Lateral movement is a critical phase within advanced persistent threat (APT) campaigns, enabling attackers to escalate privileges and expand access while remaining undetected. Detecting such activities early is essential, but many detection techniques only provide after-the-event analyses. One technique that does allow for proactive monitoring is the Targeted Hunting integrating Threat Intelligence (TaHiTI) methodology, which offers a structured combination of threat hunting and hypothesis-driven detection, making it an interesting option for detecting lateral movement attacks in real-time. Unfortunately, TaHiTI requires a qualitative evaluation of large amounts of collected data, and its effectiveness is therefore often dependent on the skills of the security analyst employing the methodology. This may make it an unpopular option despite its promise. In this paper, an approach that could be employed to assist in training TaHiTI analysts, and therefore increase the number of analysts that can perform these qualitative analyses, is introduced. The proposed approach features a simulated environment, which is also evaluated to confirm that it is appropriate for simulating lateral movement attacks. Five attacks, based on the Mitre ATT&CK framework, are simulated using the environment while various levels of monitoring are applied. The results match the expected outcomes had it been a real-world network, suggesting that the simulated environment is an appropriate substitute to use when training cybersecurity analysts in the use of the TaHiTI methodology.