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1. Understanding the Security of ARM Debugging Features

   Ning, Z; Zhang, F. (May 2019, Proceedings - IEEE Symposium on Security and Privacy)

   Processors nowadays are consistently equipped with debugging features to facilitate the program analysis. Specifically, the ARM debugging architecture involves a series of CoreSight components and debug registers to aid the system debugging, and a group of debug authentication signals are designed to restrict the usage of these components and registers. Meantime, the security of the debugging features is under-examined since it normally requires physical access to use these features in the traditional debugging model. However, ARM introduces a new debugging model that requires no physical access since ARMv7, which exacerbates our concern on the security of the debugging features. In this paper, we perform a comprehensive security analysis of the ARM debugging features, and summarize the security and vulnerability implications. To understand the impact of the implications, we also investigate a series of ARM-based platforms in different product domains (i.e., development boards, IoT devices, cloud servers, and mobile devices). We consider the analysis and investigation expose a new attacking surface that universally exists in ARM-based platforms. To verify our concern, we further craft Nailgun attack, which obtains sensitive information (e.g., AES encryption key and fingerprint image) and achieves arbitrary payload execution in a high-privilege mode from a low-privilege mode via misusing the debugging features. This attack does not rely on software bugs, and our experiments show that almost all the platforms we investigated are vulnerable to the attack. The potential mitigations are discussed from different perspectives in the ARM ecosystem. 

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2. A Study of Data Store-based Home Automation

   https://doi.org/10.1145/3292006.3300031  

   Kafle, Kaushal; Moran, Kevin; Manandhar, Sunil; Nadkarni, Adwait; Poshyvanyk, Denys (March 2019, Proceedings of the Ninth ACM Conference on Data and Application Security and Privacy)

   Home automation platforms provide a new level of convenience by enabling consumers to automate various aspects of physical objects in their homes. While the convenience is beneficial, security flaws in the platforms or integrated third-party products can have serious consequences for the integrity of a user's physical environment. In this paper we perform a systematic security evaluation of two popular smart home platforms, Google's Nest platform and Philips Hue, that implement home automation "routines" (i.e., trigger-action programs involving apps and devices) via manipulation of state variables in a centralized data store. Our semi-automated analysis examines, among other things, platform access control enforcement, the rigor of non-system enforcement procedures, and the potential for misuse of routines. This analysis results in ten key findings with serious security implications. For instance, we demonstrate the potential for the misuse of smart home routines in the Nest platform to perform a lateral privilege escalation, illustrate how Nest's product review system is ineffective at preventing multiple stages of this attack that it examines, and demonstrate how emerging platforms may fail to provide even bare-minimum security by allowing apps to arbitrarily add/remove other apps from the user's smart home. Our findings draw attention to the unique security challenges of platforms that execute routines via centralized data stores, and highlight the importance of enforcing security by design in emerging home automation platforms. 

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3. Security in Centralized Data Store-based Home Automation Platforms: A Systematic Analysis of Nest and Hue

   https://doi.org/10.1145/3418286  

   Kafle, Kaushal; Moran, Kevin; Manandhar, Sunil; Nadkarni, Adwait; Poshyvanyk, Denys (January 2021, ACM Transactions on Cyber-Physical Systems)

   Home automation platforms enable consumers to conveniently automate various physical aspects of their homes. However, the security flaws in the platforms or integrated third-party products can have serious security and safety implications for the user’s physical environment. This article describes our systematic security evaluation of two popular smart home platforms, Google’s Nest platform and Philips Hue, which implement home automation “routines” (i.e., trigger-action programs involving apps and devices) via manipulation of state variables in a centralized data store . Our semi-automated analysis examines, among other things, platform access control enforcement, the rigor of non-system enforcement procedures, and the potential for misuse of routines, and it leads to 11 key findings with serious security implications. We combine several of the vulnerabilities we find to demonstrate the first end-to-end instance of lateral privilege escalation in the smart home, wherein we remotely disable the Nest Security Camera via a compromised light switch app. Finally, we discuss potential defenses, and the impact of the continuous evolution of smart home platforms on the practicality of security analysis. Our findings draw attention to the unique security challenges of smart home platforms and highlight the importance of enforcing security by design. 

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4. Erebus: Access Control for Augmented Reality Systems., USENIX Security, 2023. Published.

   Kim, Y.; Goutam, S.; Rahmati, A.; Kaufman, A. (January 2023, USENIX Security)

   Augmented Reality (AR) is widely considered the next evolution in personal devices, enabling seamless integration of the digital world into our reality. Such integration, however, often requires unfettered access to sensor data, causing significant over privilege for applications that run on these platforms. Through analysis of 17 AR systems and 45 popular AR applications, we explore existing mechanisms for access control in AR platforms, identify key trends in how AR applications use sensor data, and pinpoint unique threats users face in AR environments. Using these findings, we design and implement Erebus, an access control framework for AR platforms that enables fine-grained control over data used by AR applications. Erebus achieves the principle of least privileged through the creation of a domain-specific language (DSL) for permission control in AR platforms, allowing applications to specify data needed for their functionality. Using this DSL, Erebus further enables users to customize app permissions to apply under specific user conditions. We implement Erebus on Google’s ARCore SDK and port five existing AR applications to demonstrate the capability of Erebus to secure various classes of apps. Performance results using these applications and various microbenchmarks show that Erebus achieves its security goals while being practical, introducing negligible performance overhead to the AR system. 

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5. A Study of Application Sandbox Policies in Linux

   https://doi.org/10.1145/3532105.3535016  

   Dunlap, Trevor; Enck, William; Reaves, Bradley (June 2022, ACM Symposium on Access Control Models and Technologies (SACMAT))

   Desktop operating systems, including macOS, Windows 10, and Linux, are adopting the application-based security model pervasive in mobile platforms. In Linux, this transition is part of the movement towards two distribution-independent application platforms: Flatpak and Snap. This paper provides the first analysis of sandbox policies defined for Flatpak and Snap applications, covering 283 applications contained in both platforms. First, we find that 90.1% of Snaps and 58.3% of Flatpak applications studied are contained by tamperproof sandboxes. Further, we find evidence that package maintainers actively attempt to define least-privilege application policies. However, defining policy is difficult and error-prone. When studying the set of matching applications that appear in both Flatpak and Snap app stores, we frequently found policy mismatches: e.g., the Flatpak version has a broad privilege (e.g., file access) that the Snap version does not, or vice versa. This work provides confidence that Flatpak and Snap improve Linux platform security while highlighting opportunities for improvement. 

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