In this talk, we'll go over part of the landscape of adversarial machine learning from both perspectives. First we'll explore how testers can attack different types of models, and what an organisation stands to lose. After that we'll dive into both operational and technical mitigations a data scientist or architect can undertake to avoid falling prey to these attacks.