The development of new technologies for video surveillance and automatic violence detection can bring more security to our daily lives. Solutions previously published in the state-of-the-art had presented techniques to detect violence at movie scenes, sports matches, or crowds. In this work, we propose a novel system architecture based on human Pose Track for detecting evidence of assaults in real-world videos from closed-circuit television (CCTV) of Brazilian lottery agencies. The results showed that our method can identify individuals with hands up and lying down with accuracy rates up to 85%. We believe that the detection of potentially risky situations in real-time is a crucial tool in the fighting against crime.