Video game cheats destroy the online play experience of users and result in financial losses for game developers. Similar to hacking communities, cheat developers often organize themselves around forums where they share game cheats and know-how. In this paper, we perform a large-scale measurement of two online forums, MPGH and UnknownCheats, devoted to video game cheating that are nowadays very active and altogether have more than 7 million posts. Video game cheats often require an auxiliary tool to access the victim process, i.e., an injector. This is a type of program that manipulates the game program memory, and it is a key piece for evading cheat detection on the client side. We leverage the output of our measurement study to build a machine learning classifier that identifies injectors based on their behavioural traits. Our system will help game developers and the anti-cheat industry to identify attack vectors more quickly and will reduce the barriers to study this topic within the academic community.