Ham:dir:~/Maildir/.Websites.internlnet/cur Ham:dir:~/Maildir/.Websites.omroephumor/cur \ Ham:dir:~/Maildir/.Reference.Software/cur \
Ham:dir:~/Maildir/.Personal.financial/cur \ Ham:dir:~/Maildir/.Organisation.Hostel/cur \ Ham:dir:~/Maildir/.Organisation.ABOU/cur \ Ham:dir:~/Maildir/.Hobbies.scatterlings/cur \ Ham:dir:~/Maildir/.Computers.zeroconf/cur \ Ham:dir:~/Maildir/.Computers.macports/cur \ Ham:dir:~/Maildir/.Computers.bugreports/cur \ Ham:dir:~/Maildir/.Computers.Debian/cur \ Ham:dir:~/Maildir/.Spam.falsepositives/cur \ Spam:dir:~/Maildir/.Spam.falsenegatives/cur \ mass-check -c=/usr/share/spamassassin -p=/home/freek/.spamassassin -progress -lint \ Note: -lint was only introduces in mass-check 3.1 and a ~ in the -p option is not recognized. Incorrect mails may skew the results significantly. Important: You must first verify that the mails in these folders is indeed spam or ham. In the masses subdirectory, you will find miscellaneous tools to test the efficiency of all rules.įirst of all, you should run mass-check, which takes your messages, and counts which rules are matched: Note that the tflags is not used in regular operation, but it must be set to "nice" for negative scoring rules, in case you want to verify the efficiency later on.ĭownload SpamAssassin. Header DEBIAN_LIST List-Id =~ //ĭescribe DEBIAN_LIST Debian Mailinglist ID It is important to verify the efficiency of these rules to avoid false positives.
#SPAMASSASSIN RULE MANUAL#
Since my mail profile is different, I added a few manual rules to SpamAssassin, mostly to cope with language specific characteristics, as well as mailing list specific characteristics. For one thing URL with rule specifications moved from to, while the first URL is still hard-coded in the rule-get script.Īn alternative location is to look at the SpamAssassin wiki: based on language or mailing list topic) rather then using these untested generic rules.Īlso, the rule-get project seems mostly dead. You may get some inspiration, but in general it is better to create some custom rules yourself based on your specific mail behaviour (e.g. For one thing, badly scored custom rules may result in a lot of false positives. I manage some custom rules with the "rule-get" script. The rules included with SpamAssassin should in most cases be enough to block all spam. A lot of people have written their custom rules for Bayes. For example, HTML has a higher change of being spam, so I mark it as such. In addition to the Bayes rules, SpamAssassin has many other rules. This is a big assumption, so I do not run it automatically, but have to remember to run it manualy every once in a while. The last line assumes that all mail in the default inbox is non-spam. Sa-learn -ham $HOME/Maildir/cur/ > $HOME/log/spam.log Sa-learn -ham $HOME/Maildir/.Spam.falsepositives/cur/ > $HOME/log/spam.log Sa-learn -spam $HOME/Maildir/.Spam.falsenegatives/cur/ > $HOME/log/spam.log Sa-learn -spam $HOME/Maildir/.Spam.negatives/cur/ > $HOME/log/spam.log PATH=/bin:/sbin:/usr/bin:/usr/sbin:/usr/local/bin:/home/freek/bin Spam/falsepositives I put here non-spam mails that were accidentilly marked as spam. Spam/falsenegatives I put here spam mail that slipped through. I run a cron job to extract the confirmed spam from the report and store it in here. Spam/negatives The confirmed mail is often stored as an attachment to another mail with the spamassassin report. Spam/confirmed After confirming something is spam, I put it in this box. I will have to check these manually (if it is sure, it simply deletes them). Spam/incoming SpamAssassin will store mail which it suspect is spam, but is not 100% sure. When a new mail arrives, it looks at the word usages, and based on that gives a propability score wether the mail is spam or not.
#SPAMASSASSIN RULE FULL#
It may learn that a spam mail often contains words like viagra, while ham mails contains your full name. You do so by giving it a large sample set (at least 100 mails), which it examins for word usage. The first step is to learn Spamassassin the difference between spam and non-spam ("ham") mails. SpamAssassin uses Bayesian filtering of email to stop spam. SpamAssassin is technique to block spam, based on multiple rules. 4.3 Verify falsepositives and false negatives.
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