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  1. Trusted execution environments (TEEs) have been proposed to protect GPU computation for machine learning applications operating on sensitive data. However, existing GPU TEE solutions either require CPU and/or GPU hardware modification to realize TEEs for GPUs, which prevents current systems from adopting them, or rely on untrusted system software such as GPU device drivers. In this paper, we propose using CPU secure enclaves, e.g., Intel SGX, to build GPU TEEs without modifications to existing hardware. To tackle the fundamental limitations of these enclaves, such as no support for I/O operations, we design and develop GEVisor, a formally verified security reference monitor software to enable a trusted I/O path between enclaves and GPU without trusting the GPU device driver. GEVisor operates in the Virtual Machine Extension (VMX) root mode, monitors the host system software to prevent unauthorized access to the GPU code and data outside the enclave, and isolates the enclave GPU context from other contexts during GPU computation. We implement and evaluate GEVisor on a commodity machine with an Intel SGX CPU and an NVIDIA Pascal GPU. Our experimental results show that our approach maintains an average overhead of 13.1% for deep learning and 18% for GPU benchmarks compared to native GPU computation while providing GPU TEEs for existing CPU and GPU hardware. 
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    Free, publicly-accessible full text available October 30, 2024
  2. WebGL is a set of standardized JavaScript APIs for GPU-accelerated graphics. Security of the WebGL interface is paramount because it exposes remote and unsandboxed access to the underlying graphics stack (including the native GL libraries and GPU drivers) in the host OS. Unfortunately, applying state-of-the-art fuzzing techniques to the WebGL interface for vulnerability discovery is challenging because of (1) its huge input state space, and (2) the infeasibility of collecting code coverage across concurrent processes, closed-source libraries, and device drivers in the kernel. Our fuzzing technique, GLeeFuzz, guides input mutation by error messages instead of code coverage. Our key observation is that browsers emit meaningful error messages to aid developers in debugging their WebGL programs. Error messages indicate which part of the input fails (e.g., incomplete arguments, invalid arguments, or unsatisfied dependencies between API calls). Leveraging error messages as feedback, the fuzzer effectively expands coverage by focusing mutation on erroneous parts of the input. We analyze Chrome’s WebGL implementation to identify the dependencies between error-emitting statements and rejected parts of the input, and use this information to guide input mutation. We evaluate our GLeeFuzz prototype on Chrome, Firefox, and Safari on diverse desktop and mobile OSes. We discovered 7 vulnerabilities, 4 in Chrome, 2 in Safari, and 1 in Firefox. The Chrome vulnerabilities allow a remote attacker to freeze the GPU and possibly execute remote code at the browser privilege. 
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    Free, publicly-accessible full text available August 9, 2024
  3. iOS is one of the most valuable targets for security researchers. Unfortunately, studying the internals of this operating system is notoriously hard, due to the closed nature of the iOS ecosystem and the absence of easily-accessible analysis tools. To address this issue, we developed TruEMU, which we present in this talk. TruEMU is the first open-source, extensible, whole-system iOS emulator. Compared to the few available alternatives, TruEMU enables complete iOS kernel emulation, including emulation of the SecureROM and the USB kernel stack. More importantly, TruEMU is completely free and open-source, and it is based on the well-known and highly extensible emulator QEMU. This talk will start by presenting the challenges and the solutions we devised to reverse engineer current iOS boot code and kernel code, and explain how to provide adequate support in QEMU. Then, to showcase TruEMU's usefulness and capabilities, we will demonstrate how it can completely boot modern iOS images, including iOS 14 and the latest iOS 15, and how it can properly run different user-space components, such as launchd, restored, etc. Later, we will showcase two promising ways to use TruEMU as an iOS vulnerability research platform. Specifically, we will demonstrate how to use TruEMU to enable coverage-based fuzzing of the iOS kernel USB stack. Further, we will show how TruEMU provides a platform to implement coverage-based, syscall-level fuzzing. This platform enables security researchers to automatically explore multiple attack surfaces of iOS. In sum, building a complete emulator for iOS is a daunting task. Many features (i.e., many peripherals) still need to be implemented to allow a complete emulation of a modern iOS device. We hope this talk will also bootstrap a large community involvement in this project that will progressively shed more light on the obscure corners of iOS security. 
