Basically online social networks, such as Orkut, Facebook, are increasingly utilized by many people. These networks allow users to publish details about themselves and to connect to their friends. Some of the information people want to be private. Yet it is possible to use learning algorithms on released data to predict private information. Here, the authors explore how to launch inference attacks using released social networking data to predict private information. They then devise sanitization techniques that could be used in various situations.