DEMO: Attaching InternalBlue to the Proprietary macOS IOBluetooth Framework

In this demo, we provide an overview of the macOS Bluetooth stack internals and gain access to undocumented low-level interfaces. We leverage this knowledge to add macOS support to the InternalBlue firmware modification and wireless experimentation framework.Comment: 13th ACM Conference on Security and Privacy in Wireless and Mobile Network

Inside Job: Diagnosing Bluetooth Lower Layers Using Off-the-Shelf Devices

Bluetooth is among the dominant standards for wireless short-range communication with multi-billion Bluetooth devices shipped each year. Basic Bluetooth analysis inside consumer hardware such as smartphones can be accomplished observing the Host Controller Interface (HCI) between the operating system's driver and the Bluetooth chip. However, the HCI does not provide insights to tasks running inside a Bluetooth chip or Link Layer (LL) packets exchanged over the air. As of today, consumer hardware internal behavior can only be observed with external, and often expensive tools, that need to be present during initial device pairing. In this paper, we leverage standard smartphones for on-device Bluetooth analysis and reverse engineer a diagnostic protocol that resides inside Broadcom chips. Diagnostic features include sniffing lower layers such as LL for Classic Bluetooth and Bluetooth Low Energy (BLE), transmission and reception statistics, test mode, and memory peek and poke

Acoustic Integrity Codes: Secure Device Pairing Using Short-Range Acoustic Communication

Secure Device Pairing (SDP) relies on an out-of-band channel to authenticate devices. This requires a common hardware interface, which limits the use of existing SDP systems. We propose to use short-range acoustic communication for the initial pairing. Audio hardware is commonly available on existing off-the-shelf devices and can be accessed from user space without requiring firmware or hardware modifications. We improve upon previous approaches by designing Acoustic Integrity Codes (AICs): a modulation scheme that provides message authentication on the acoustic physical layer. We analyze their security and demonstrate that we can defend against signal cancellation attacks by designing signals with low autocorrelation. Our system can detect overshadowing attacks using a ternary decision function with a threshold. In our evaluation of this SDP scheme's security and robustness, we achieve a bit error ratio below 0.1% for a net bit rate of 100 bps with a signal-to-noise ratio (SNR) of 14 dB. Using our open-source proof-of-concept implementation on Android smartphones, we demonstrate pairing between different smartphone models.Comment: 11 pages, 11 figures. Published at ACM WiSec 2020 (13th ACM Conference on Security and Privacy in Wireless and Mobile Networks). Updated reference

MagicPairing: Apple's Take on Securing Bluetooth Peripherals

Device pairing in large Internet of Things (IoT) deployments is a challenge for device manufacturers and users. Bluetooth offers a comparably smooth trust on first use pairing experience. Bluetooth, though, is well-known for security flaws in the pairing process. In this paper, we analyze how Apple improves the security of Bluetooth pairing while still maintaining its usability and specification compliance. The proprietary protocol that resides on top of Bluetooth is called MagicPairing. It enables the user to pair a device once with Apple's ecosystem and then seamlessly use it with all their other Apple devices. We analyze both, the security properties provided by this protocol, as well as its implementations. In general, MagicPairing could be adapted by other IoT vendors to improve Bluetooth security. Even though the overall protocol is well-designed, we identified multiple vulnerabilities within Apple's implementations with over-the-air and in-process fuzzing

Lost and Found: Stopping Bluetooth Finders from Leaking Private Information

A Bluetooth finder is a small battery-powered device that can be attached to important items such as bags, keychains, or bikes. The finder maintains a Bluetooth connection with the user's phone, and the user is notified immediately on connection loss. We provide the first comprehensive security and privacy analysis of current commercial Bluetooth finders. Our analysis reveals several significant security vulnerabilities in those products concerning mobile applications and the corresponding backend services in the cloud. We also show that all analyzed cloud-based products leak more private data than required for their respective cloud services. Overall, there is a big market for Bluetooth finders, but none of the existing products is privacy-friendly. We close this gap by designing and implementing PrivateFind, which ensures locations of the user are never leaked to third parties. It is designed to run on similar hardware as existing finders, allowing vendors to update their systems using PrivateFind.Comment: WiSec '2

