mirror of
https://github.com/mail-in-a-box/mailinabox.git
synced 2024-11-24 02:37:05 +00:00
119 lines
4.4 KiB
Bash
Executable File
119 lines
4.4 KiB
Bash
Executable File
#!/bin/bash
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# Spam filtering with spamassassin via spampd
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# -------------------------------------------
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#
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# spampd sits between postfix and dovecot. It takes mail from postfix
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# over the LMTP protocol, runs spamassassin on it, and then passes the
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# message over LMTP to dovecot for local delivery.
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#
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# In order to move spam automatically into the Spam folder we use the dovecot sieve
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# plugin.
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source /etc/mailinabox.conf # get global vars
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source setup/functions.sh # load our functions
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# Install packages and basic configuration
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# ----------------------------------------
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# Install packages.
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apt_install spampd razor pyzor dovecot-antispam
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# Allow spamassassin to download new rules.
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tools/editconf.py /etc/default/spamassassin \
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CRON=1
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# Configure pyzor.
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hide_output pyzor discover
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# Pass messages on to docevot on port 10026.
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# This is actually the default setting but we don't want to lose track of it.
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# We've already configured Dovecot to listen on this port.
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tools/editconf.py /etc/default/spampd DESTPORT=10026
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# Spamassassin normally wraps spam as an attachment inside a fresh
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# email with a report about the message. This also protects the user
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# from accidentally openening a message with embedded malware.
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#
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# It's nice to see what rules caused the message to be marked as spam,
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# but it's also annoying to get to the original message when it is an
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# attachment, modern mail clients are safer now and don't load remote
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# content or execute scripts, and it is probably confusing to most users.
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#
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# Tell Spamassassin not to modify the original message except for adding
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# the X-Spam-Status mail header and related headers.
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tools/editconf.py /etc/spamassassin/local.cf -s \
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report_safe=0
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# Bayesean learning
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# -----------------
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#
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# Spamassassin can learn from mail marked as spam or ham, but it needs to be
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# configured. We'll store the learning data in our storage area.
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#
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# These files must be:
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#
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# * Writable by sa-learn-pipe script below, which run as the 'mail' user, for manual tagging of mail as spam/ham.
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# * Readable by the spampd process ('spampd' user) during mail filtering.
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# * Writable by the debian-spamd user, which runs /etc/cron.daily/spamassassin.
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#
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# We'll have these files owned by spampd and grant access to the other two processes.
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tools/editconf.py /etc/spamassassin/local.cf -s \
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bayes_path=$STORAGE_ROOT/mail/spamassassin/bayes
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mkdir -p $STORAGE_ROOT/mail/spamassassin
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chown -R spampd:spampd $STORAGE_ROOT/mail/spamassassin
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# To mark mail as spam or ham, just drag it in or out of the Spam folder. We'll
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# use the Dovecot antispam plugin to detect the message move operation and execute
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# a shell script that invokes learning.
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# Enable the Dovecot antispam plugin.
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# (Be careful if we use multiple plugins later.) #NODOC
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sed -i "s/#mail_plugins = .*/mail_plugins = \$mail_plugins antispam/" /etc/dovecot/conf.d/20-imap.conf
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# Configure the antispam plugin to call sa-learn-pipe.sh.
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cat > /etc/dovecot/conf.d/99-local-spampd.conf << EOF;
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plugin {
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antispam_backend = pipe
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antispam_spam_pattern_ignorecase = SPAM
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antispam_allow_append_to_spam = yes
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antispam_pipe_program_spam_args = /usr/local/bin/sa-learn-pipe.sh;--spam
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antispam_pipe_program_notspam_args = /usr/local/bin/sa-learn-pipe.sh;--ham
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antispam_pipe_program = /bin/bash
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}
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EOF
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# Have Dovecot run its mail process with a supplementary group (the spampd group)
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# so that it can access the learning files.
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tools/editconf.py /etc/dovecot/conf.d/10-mail.conf \
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mail_access_groups=spampd
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# Here's the script that the antispam plugin executes. It spools the message into
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# a temporary file and then runs sa-learn on it.
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# from http://wiki2.dovecot.org/Plugins/Antispam
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rm -f /usr/bin/sa-learn-pipe.sh # legacy location #NODOC
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cat > /usr/local/bin/sa-learn-pipe.sh << EOF;
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cat<&0 >> /tmp/sendmail-msg-\$\$.txt
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/usr/bin/sa-learn \$* /tmp/sendmail-msg-\$\$.txt > /dev/null
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rm -f /tmp/sendmail-msg-\$\$.txt
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exit 0
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EOF
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chmod a+x /usr/local/bin/sa-learn-pipe.sh
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# Create empty bayes training data (if it doesn't exist). Once the files exist,
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# ensure they are group-writable so that the Dovecot process has access.
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sudo -u spampd /usr/bin/sa-learn --sync 2>/dev/null
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chmod -R 660 $STORAGE_ROOT/mail/spamassassin
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chmod 770 $STORAGE_ROOT/mail/spamassassin
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# Initial training?
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# sa-learn --ham storage/mail/mailboxes/*/*/cur/
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# sa-learn --spam storage/mail/mailboxes/*/*/.Spam/cur/
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# Kick services.
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restart_service spampd
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restart_service dovecot
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