On Mon, 2004-11-08 at 09:09, windtim@xxxxxxxx wrote: > Hi > i've Fedora Core 2 and i use evolution 1.4. I want to set it to work with > spamassassin and clamav ( to delete virus and spam from my mailbox). How can i do? > Help in advance for the help There are two basic ways to setup spamassassin. If you have control of the MTA where the email is arriving it is best to configure spamassassin as a filter used by the MTA process. I have done this for sendmail using procmail. There are also milters that let you configure spamassassin as part of your MTA. This is dependent on the particular MTA you are using. Mimedefang is also a good way to implement this. There are a lot of good how to's on the web on how to configure your particular MTA to work with spamassassin so I won't go into that here. If you are using evolution only and pulling your email via pop3 or imap then you can configure a filter in evolution that calls spamassassin on each message as it arrives. I have also done this before and it works very well. To setup a filter in evolution do the following: Install spamassassin on your system in evolution configure a filter that has under execute actions if all criteria are met pipe message to a shell command specify the command as /usr/bin/spamassassin -e -P specify the last option as returns greater than 0 Under the then section of the filter I have the following: set status read move to folder "possible junk mail" in "local folders" stop processing This will cause all messages identified as spam to be marked as read, moved to a holding folder, and the filter will stop processing. If you don't put the stop processing option in the next filter in the list will do its thing to the message. You also need to configure spamassassin. You need to create under your users account a .spamassassin directory. (this may get created automatically if you run spamassassin manually once. I don't remember if it did that or not.) In that directory you will want to create a user_prefs file. You should be able to find examples in the package or on the web. I have included important bits from mine below. The other files in the .spamassassin directory that should get created automatically I think are: bayes_journal, bayes_seen, and bayes_toks. These files are what is used by the baysian filter system. That is what keeps track of what you declare to be spam or not spam. Spamassassin also uses additional rule sets in addition to bayes to identify spam. Also note: bayes will not start working until you have processed 200 spam and 200 ham messages using sa-learn. sa-learn is the program that is used to manually teach the bayes database what you consider ham and spam. Read up on the man page for how to use it. (I think the first time you run sa-learn it will read your user_prefs file and create the bayes files listed above.) You can also pull additional rule sets for the SARE web site. http://www.rulesemporium.com/ By selectively adding some of the SARE rulesets you can greatly increase the hit rate and accuracy of spamassassin. The latest version of spamassassin implements SURBLs which according to reports work very well. You may or may not want/need to implement SURBLs. Also you may want to disable network checks as these can take a lot of time to complete. Another tip, is if you are receiving a lot of mail list traffic such as fedora mailing list, you should put a filter in ahead of the spamassassin check that moves those mailing list messages to their own folders and stops processing. I have found that very little spam hits mailing lists. If you don't do this your system will take a long time to download email since it will kick off a spamassassin process for each message. Save spamassassin for non-mailing list messages. Once you have it in place you should create another folder for missed spam. Any messages that end up in your inbox that you identify as spam move them to this missed spam folder. Then periodically run sa-learn on that folder to teach bayes what spam is. You may also want to setup a folder for false positives (ham wrongly identified as spam). Go through the spam folder and move any false positives to the false positive folder then run sa-learn on that folder telling it that it is ham. You will want to run sa-learn on your regular inbox identifying all messages as ham as well. After doing this for a few days or couple of weeks (depends on the volume of email you get) things should hit a point where virtually all spam is identified and you have no false positives. Once you hit that point you can reduce the frequency you run sa-learn on those folders and your inbox. Also in the user_prefs file you can whitelist certain addresses. You may want to do this for friends and business contacts or you can do this as needed as a quick way to resolve any false positives you may get. # How many hits before a mail is considered spam. required_hits 5.0 # Whether to change the subject of suspected spam rewrite_subject 0 # Text to prepend to subject if rewrite_subject is used subject_tag *****SPAM***** # Encapsulate spam in an attachment report_safe 1 # Use terse version of the spam report use_terse_report 0 # Enable the Bayes system bayes_path /home/scot/.spamassassin/bayes auto_whitelist_path /home/scot/.spamassassin/auto-whitelist bayes_file_mode 777 auto_whitelist_file_mode 777 use_bayes 1 bayes_ignore_header ReSent-Date bayes_ignore_header ReSent-From bayes_ignore_header ReSent-Message-ID bayes_ignore_header ReSent-Subject bayes_ignore_header ReSent-To bayes_ignore_header Resent-Date bayes_ignore_header Resent-From bayes_ignore_header Resent-Message-ID bayes_ignore_header Resent-Subject bayes_ignore_header Resent-To # Enable Bayes auto-learning auto_learn 1 Good luck and happy spam hunting! -- Scot L. Harris webid@xxxxxxxxxx This is a test of the emergency broadcast system. Had there been an actual emergency, then you would no longer be here.
