The everyday life of a prison is not only shaped by the objective of resocialisation but also, as a rule, by aspects of security, which have the highest priority. A particular challenge is the prompt detection of potentially dangerous behavior. In the face of scarce human resources and psychologically limited attention, the use of video live streams is not an optimal solution. An alternative are 3D sensors, which enable the automatic and robust detection of such behavior in detention rooms and other areas such as hospital wards or workshops, while respecting the privacy of the monitored people. In this paper we present our research on this matter, based on realistic data that was acquired in an Austrian prison over 3.5 months. We discuss the recording setup and resulting dataset, and present algorithms for detecting selected behaviors. The experimental results show that these behaviors can be detected reliably, demonstrating that automatic behavior analysis in 3D data is a promising means for supporting the security personnel.