The spam-identification tactics used include:
- header analysis: spammers use a number of tricks to mask their identities, fool you into thinking they’ve sent a valid mail, or fool you into thinking you must have subscribed at some stage. SpamAssassin tries to spot these.
- text analysis: again, spam mails often have a characteristic style (to put it politely), and some characteristic disclaimers and CYA text. SpamAssassin can spot these, too.
- blacklists: SpamAssassin supports many useful existing blacklists.
- learning classifier: we use forms of probability-analysis classification, so that a user can train it to recognise mails similar to a training set.
- distributed hash databases: spam typically operates by sending an identical message to hundreds of people, these databases short-circuit this by allowing the first person to receive a spam to add it to the database — at which point everyone else will automatically block it.
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