The widespread use of Smart Home devices has attracted significant research interest in understanding their behavior within home networks. Unlike general-purpose computers, these devices exhibit relatively simple and predictable network activity patterns. However, previous studies have primarily focused on normal network conditions, overlooking potential hidden patterns that emerge under challenging conditions. Discovering the latter is crucial for assessing device robustness.This paper addresses this gap by presenting a framework that systematically and automatically reveals these hidden communication patterns. By actively disturbing communication and blocking observed traffic, the framework generates comprehensive profiles structured as behavior trees, uncovering traffic flows that are missed by more shallow methods. This approach was applied to ten real-world devices, identifying 254 unique flows, with over 27% only discovered through this new method. These insights enhance our understanding of device robustness, and the thus obtained profiles provide a more complete description of the network behavior of devices, as needed, for example, for the configuration of security solutions.