In today’s world, endangered species are threatened by widespread poaching, requiring intelligent land patrol strategies to effectively detect and prevent such activities. Several recent works have developed game-theoretic models for anti-poaching where equilibrium strategies correspond to effective patrol strategies [6]. Due to the complexity of the models, simulators are usually developed and Multi-Agent Reinforcement Learning (MARL) methods are pro- posed to learn these strategies. Yet, even as anti-poaching emerges as a popular domain for MARL, the absence of both a general model and a publicly accessible implementation hinders both the evaluation and development of new solutions. In this work, we aim to provide such a model of Anti-Poaching with a publicly available implementation.