The widespread use of smart devices gives rise to privacy concerns. Fingerprinting smart devices can jeopardize privacy by allowing remote identification without user awareness. We study the feasibility of using microphones and speakers embedded in smartphones to uniquely fingerprint individual devices. During fabrication, subtle imperfections arise in device microphones and speakers, which induce anomalies in produced and received sounds. We exploit this observation to fingerprint smartphones through playback and recording of audio samples. We explore different acoustic features and analyze their ability to successfully fingerprint smartphones. Our experiments show that not only is it possible to fingerprint devices manufactured by different vendors but also devices that have the same maker and model; on average we were able to accurately attribute 98% of all recorded audio clips from 50 different Android smartphones. Our study also identifies the prominent acoustic features capable of fingerprinting smart devices with a high success rate, and examines the effect of background noise and other variables on fingerprinting accuracy.