mailinabox/setup/spamassassin.sh

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3.9 KiB
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#!/bin/bash
# Spam filtering with spamassassin via spampd
# -------------------------------------------
#
# spampd sits between postfix and dovecot. It takes mail from postfix
# over the LMTP protocol, runs spamassassin on it, and then passes the
# message over LMTP to dovecot for local delivery.
#
# In order to move spam automatically into the Spam folder we use the dovecot sieve
# plugin.
source /etc/mailinabox.conf # get global vars
source setup/functions.sh # load our functions
# Install packages and basic configuration
# ----------------------------------------
# Install packages.
apt_install spampd razor pyzor dovecot-antispam
# Allow spamassassin to download new rules.
tools/editconf.py /etc/default/spamassassin \
CRON=1
# Configure pyzor.
hide_output pyzor discover
# Pass messages on to docevot on port 10026.
# This is actually the default setting but we don't want to lose track of it.
# We've already configured Dovecot to listen on this port.
tools/editconf.py /etc/default/spampd DESTPORT=10026
# Bayesean learning
# -----------------
#
# Spamassassin can learn from mail marked as spam or ham, but it needs to be
# configured. We'll store the learning data in our storage area.
#
# These files must be:
#
# * Writable by sa-learn-pipe script below, which run as the 'mail' user, for manual tagging of mail as spam/ham.
# * Readable by the spampd process ('spampd' user) during mail filtering.
# * Writable by the debian-spamd user, which runs /etc/cron.daily/spamassassin.
#
# We'll have these files owned by spampd and grant access to the other two processes.
tools/editconf.py /etc/spamassassin/local.cf -s \
bayes_path=$STORAGE_ROOT/mail/spamassassin/bayes
mkdir -p $STORAGE_ROOT/mail/spamassassin
chown -R spampd:spampd $STORAGE_ROOT/mail/spamassassin
# To simplify the correction of false-positives, we do not want to encapsulate
# spam.
tools/editconf.py /etc/spamassassin/local.cf -s \
report_safe=0
# To mark mail as spam or ham, just drag it in or out of the Spam folder. We'll
# use the Dovecot antispam plugin to detect the message move operation and execute
# a shell script that invokes learning.
# Enable the Dovecot antispam plugin.
# (Be careful if we use multiple plugins later.) #NODOC
sed -i "s/#mail_plugins = .*/mail_plugins = \$mail_plugins antispam/" /etc/dovecot/conf.d/20-imap.conf
# Configure the antispam plugin to call sa-learn-pipe.sh.
cat > /etc/dovecot/conf.d/99-local-spampd.conf << EOF;
plugin {
antispam_backend = pipe
antispam_spam_pattern_ignorecase = SPAM
antispam_allow_append_to_spam = yes
antispam_pipe_program_spam_args = /usr/local/bin/sa-learn-pipe.sh;--spam
antispam_pipe_program_notspam_args = /usr/local/bin/sa-learn-pipe.sh;--ham
antispam_pipe_program = /bin/bash
}
EOF
# Have Dovecot run its mail process with a supplementary group (the spampd group)
# so that it can access the learning files.
tools/editconf.py /etc/dovecot/conf.d/10-mail.conf \
mail_access_groups=spampd
# Here's the script that the antispam plugin executes. It spools the message into
# a temporary file and then runs sa-learn on it.
# from http://wiki2.dovecot.org/Plugins/Antispam
rm -f /usr/bin/sa-learn-pipe.sh # legacy location #NODOC
cat > /usr/local/bin/sa-learn-pipe.sh << EOF;
cat<&0 >> /tmp/sendmail-msg-\$\$.txt
/usr/bin/sa-learn \$* /tmp/sendmail-msg-\$\$.txt > /dev/null
rm -f /tmp/sendmail-msg-\$\$.txt
exit 0
EOF
chmod a+x /usr/local/bin/sa-learn-pipe.sh
# Create empty bayes training data (if it doesn't exist). Once the files exist,
# ensure they are group-writable so that the Dovecot process has access.
sudo -u spampd /usr/bin/sa-learn --sync 2>/dev/null
chmod -R 660 $STORAGE_ROOT/mail/spamassassin
chmod 770 $STORAGE_ROOT/mail/spamassassin
# Initial training?
# sa-learn --ham storage/mail/mailboxes/*/*/cur/
# sa-learn --spam storage/mail/mailboxes/*/*/.Spam/cur/
# Kick services.
restart_service spampd
restart_service dovecot