As computing becomes increasingly mobile, the demand for information about the environment, or context, becomes of significant importance. Applications must adapt to the changing environment, however acquiring the necessary context information can be very expensive because collecting it usually requires communication among devices. We explore collecting reasonably accurate context information passively by defining passively sensed context through network overhearing, defining context metrics without added communication cost. We use this framework to build a small suite of commonly used context metrics and evaluate the quality with which they can reflect ground truth using simulation. We also provide an implementation of this passive sensing framework for Linux, which we evaluate on a real mobile ad-hoc network using mobile autonomous robots with commodity 802.11 b/g wireless cards.