Spam Assassin

SpamAssassin is a mature, widely-deployed open source project that serves as a mail filter to identify Spam. SpamAssassin uses a variety of mechanisms including header and text analysis, Bayesian filtering, DNS blocklists, and collaborative filtering databases. New Spam Assassin rules are published daily to catch new spam patterns.

SpamAssassin is an intelligent email filter which uses a diverse range of tests to identify unsolicited bulk email, more commonly known as Spam. These tests are applied to email headers and content to classify email using advanced statistical methods. In addition, SpamAssassin has a modular architecture that allows other technologies to be quickly wielded against spam and is designed for easy integration into virtually any email system. In SpamAssassin 3.x, the scores are assigned using a neural network trained with error back propagation (Perceptron). Both systems attempt to optimise the efficiency of the rules that are run in terms of minimizing the number of false positives and false negatives.