The posibilities that the management of a vast amount of computers and/or networks offer, is attracting an increasing number of malware writers. In this document, the authors propose a methodology thought to detect malicious botnet traffic, based on the analysis of the packets flow that circulate in the network. This objective is achieved by means of the parametrization of the static characteristics of packets, which are lately analysed using supervised machine learning techniques focused on traffic labelling so as to face proactively to the huge volume of information nowadays filters work with.