Do you use MS Exchange public folders for bayes learning?

[Matt Yackley <sa...@yackley.org>]

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Hi all,

I would like to throw out a request for admins that are using, have tried or want to
use MS Exchage public folders to gather messages that will be fed back to sa-learn.

Background:
Since there are not many (any?) good ways to retrieve email messages out of an
Exchange/Outlook system in order to feed the messages back to a SA server to be run
through sa-learn, the best option for a large amount of users is to setup a public
folder and have users drop their messages in the PFs, then run an automated script
on the SA server to pull those messages in using a script like Nick Burch's
power-imap-sa-learn.pl [1].

However there seems to be an issue with MS Exchange public folders and IMAP.  When
an email message is placed in a public folder, then retrived via IMAP, Exchange
strips out some of the SMTP headers and inserts some custom MS headers.  This is
clearly a non-optimal method due the loss of some great spam/ham signs.  While the
messages are fairly close to their original forms, they could be much better.

Request:
I currently have a ticket open with MS Premier support due to a "bug" in MS's
implementation of IMAP & public folders.  At this point in time, MS support confirms
that they can replicate the behavior and have escalated the issue and have sent it
off to the Exchange development team for a RFC.  My best guess is that they will
confirm the issue, but say that there is not enough reason to develop a fix or a
patch for the issue.

I would like to gather a list of admins who would be like this issue to be resolved,
so that I can have a little more "push" with MS.  It may help if I can let them know
that I have discussed this with X number of admins, who have X numbers of servers
and users who would like to this this issue resolved.

If you use SpamAssassin as a filter for an Exchange system and would like to add
your voice, please contact me off-list.

Thanks for your time,

Matt Yackley

[1] http://tirian.magd.ox.ac.uk/~nick/code/

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