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Telephony has become a cost-effective medium for spammers to engage, and phone numbers are now being used to drive call traffic to spammer operated resources. The convergence of telephony and the Internet with technologies like Voice over IP (VoIP) is fueling the growth of Over-The-Top (OTT) messaging applications (like WhatsApp, Viber) that allow smartphone users to communicate with each other in myriad ways. These social channels (OSNs and OTT applications) and VoIP applications (like Skype, Google Hangouts) are used by millions of users around the globe. In fact, the volume of messages via OTT messaging applications has overtaken traditional SMS and e-mail. As a result, these social channels have become an attractive attack vector for spammers and malicious actors who are now abusing it for illicit activities like delivering spam and phishing messages. In this work, we aim to detect cybercriminals / spammers that use phone numbers to spread spam on OSNs. We divide this thesis into 4 parts – (1) Understanding the threat landscape of phone attacks on OTT messaging applications leveraging information from OSNs, (2) Uncovering the spam ecosystem on OSNs and identifying spammers which contribute is spreading spam, (3) Evaluating the trustworthiness of current caller ID services and machine learning model that identify spam calls / spammers, (4) Proposing a robust phone reputation score for identifying spam phone numbers on OSNs.