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Bayesian poisoning is a technique used by e-mail spammers to attempt to degrade the effectiveness of spam filters that rely on Bayesian spam filtering. Bayesian filtering relies on Bayesian probability to determine whether an incoming mail is spam or is not spam. The spammer hopes that the addition of random words that are unlikely to appear in a spam message will cause the spam filter to believe the message to be legitimate—a statistical type II error.
Spammers also hope to cause the spam filter to have a higher false positive rate by turning previously innocent words into spammy words in the Bayesian database because a user who trains their spam filter on a poisoned message will be indicating to the filter that the words added by the spammer are a good indication of spam.