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1. STASE: Static Analysis Guided Symbolic Execution for UEFI Vulnerability Signature Generation

   Shafiuzzaman, Md; Desai, Achintya; Sarker, Laboni; Bultan, Tevfik (October 2024, ACM)

   Since its major release in 2006, the Unified Extensible Firmware Interface (UEFI) has become the industry standard for interfacing a computer’s hardware and operating system, replacing BIOS. UEFI has higher privileged security access to system resources than any other software component, including the system kernel. Hence, identifying and characterizing vulnerabilities in UEFI is extremely important for computer security. However, automated detection and characterization of UEFI vulnerabilities is a challenging problem. Static vulnerability analysis techniques are scalable but lack precision (reporting many false positives), whereas symbolic analysis techniques are precise but are hampered by scalability issues due to path explosion and the cost of constraint solving. In this paper, we introduce a technique called STatic Analysis guided Symbolic Execution (STASE), which integrates both analysis approaches to leverage their strengths and minimize their weaknesses. We begin with a rule-based static vulnerability analysis on LLVM bitcode to identify potential vulnerability targets for symbolic execution. We then focus symbolic execution on each target to achieve precise vulnerability detection and signature generation. STASE relies on the manual specification of reusable vulnerability rules and attacker-controlled inputs. However, it automates the generation of harnesses that guide the symbolic execution process, addressing the usability and scalability of symbolic execution, which typically requires manual harness generation to reduce the state space. We implemented and applied STASE to the implementations of UEFI code base. STASE detects and generates vulnerability signatures for 5 out of 9 recently reported PixieFail vulnerabilities and 13 new vulnerabilities in Tianocore’s EDKII codebase. 

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2. On Runtime Software Security of TrustZone-M Based IoT Devices

   https://doi.org/10.1109/GLOBECOM42002.2020.9322370  

   Luo, Lan; Zhang, Yue; Zou, Cliff; Shao, Xinhui; Ling, Zhen; Fu, Xinwen (December 2020, GLOBECOM 2020 - 2020 IEEE Global Communications Conference)

   null (Ed.)

   Internet of Things (IoT) devices have been increasingly integrated into our daily life. However, such smart devices suffer a broad attack surface. Particularly, attacks targeting the device software at runtime are challenging to defend against if IoT devices use resource-constrained microcontrollers (MCUs). TrustZone-M, a TrustZone extension for MCUs, is an emerging security technique fortifying MCU based IoT devices. This paper presents the first security analysis of potential software security issues in TrustZone-M enabled MCUs. We explore the stack-based buffer overflow (BOF) attack for code injection, return-oriented programming (ROP) attack, heap-based BOF attack, format string attack, and attacks against Non-secure Callable (NSC) functions in the context of TrustZone-M. We validate these attacks using the Microchip SAM L11 MCU, which uses the ARM Cortex-M23 processor with the TrustZone-M technology. Strategies to mitigate these software attacks are also discussed. 

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3. Vigilia: Securing Smart Home Edge Computing

   https://doi.org/10.1109/SEC.2018.00013  

   Trimananda, Rahmadi; Younis, Ali; Wang, Bojun; Xu, Bin; Demsky, Brian; Xu, Guoqing (October 2018, ACM/IEEE Symposium on Edge Computing)

   Smart home IoT devices are becoming increasingly popular. Modern programmable smart home hubs such as SmartThings enable homeowners to manage devices in sophisticated ways to save energy, improve security, and provide conveniences. Unfortunately, many smart home systems contain vulnerabilities, potentially impacting home security and privacy. This paper presents Vigilia, a system that shrinks the attack surface of smart home IoT systems by restricting the network access of devices. As existing smart home systems are closed, we have created an open implementation of a similar programming and configuration model in Vigilia and extended the execution environment to maximally restrict communications by instantiating device-based network permissions. We have implemented and compared Vigilia with forefront IoT-defense systems; our results demonstrate that Vigilia outperforms these systems and incurs negligible overhead. 

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4. Physical Devices-Agnostic Hybrid Fuzzing of IoT Firmware

   https://doi.org/10.1109/JIOT.2023.3303780  

   Situ, Lingyun; Zhang, Chi; Guan, Le; Zuo, Zhiqiang; Wang, Linzhang; Li, Xuandong; Liu, Peng; Shi, Jin (January 2023, IEEE Internet of Things Journal)

   With the rapid expansion of the Internet of Things, a vast number of microcontroller-based IoT devices are now susceptible to attacks through the Internet. Vulnerabilities within the firmware are one of the most important attack surfaces. Fuzzing has emerged as one of the most effective techniques for identifying such vulnerabilities. However, when applied to IoT firmware, several challenges arise, including: (1) the inability of firmware to execute properly in the absence of peripherals, (2) the lack of support for exploring input spaces of multiple peripherals, (3) difficulties in instrumenting and gathering feedback, and (4) the absence of a fault detection mechanism. To address these challenges, we have developed and implemented an innovative peripheral-independent hybrid fuzzing tool called . This tool enables testing of microcontroller-based firmware without reliance on specific peripheral hardware. First, a unified virtual peripheral was integrated to model the behaviors of various peripherals, thus enabling the physical devices-agnostic firmware execution. Then, a hybrid event generation approach was used to generate inputs for different peripheral accesses. Furthermore, two-level coverage feedback was collected to optimize the testcase generation. Finally, a plugin-based fault detection mechanism was implemented to identify typical memory corruption vulnerabilities. A Large-scale experimental evaluation has been performed to show ’s effectiveness and efficiency. 

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5. FuzzUSB: Hybrid Stateful Fuzzing of USB Gadget Stacks

   https://doi.org/10.1109/SP46214.2022.00037  

   Kim, Kyungtae; Kim, Taegyu; Warrich, Ertza; Lee, Byounyoung; Butler, Kevin; Bianchi, Antonio; Tian, Dave (May 2022, 2022 IEEE Symposium on Security and Privacy (SP))

   Universal Serial Bus (USB) is the de facto protocol supported by peripherals and mobile devices, such as USB thumb drives and smartphones. For many devices, USB Type-C ports are the primary interface for charging, file transfer, audio, video, etc. Accordingly, attackers have exploited different vulnerabilities within USB stacks, compromising host machines via BadUSB attacks or jailbreaking iPhones from USB connections. While there exist fuzzing frameworks dedicated to USB vulnerability discovery, all of them focus on USB host stacks and ignore USB gadget stacks, which enable all the features within modern peripherals and smart devices. In this paper, we propose FUZZUSB, the first fuzzing framework for the USB gadget stack within commodity OS kernels, leveraging static analysis, symbolic execution, and stateful fuzzing. FUZZUSB combines static analysis and symbolic execution to extract internal state machines from USB gadget drivers, and uses them to achieve state-guided fuzzing through multi-channel in- puts. We have implemented FUZZUSB upon the syzkaller kernel fuzzer and applied it to the most recent mainline Linux, Android, and FreeBSD kernels. As a result, we have found 34 previously unknown bugs within the Linux and Android kernels, and opened 7 CVEs. Furthermore, compared to the baseline, FUZZUSB has also demonstrated different improvements, including 3× higher code coverage, 50× improved bug-finding efficiency for Linux USB gadget stacks, 2× higher code coverage for FreeBSD USB gadget stacks, and reproducing known bugs that could not be detected by the baseline fuzzers. We believe FUZZUSB provides developers a powerful tool to thwart USB-related vulnerabilities within modern devices and complete the current USB fuzzing scope. 

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