Penetration Testing for Spam Filters

Despite all the advances on techniques to block spam e-mail messages we still receive them on a frequent basis. This is due mainly to the ability of the spammers to modify the message and pass the filters. Therefore a testing technique that could resemble the behavior of spammers would improve the number of scenarios tested and allow filters to be developed based on the potential changes made by the spammers. An approach based on Natural Language Processing (NLP) for the penetration of spam filters is proposed here. Preliminary results using SpamAssassin are provided indicating the feasibility of the proposed approach.