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  4. 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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  5. Controller Area Network (CAN) is the de-facto standard in-vehicle network system. Despite its wide adoption by automobile manufacturers, the lack of security design makes it vulnerable to attacks. For instance, broadcasting packets without authentication allows the impersonation of electronic control units (ECUs). Prior mitigations, such as message authentication or intrusion detection systems, fail to address the compatibility requirement with legacy ECUs, stealthy and sporadic malicious messaging, or guaranteed attack detection. We propose a novel authentication system called ShadowAuth that overcomes the aforementioned challenges by offering backward-compatible packet authentication to ECUs without requiring ECU firmware source code. Specifically, our authentication scheme provides transparent CAN packet authentication without modifying existing CAN packet definitions (e.g., J1939) via automatic ECU firmware instrumentation technique to locate CAN packet transmission code, and instrument authentication code based on the CAN packet behavioral transmission patterns. ShadowAuth enables vehicles to detect state-of-the-art CAN attacks, such as bus-off and packet injection, responsively within 60ms without false positives. ShadowAuth provides a sound and deployable solution for real-world ECUs. 
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  6. Confidential computing aims to secure the code and data in use by providing a Trusted Execution Environment (TEE) for applications using hardware features such as Intel SGX.Timing and cache side-channel attacks, however, are often outside the scope of the threat model, although once exploited they are able to break all the default security guarantees enforced by hardware. Unfortunately, tools detecting potential side-channel vulnerabilities within applications are limited and usually ignore the strong attack model and the unique programming model imposed by Intel SGX. This paper proposes a precise side-channel analysis tool, ENCIDER, detecting both timing and cache side-channel vulnerabilities within SGX applications via inferring potential timing observation points and incorporating the SGX programming model into analysis. ENCIDER uses dynamic symbolic execution to decompose the side-channel requirement based on the bounded non-interference property and implements byte-level information flow tracking via API modeling. We have applied ENCIDER to 4 real-world SGX applications, 2 SGX crypto libraries, and 3 widely-used crypto libraries, and found 29 timing side channels and 73 code and data cache side channels. We have reported our findings to the corresponding parties, e.g., Intel and ARM, who have confirmed most of the vulnerabilities detected. 
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  7. Localization is one form of cooperative spectrum sensing that lets multiple sensors work together to estimate the location of a target transmitter. However, the requisite exchange of spectrum measurements leads to exposure of the physical loca- tion of participating sensors. Furthermore, in some cases, a com- promised participant can reveal the sensitive characteristics of all participants. Accordingly, a lack of sufficient guarantees about data handling discourages such devices from working together. In this paper, we provide the missing data protections by processing spectrum measurements within attestable containers or enclaves. Enclaves provide runtime memory integrity and confidentiality using hardware extensions and have been used to secure various applications [1]–[8]. We use these enclave features as building blocks for new privacy-preserving particle filter protocols that minimize disruption of the spectrum sensing ecosystem. We then instantiate this enclave using ARM TrustZone and Intel SGX, and we show that enclave-based particle filter protocols incur minimal overhead (adding 16 milliseconds of processing to the measurement processing function when using SGX versus unprotected computation) and can be deployed on resource-constrained platforms that support TrustZone (incurring only a 1.01x increase in processing time when doubling particle count from 10,000 to 20,000), whereas cryptographically-based approaches suffer from multiple orders of magnitude higher costs. We effectively deploy enclaves in a distributed environment, dramatically improving current data handling techniques. To our best knowledge, this is the first work to demonstrate privacy-preserving localization in a multi-party environment with reasonable overhead. 
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  8. null (Ed.)
    For system logs to aid in security investigations, they must be beyond the reach of the adversary. Unfortunately, attackers that have escalated privilege on a host are typically able to delete and modify log events at will. In response to this threat, a variety of secure logging systems have appeared over the years that attempt to provide tamper-resistance (e.g., write once read many drives, remote storage servers) or tamper-evidence (e.g., cryptographic proofs) for system logs. These solutions expose an interface through which events are committed to a secure log, at which point they enjoy protection from future tampering. However, all proposals to date have relied on the assumption that an event's occurrence is concomitant with its commitment to the secured log. In this work, we challenge this assumption by presenting and validating a race condition attack on the integrity of audit frameworks. Our attack exploits the intrinsically asynchronous nature of I/O and IPC activity, demonstrating that an attacker can snatch events about their intrusion out of message buffers after they have occurred but before they are committed to the log, thus bypassing existing protections. We present a first step towards defending against our attack by introducing KennyLoggings, the first kernel- based tamper-evident logging system that satisfies the synchronous integrity property, meaning that it guarantees tamper-evidence of events upon their occurrence. We implement KennyLoggings on top of the Linux kernel and show that it imposes between 8% and 11% overhead on log-intensive application workloads. 
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  9. null (Ed.)