DEMO: BTLEmap: Nmap for Bluetooth Low Energy

The market for Bluetooth Low Energy devices is booming and, at the same time, has become an attractive target for adversaries. To improve BLE security at large, we present BTLEmap, an auditing application for BLE environments. BTLEmap is inspired by network discovery and security auditing tools such as Nmap for IP-based networks. It allows for device enumeration, GATT service discovery, and device fingerprinting. It goes even further by integrating a BLE advertisement dissector, data exporter, and a user-friendly UI, including a proximity view. BTLEmap currently runs on iOS and macOS using Apple's CoreBluetooth API but also accepts alternative data inputs such as a Raspberry Pi to overcome the restricted vendor API. The open-source project is under active development and will provide more advanced capabilities such as long-term device tracking (in spite of MAC address randomization) in the future.Comment: 13th ACM Conference on Security and Privacy in Wireless and Mobile Network

ChirpOTLE: A Framework for Practical LoRaWAN Security Evaluation

Low-power wide-area networks (LPWANs) are becoming an integral part of the Internet of Things. As a consequence, businesses, administration, and, subsequently, society itself depend on the reliability and availability of these communication networks. Released in 2015, LoRaWAN gained popularity and attracted the focus of security research, revealing a number of vulnerabilities. This lead to the revised LoRaWAN 1.1 specification in late 2017. Most of previous work focused on simulation and theoretical approaches. Interoperability and the variety of implementations complicate the risk assessment for a specific LoRaWAN network. In this paper, we address these issues by introducing ChirpOTLE, a LoRa and LoRaWAN security evaluation framework suitable for rapid iteration and testing of attacks in testbeds and assessing the security of real-world networks.We demonstrate the potential of our framework by verifying the applicability of a novel denial-of-service attack targeting the adaptive data rate mechanism in a testbed using common off-the-shelf hardware. Furthermore, we show the feasibility of the Class B beacon spoofing attack, which has not been demonstrated in practice before.Comment: 11 pages, 14 figures, accepted at ACM WiSec 2020 (13th ACM Conference on Security and Privacy in Wireless and Mobile Networks

IoT Sentinel: Automated Device-Type Identification for Security Enforcement in IoT

With the rapid growth of the Internet-of-Things (IoT), concerns about the security of IoT devices have become prominent. Several vendors are producing IP-connected devices for home and small office networks that often suffer from flawed security designs and implementations. They also tend to lack mechanisms for firmware updates or patches that can help eliminate security vulnerabilities. Securing networks where the presence of such vulnerable devices is given, requires a brownfield approach: applying necessary protection measures within the network so that potentially vulnerable devices can coexist without endangering the security of other devices in the same network. In this paper, we present IOT SENTINEL, a system capable of automatically identifying the types of devices being connected to an IoT network and enabling enforcement of rules for constraining the communications of vulnerable devices so as to minimize damage resulting from their compromise. We show that IOT SENTINEL is effective in identifying device types and has minimal performance overhead

InternalBlue - Bluetooth Binary Patching and Experimentation Framework

Bluetooth is one of the most established technologies for short range digital wireless data transmission. With the advent of wearables and the Internet of Things (IoT), Bluetooth has again gained importance, which makes security research and protocol optimizations imperative. Surprisingly, there is a lack of openly available tools and experimental platforms to scrutinize Bluetooth. In particular, system aspects and close to hardware protocol layers are mostly uncovered. We reverse engineer multiple Broadcom Bluetooth chipsets that are widespread in off-the-shelf devices. Thus, we offer deep insights into the internal architecture of a popular commercial family of Bluetooth controllers used in smartphones, wearables, and IoT platforms. Reverse engineered functions can then be altered with our InternalBlue Python framework---outperforming evaluation kits, which are limited to documented and vendor-defined functions. The modified Bluetooth stack remains fully functional and high-performance. Hence, it provides a portable low-cost research platform. InternalBlue is a versatile framework and we demonstrate its abilities by implementing tests and demos for known Bluetooth vulnerabilities. Moreover, we discover a novel critical security issue affecting a large selection of Broadcom chipsets that allows executing code within the attacked Bluetooth firmware. We further show how to use our framework to fix bugs in chipsets out of vendor support and how to add new security features to Bluetooth firmware

Conducting a Large-scale Field Test of a Smartphone-based Communication Network for Emergency Response

Smartphone-based communication networks form a basis for services in emergency response scenarios, where communication infrastructure is impaired or overloaded. Still, their design and evaluation are largely based on simulations that rely on generic mobility models and weak assumptions regarding user behavior. For a realistic assessment, scenario-specific models are essential. To this end, we conducted a large-scale field test of a set of emergency services that relied solely on ad hoc communication. Over the course of one day, we gathered data from smartphones distributed to 125 participants in a scripted disaster event. In this paper, we present the scenario, measurement methodology, and a first analysis of the data. Our work provides the first trace combining user interaction, mobility, and additional sensor readings of a large-scale emergency response scenario, facilitating future research