License: GPL
I have been fairly comfortable with my current mail filtering
solution. Unlike some other blogs on Planet, when last I was doing
exhaustive checks, I had not had a false positive in six months
(now I just do random spot checks). The false negatives creep up
from a few a week to a few a day (with a mail feed of about 1k
emails a day). And the stuff that is classified as a definite spam
is REJECTed (I do keep a copy), which means that a
legitimate correspondent would have an idea something went wrong
(unless they are ignoring such bounces form their own
MAILER-DAEMON).
Part of the reason for this satisfactory performance is that I
use a layered approach, with several tools playing off each other,
ameliorating each others mistakes. Admittedly, this took painful
training — I created a testcrm user, and bounced a
copy of every mail I got to it using a .forward. Then,
over a course of two months, I would painstakingly go over the
classification, training on error, until the failure rates dropped
to levels I felt comfortable with, and moved the CRM114 and
Spamassassin configuration over for my own use.
I recently added a hand crafted Greylisting implementation to MIMEDefang — in good MIMEDefang tradition, this is a heavily tweaked version of an implementation on the mailing list, using PostgreSQL. I have modified it to not greylist every single new email that comes my way, but to only greylist stuff that CRM114 and Spamassassin have been unable to classify strongly as Spam or ham. mail that has been strongly classified already, in turn, affects greylisting.
Here is the SQL code for the implementation, and the mimedefang-filter itself, showing how I integrate CRM114 and Spamassassin along with greylisting in a Sendmail Milter.
Have fun.