spammy

Spam filter

Spam filtering software using machine learning and Python.

Spam filtering made easy for you

GitHub

140 stars
9 watching
30 forks
Language: Python
last commit: about 5 years ago
Linked from 1 awesome list

emailmachine-learningpythonspam-filtering

Backlinks from these awesome lists:

Related projects:

Repository Description Stars
ma-shamshiri/spam-detector A program designed to classify emails as spam or not using machine learning algorithms. 33
spamscope/spamscope An advanced spam analysis tool that processes email streams in real-time using Apache Storm and various machine learning models. 292
db0/threativore A bot designed to detect and filter out spam from online discussions 12
rspamd/rspamd An email processing framework with advanced spam filtering capabilities 2,071
codefriar/rubyspamassassin A Ruby-based service that helps filter out spam from incoming emails using the SpamAssassin system. 29
shiva-spampot/shiva A system designed to detect and analyze spam emails by capturing and parsing them in real-time 133
joshfrench/rakismet A Rails gem that integrates Akismet's spam filtering service into Rails applications. 355
moqada/django-simple-spam-blocker A Django application that uses regular expressions to block spam on specific paths in a web application 23
gocom/rah_comment_spam Provides customizable anti-spam tools for Textpattern CMS' comment system. 2
markets/invisible_captcha A flexible spam protection solution for web applications 1,164
mosparo/mosparo Protects online forms from spam by analyzing user input data 191
gkswamy98/imessage-spam-detection An iMessage app that detects whether a message is spam by analyzing text patterns using a trained machine learning model. 36
omergunal/pot Automated phishing attack simulation tool 251
karser/karserrecaptcha3bundle A Symfony bundle for integrating Google reCAPTCHA v3 as an anti-spam measure in web applications 162
yingtongdou/nash-detect An algorithm for detecting spam reviews using reinforcement learning to train robust detectors against strategically synthesized attacks. 118