIPDB(api_key=API_KEY, db_file='abuseipdb.json')
  abuse.colors_legend()

• check list of IPs

  Specify list of IPs to be checked using add_ip_list method. Then call check method and wait for results.

  ips = ['1.2.3.4', '5.6.7.8', '9.10.11.12', '13.14.15.16']
  abuse.add_ip_list(ips)
  abuse.check()

• no db caching approach

  If you are not interested in caching data in local database and only want to request for IP addresses one by one use the following code. Have in mind that .check_ip method enriches results and removes reports section. If using wrapper is like overkill in your project, go to: https://docs.abuseipdb.com/?python#check-endpoint

  from abuseipdb_wrapper import AbuseIPDB
  API_KEY = 'YOUR_API_KEY'
  abuse = AbuseIPDB(api_key=API_KEY)
  ips = ['1.2.3.4', '2.3.4.5', '3.4.5.6']
  for IP in ips:
      result = abuse.check_ip()  # enriched with url and request time
      result = abuse.check_ip_orig()  # results in original form
      print(result)

• show local db

  To display collected informations use show method. Alternatively call print on your AbuseIPDB object. You can specify columns to be displayed using apply_columns_order method. It affects both vertical and table view.

  columns = ['ipAddress', 'abuseConfidenceScore', 'totalReports', 'countryCode', 'domain', 'isp']
  abuse.apply_columns_order(columns)
  # show db by print or using .show method
  print(abuse)
  abuse.show(matched_only=False, table_view=True)

• viewer

  For interactive IP check use .viewer method. It let you to provide multiple IPs at once. Use help for more information.

  abuse.viewer()
  ~< abuse >~: columns [columns list]         # shows or apply columns order
  ~< abuse >~: export [csv, html, xlsx, md]   # export to file
  ~< abuse >~: all                            # check/show all database

• exports

  abuse.export_csv('out.csv', matched_only=False)
  abuse.export_html_styled('out.html', matched_only=False)
  abuse.export_xlsx_styled('out.xlsx', matched_only=False)
  abuse.export_md('out.md', matched_only=False)

• convert to dataframe object

  import pandas as pd
  matched = abuse.get_db(matched_only=False)
  df = pd.DataFrame(matched.values())

• json columns

  • abuseConfidenceScore

  • countryCode

  • date # additional

  • domain

  • hostnames

  • ipAddress

  • ipVersion

  • isPublic

  • isWhitelisted

  • isp

  • lastReportedAt

  • numDistinctUsers

  • totalReports

  • url # additional

  • usageType

  • isTor

Screenshots

• banner

• colors legend

• help

• vertical view

• table view

Changelog

• v.0.2.0:

  • removed pandas and Jinja2 dependencies

  • custom export functions

  • date as isoformat with timezone

• v.0.1.9:

  • additional isTorNode field replaced with isTor supported by api

• v.0.1.8:

  • more flexible exports

  • passing api_key to AbuseIPDB is now optional

  • keep order for passing IPs

  • viewer:

    • skip private IPs flag

    • sumup flag

    • force new check flag

    • more verbose logs

    • asterisks for api key using pwinput

  • colors support for: windows-cmd, windows-terminal, windows-powershell, vscode, linux-terminal

  • tests coverage for most features

  • export to markdown

  • and few smaller changes

• v.0.1.7:

  • abuse entrypoint

  • columns command in interactive view

  • export command in interactive view (to .csv, .html, .xlsx)

  • tor exit nodes enrichment

  • storing db file in user home directory

  • original API request using .check_ip_orig

  • getpass and keyring for API_KEY read & store

• v.0.1.6 and before:

  • black background for better view in powershell

  • export to csv, html, xlsx (from pandas df)

  • wrap text in table cells - made using rich table

  • return dataframe object

  • enrich results with date of last check