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From "Saahil Sirowa (JIRA)" <j...@apache.org>
Subject [jira] [Comment Edited] (COMDEV-267) GSOC 2018 SpamAssassin Improve Headers for RBL research
Date Sun, 11 Mar 2018 23:34:00 GMT

    [ https://issues.apache.org/jira/browse/COMDEV-267?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16394699#comment-16394699
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Saahil Sirowa edited comment on COMDEV-267 at 3/11/18 11:33 PM:
----------------------------------------------------------------

Hello, I m Computer Science and Engineering student at IITH. I would like to work on this
project for GSoC. Can you help me get started?


was (Author: ssirowa):
Hello, I would like to work on this project for GSoC. Can you help me get started?

> GSOC 2018 SpamAssassin Improve Headers for RBL research
> -------------------------------------------------------
>
>                 Key: COMDEV-267
>                 URL: https://issues.apache.org/jira/browse/COMDEV-267
>             Project: Community Development
>          Issue Type: Project
>          Components: GSoC/Mentoring ideas
>            Reporter: Kevin A. McGrail
>            Priority: Major
>              Labels: gsoc2018
>
> add subtests to headers for SA for logging / research purposes
> parse out URIs from $report _URIDOMAINS(,)_ list
> add_header all Status _YESNO_, score=_SCORE_ required=_REQD_ tests=_TESTS_ subtests=_SUBTESTS_
autolearn=_AUTOLEARN_ version=_VERSION_
> logic such as a tflag describe an RBL and then have rbls=_RBLS_.  So every rbl test
for PCCC will have a tflag that gives it a name like PCCC even if I have 20 tests.  Same
for URIBL or SURBL or SpamHause.  So the rbls=PCCC,SURBL,URIBL as an overarching hit about
which RBL hit.
> With this we can better identify overlap of RBLs.
> Also, it appears that URIDOMAINS(,)_ is not being interpolated in report body. 
>  
> Apache SpamAssassin is a mail filter to identify spam. It is an intelligent email filter
which uses a diverse range of tests to identify unsolicited bulk email, more commonly known
as Spam. These tests are applied to email headers and content to classify email using advanced
statistical methods. 
> In addition, SpamAssassin has a modular architecture that allows other technologies to
be quickly wielded against spam and is designed for easy integration into virtually any email
system. 
> It is primarily written in Perl with a few bits in C and shell scripts for system integration.
> The compendium at https://raptor.pccc.com/raptor.cgim?template=email_spam_compendium
is helpful to understand some of the concepts with SpamAssassin
> It will be helpful for a student in this project to understand SMTP but a willingness
to learn and setup your own mail server on a Linux Distribution with SpamAssassin for a personal
test domain will be very desired with assistance provided to get the basic framework for a
sandbox for learning.
> As email becomes more commodotized by major providers, knowledge of email systems and
their security is dwindling.  This opportunity can provide real-world experience with an
email security product that is employed by countless commercial systems in the world.



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