Hardware supply-chain attacks are raising significant security threats to the boot process of multiprocessor systems. In this paper, we investigate critical stages of the multiprocessor system boot process and identify a new, prevalent hardware supply-chain attack surface that can bypass secure boot due to the absence of processor-authentication mechanisms. To defend against such attacks, in this paper, we present PA-Boot, the first formally verified processor-authentication protocol for secure boot in multiprocessor systems. PA-Boot is proved functionally correct and is guaranteed to detect multiple adversarial behaviors, such as processor replacements and man-in-the-middle attacks. The fine-grained formalization of PA-Boot and its fully mechanized security proofs are carried out in the Isabelle/HOL theorem prover with 348 lemmas/theorems and ~7,100 LoC. We further implement in C an instance of PA-Boot. Experiments on the proof-of-concept implementation indicate that PA-Boot can effectively identify boot-process attacks with a minor overhead (4.98% on Linux boot process) and thereby improve the security of multiprocessor systems.

Fuzzing is an effective method for detecting security bugs in software, and there have been quite a few effective works on fuzzing Android. Researchers have developed methods for fuzzing open-source native APIs and Java interfaces on actual Android devices. However, the realm of automatically fuzzing Android closed-source native libraries, particularly on emulators, remains insufficiently explored. There are two key challenges: firstly, the multi-language programming model inherent to Android; and secondly, the absence of a Java runtime environment within the emulator. To address these challenges, we propose Atlas, a practical automated fuzz framework for Android closed-source native libraries. Atlas consists of an automatic harness generator and a fuzzer containing the necessary runtime environment. The generator uses static analysis techniques to deduce the correct calling sequences and parameters of the native API according to the information from the "native world" and the "Java world". To maximize the practicality of the generated harness, Atlas heuristically optimizes the generated harness. The Fuzzer provides the essential Java runtime environment in the emulator, making it possible to fuzz the Android closed-source native libraries on a multi-core server. We have tested Atlas on 17 pre-installed apps from four Android vendors. Atlas generates 820 harnesses containing 767 native APIs, of which 78% is practical. Meanwhile, Atlas has discovered 74 new security bugs with 16 CVEs assigned. The experiments show that Atlas can efficiently generate high-quality harnesses and find security bugs.

Embedded devices are becoming ubiquitous, and ARM is becoming the dominant architecture for them. Meanwhile, there is a pressing need to perform security assessments for these devices. Due to different types of peripherals, emulating the software, i.e., firmware, of these devices in scale is challenging. Therefore, static analysis is still widely used. Existing works usually leverage off-the-shelf tools to disassemble stripped ARM binaries and (implicitly) assume that reliably disassembling binaries is a solved problem. However, whether this assumption really holds is unknown. In this paper, we conduct the first comprehensive study on ARM disassembly tools. Specifically, we build 1,896 ARM binaries (including 248 obfuscated ones) with different compilers, compiling options, and obfuscation methods. We then evaluate them using eight state-of-the-art ARM disassembly tools (including both commercial and noncommercial ones) in three different versions on their capabilities to locate instruction boundary, function boundary, and function signature. Instruction and function boundary are two fundamental primitives that the other primitives are built upon while function signature is significant for control flow integrity (CFI) techniques. Our work reveals some observations that have not been systematically summarized and/or confirmed. For instance, we find that the existence of both ARM and Thumb instruction sets, and the reuse of theBLinstruction for both function calls and branches bring serious challenges to disassembly tools. Our evaluation sheds light on the limitations of state-of-the-art disassembly tools and points out potential directions for improvement.

IoT devices are abnormally prone to diverse errors due to harsh environments and limited computational capabilities. As a result, correct error handling is critical in IoT. Implementing correct error handling is non-trivial, thus requiring extensive testing such as fuzzing. However, existing fuzzing cannot effectively test IoT error-handling code. First, errors typically represent corner cases, thus are hard to trigger. Second, testing error-handling code would frequently crash the execution, which prevents fuzzing from testing following deep error paths.In this paper, we propose IFIZZ, a new bug detection system specifically designed for testing error-handling code in Linux-based IoT firmware. IFIZZ first employs an automated binary-based approach to identify realistic runtime errors by analyzing errors and error conditions in closed-source IoT firmware. Then, IFIZZ employs state-aware and bounded error generation to reach deep error paths effectively. We implement and evaluate IFIZZ on 10 popular IoT firmware. The results show that IFIZZ can find many bugs hidden in deep error paths. Specifically, IFIZZ finds 109 critical bugs, 63 of which are even in widely used IoT libraries. IFIZZ also features high code coverage and efficiency, and covers 67.3% more error paths than normal execution. Meanwhile, the depth of error handling covered by IFIZZ is 7.3 times deeper than that covered by the state-of-the-art method. Furthermore, IFIZZ has been practically adopted and deployed in a worldwide leading IoT company. We will open-source IFIZZ to facilitate further research in this area.