Xiaomi is the leading company in the fitness tracking industry. Successful attacks on its fitness tracking ecosystem would result in severe consequences, including the loss of sensitive health and personal data. Despite these relevant risks, we know very little about the security mechanisms adopted by Xiaomi. In this work, we uncover them and show that they are insecure. In particular, Xiaomi protects its fitness tracking ecosystem with custom application-layer protocols spoken over insecure Bluetooth Low-Energy (BLE) connections (ignoring standard BLE security mechanisms already supported by their devices) and TLS connections. We identify severe vulnerabilities affecting such proprietary protocols, including unilateral and replayable authentication. Those issues are critical as they affect all Xiaomi trackers released since 2016 and up-to-date Xiaomi companion apps for Android and iOS. We show in practice how to exploit the identified vulnerabilities by presenting six impactful attacks. Four attacks enable to wirelessly impersonate any Xiaomi fitness tracker and companion app, man-in-the-middle (MitM) them, and eavesdrop on their communication. The other two attacks leverage a malicious Android application to remotely eavesdrop on data from a tracker and impersonate a Xiaomi fitness app. Overall, the attacks have a high impact as they can be used to exfiltrate and inject sensitive data from any Xiaomi tracker and compatible app. We propose five practical and low-overhead countermeasures to mitigate the presented vulnerabilities. Moreover, we present breakmi, a modular toolkit that we developed to automate our reverse-engineering process and attacks. breakmi understands Xiaomi application-layer proprietary protocols, reimplements Xiaomi security mechanisms, and automatically performs our attacks. We demonstrate that our toolkit can be generalized by extending it to be compatible with the Fitbit ecosystem. We will open-source breakmi.@en

Xiaomi is the market leader in the electric scooter (e-scooter) segment, with millions of active users. It provides several e-scooter models and Mi Home, a mobile application for Android and iOS to manage and control an e-scooter. Mi Home and the e-scooter interact via Bluetooth Low Energy (BLE). No prior research evaluated the security of this communication channel, as it employs security protocols proprietary to Xiaomi. Exploiting these protocols results in severe security, privacy, and safety issues, e.g., an attacker could steal an e-scooter or prevent the owner from controlling it. In this work, we fill this research gap by performing the first security evaluation on all proprietary wireless protocols deployed to Xiaomi e-scooters from 2016 to 2021. We identify and reverse-engineer four of them, each having ad-hoc Pairing and Session phases. We develop four attacks exploiting these protocols at the architectural level, and we call them Malicious Pairing (MP) and Session Downgrade (SD). Both attacks can be performed from proximity, if the attacker's machine is within BLE range of the target e-scooter, or remotely, via a malicious application co-located with Mi Home. An adversary can utilize MP and SD to steal a password-protected and software-locked e-scooter, or to prevent a victim from accessing it via Mi Home. We isolate six attack root causes, including the lack of authentication while pairing, and the improper enforcement of the e-scooter password. We open-source the E-Spoofer toolkit. Our toolkit automates the MP and SD attacks, and includes a reverse-engineering module for future research. We empirically confirm the effectiveness of our attacks by exploiting three e-scooters (i.e., M365, Essential, and Mi 3), embedding five BLE subsystem boards and eight BLE firmware versions that support all four Xiaomi protocols. We design and evaluate two practical countermeasures that address our impactful attacks and their root causes, and we release them as part of E-Spoofer. We responsibly disclosed our findings to Xiaomi. @en