Malicious activities on the Web are increasingly threatening users in the Internet. Home networks are one of the prime targets of the attackers to host malwares, commonly exploited as a stepping stone to further launch a variety of attacks. Due to diversification, existing security solutions often fail to detect malicious activities which remain hidden and pose threats to users security and privacy. Characterizing behavioral patterns of known malwares can help to improve the classification accuracy of known threats. More important, since different malwares can share some commonalities, study the behavior of known malwares can enable the detection of previously unknown malicious activities. We pose the research question if it is possible to characterize such behavioral patterns analyzing the traffic from known infected clients. In this paper, we present our quest to discover such characterizations. Results show that commonalities arise but their identification may require some ingenuity. Also, more malicious activities can be found out from this analysis.