THIS IS A TEST INSTANCE. ALL YOUR CHANGES WILL BE LOST!!!!
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#Uncomment the following lines and use tail -f procmail.log to debug
#LOGFILE=$HOME/procmail.log
#VERBOSE=yes
#LOGABSTRACT=all
# Feed redirected spam to sa-learn, and also store a copy in a folder called spam.
# This folder of false negatives could be useful if we needed to rebuild our Bayes
# database in the future.
:0
* ^To:.*spam@example.com
* < 256000
{
:0c: spamassassin.spamlock
| sa-learn --spam
:0: spamassassin.filelock
spam
}
# Send all other mail through SpamAssassin
:0fw: spamassassin.lock
* < 256000
| spamassassin
# Mail that is very likely spam (>15) can be saved on the server
# (not forwarded), or by moving the # down one line, even dropped
# on the floor. Note that dropping mail on the floor is a *bad*
# idea unless you really, really believe no false positives will
# have a score greater than 15. If you want all mail forwarded,
# just add #'s in front of each of these lines:
:0: spamassassin.filelock2
* ^X-Spam-Level: \*\*\*\*\*\*\*\*\*\*\*\*\*\*\*
#/dev/null
almost-certainly-spam
# Forward all mail with a score less than 15 to my non-publicized address
:0
! privateaddress@example.net
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Way more detail on how to do this is at SingleUserUnixInstall.
Other training options
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An even easier form of mistake-based training is to use IMAP and create a Learn{{`As}}`Spam folder, as described in the \[wiki:Self:SingleUserUnixInstall#head-bea6b8dc4f219edd3b9976e8f922a8f1c0603125 IMAP section of SingleUserUnixInstall\]. |
Contributors
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