Abstract-Wireless covert channels promise to exfiltrate information with high bandwidth by circumventing traditional access control mechanisms. Ideally, they are only accessible by the intended recipient and-for regular system users/operatorsindistinguishable from normal operation. While a number of theoretical and simulation studies exist in literature, the practical aspects of WiFi covert channels are not well understood. Yet, it is particularly the practical design and implementation aspect of wireless systems that provides attackers with the latitude to establish covert channels: the ability to operate under adverse conditions and to tolerate a high amount of signal variations. Moreover, covert physical receivers do not have to be addressed within wireless frames, but can simply eavesdrop on the transmission. In this work, we analyze the possibilities to establish covert channels in WiFi systems with emphasis on exploiting physical layer characteristics. We discuss design alternatives for selected covert channel approaches and study their feasibility in practice. By means of an extensive performance analysis, we compare the covert channel bandwidth. We further evaluate the possibility of revealing the introduced covert channels based on different detection capabilities.

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 highperformance. 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. CCS CONCEPTS• Security and privacy → Mobile and wireless security; • Networks → Link-layer protocols.

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Abstract. Tens of millions of wearable fitness trackers are shipped yearly to consumers who routinely collect information about their exercising patterns. Smartphones push this health-related data to vendors' cloud platforms, enabling users to analyze summary statistics on-line and adjust their habits. Third-parties including health insurance providers now offer discounts and financial rewards in exchange for such private information and evidence of healthy lifestyles. Given the associated monetary value, the authenticity and correctness of the activity data collected becomes imperative. In this paper, we provide an in-depth security analysis of the operation of fitness trackers commercialized by Fitbit, the wearables market leader. We reveal an intricate security through obscurity approach implemented by the user activity synchronization protocol running on the devices we analyze. Although non-trivial to interpret, we reverse engineer the message semantics, demonstrate how falsified user activity reports can be injected, and argue that based on our discoveries, such attacks can be performed at scale to obtain financial gains. We further document a hardware attack vector that enables circumvention of the end-to-end protocol encryption present in the latest Fitbit firmware, leading to the spoofing of valid encrypted fitness data. Finally, we give guidelines for avoiding similar vulnerabilities in future system designs.