Why Machine Learning might just help us out Description: There are patterns in code and you've all seen it: Done wrong once, done wrong again. We ask the question how pattern recognition systems as studied in machine learning can be applied to assist in the discovery of these patterns and to extrapolate when a specific vulnerability in a code base has been identified. While malware and intrusion detection has been ML-powered for quite a while now, there may still be a lot to explore as machine learning is weaponized for offense. In this presentation, we give a practical introduction to some of the algorithms developed in machine learning, illustrate how they are used in other fields and attempt to give impulses for applications in bug hunting. We present a source code browsing tool developed during this research and demonstrate how it can be used to identify 0-day vulns.