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Being an easy-to-deploy and cost-effective low power wireless solution, Bluetooth Low Energy (BLE) has been widely used by Internet-of-Things (IoT) devices. In a typical IoT scenario, an IoT device first needs to be connected with its companion mobile app which serves as a gateway for its Internet access. To establish a connection, a device first broadcasts advertisement packets with UUIDs to nearby smartphone apps. Leveraging these UUIDs, a companion app is able to identify the device, pairs and bonds with it, and allows further data communication. However, we show that there is a fundamental flaw in the current design and implementation of the communication protocols between a BLE device and its companion mobile app, which allows an attacker to precisely fingerprint a BLE device with static UUIDs from the apps. Meanwhile, we also discover that many BLE IoT devices adopt "just works" pairing, allowing attackers to actively connect with these devices if there is no app-level authentication. Even worse, this vulnerability can also be directly uncovered from mobile apps. Furthermore, we also identify that there is an alarming number of vulnerable app-level authentication apps, which means the devices connected by these apps can be directly controlled by attackers. To raise the public awareness of IoT device fingerprinting and also uncover these vulnerable BLE IoT devices before attackers, we develop an automated mobile app analysis tool BLESCOPE and evaluate it with all of the free BLE IoT apps in Google Play store. Our tool has identified 1,757 vulnerable mobile apps in total. We also performed a field test in a 1.28 square miles region, and identified 5,822 real BLE devices, among them 5,509 (94.6%) are fingerprintable by attackers, and 431 (7.4%) are vulnerable to unauthorized access. We have made responsible disclosures to the corresponding app developers, and also reported the fingerprinting issues to the Bluetooth Special Interest Group.

Automatic Fingerprinting of Vulnerable BLE IoT Devices with Static UUIDs from Mobile Apps