Processor Microarchitecture Security

As computer systems grow more and more complicated, various optimizations can unintentionally introduce security vulnerabilities in these systems. The vulnerabilities can lead to user information and data being compromised or stolen. In particular, the ending of both Moore\u27s law and Dennard scaling motivate the design of more exotic microarchitectural optimizations to extract more performance -- further exacerbating the security vulnerabilities. The performance optimizations often focus on sharing or re-using of hardware components within a processor, between different users or programs. Because of the sharing of the hardware, unintentional information leakage channels, through the shared components, can be created. Microarchitectural attacks, such as the high-profile Spectre and Meltdown attacks or the cache covert channels that they leverage, have demonstrated major vulnerabilities of modern computer architectures due to the microarchitectural~optimizations. Key components of processor microarchitectures are processor caches used for achieving high memory bandwidth and low latency for frequently accessed data. With frequently accessed data being brought and stored in caches, memory latency can be significantly reduced when data is fetched from the cache, as opposed to being fetched from the main memory. With limited processor chip area, however, the cache size cannot be very large. Thus, modern processors adopt a cache hierarchy with multiple levels of caches, where the cache close to processor is faster but smaller, and the cache far from processor is slower but larger. This leads to a fundamental property of modern processors: {\em the latency of accessing data in different cache levels and in main memory is different}. As a result, the timing of memory operations when fetching data from different cache levels, e.g., the timing of fetching data from closest-to-processor L1 cache vs. from main memory, can reveal secret-dependent information if attacker is able to observe the timing of these accesses and correlate them to the operation of the victim\u27s code. Further, due to limited size of the caches, memory accesses by a victim may displace attacker\u27s data from the cache, and with knowledge, or reverse-engineering, of the cache architecture, the attacker can learn some information about victim\u27s data based on the modifications to the state of the cache -- which can be observed by the timing~measurements. Caches are not only structures in the processor that can suffer from security vulnerabilities. As an essential mechanism to achieving high performance, cache-like structures are used pervasively in various processor components, such as the translation lookaside buffer (TLB) and processor frontend. Consequently, the vulnerabilities due to timing differences of accessing data in caches or cache-like structures affect many components of the~processor. The main goal of this dissertation is the {\em design of high performance and secure computer architectures}. Since the sophisticated hardware components such as caches, TLBs, value predictors, and processor frontend are critical to ensure high performance, realizing this goal requires developing fundamental techniques to guarantee security in the presence of timing differences of different processor operations. Furthermore, effective defence mechanisms can be only developed after developing a formal and systematic understanding of all the possible attacks that timing side-channels can lead to. To realize the research goals, the main main contributions of this dissertation~are: \begin{itemize}[noitemsep] \item Design and evaluation of a novel three-step cache timing model to understand theoretical vulnerabilities in caches \item Development of a benchmark suite that can test if processor caches or secure cache designs are vulnerable to certain theoretical vulnerabilities. \item Development of a timing vulnerability model to test TLBs and design of hardware defenses for the TLBs to address newly found vulnerabilities. \item Analysis of value predictor attacks and design of defenses for value predictors. \item Evaluation of vulnerabilities in processor frontends based on timing differences in the operation of the frontends. \item Development of a design-time security verification framework for secure processor architectures, using information flow tracking methods. \end{itemize} \newpage This dissertation combines the theoretical modeling and practical benchmarking analysis to help evaluate susceptibility of different architectures and microarchitectures to timing attacks on caches, TLBs, value predictors and processor frontend. Although cache timing side-channel attacks have been studied for more than a decade, there is no evidence that the previously-known attacks exhaustively cover all possible attacks. One of the initial research directions covered by this dissertation was to develop a model for cache timing attacks, which can help lead towards discovering all possible cache timing attacks. The proposed three-step cache timing vulnerability model provides a means to enumerate all possible interactions between the victim and attacker who are sharing a cache-like structure, producing the complete set of theoretical timing vulnerabilities. This dissertation also covers new theoretical cache timing attacks that are unknown prior to being found by the model. To make the advances in security not only theoretical, this dissertation also covers design of a benchmarking suite that runs on commodity processors and helps evaluate their cache\u27s susceptibility to attacks, as well as can run on simulators to test potential or future cache designs. As the dissertation later demonstrates, the three-step timing vulnerability model can be naturally applied to any cache-like structures such as TLBs, and the dissertation encompasses a three-step model for TLBs, uncovering of theoretical new TLB attacks, and proposals for defenses. Building on success of analyzing caches and TLBs for new timing attacks, this dissertation then discusses follow-on research on evaluation and uncovering of new timing vulnerabilities in processor frontends. Since security analysis should be applied not just to existing processor microarchitectural features, the dissertation further analyzes possible future features such as value predictors. Although not currently in use, value predictors are actively being researched and proposed for addition into future microarchitectures. This dissertation shows, however, that they are vulnerable to attacks. Lastly, based on findings of the security issues with existing and proposed processor features, this dissertation explores how to better design secure processors from ground up, and presents a design-time security verification framework for secure processor architectures, using information flow tracking methods

A software approach to defeating side channels in last-level caches

We present a software approach to mitigate access-driven side-channel attacks that leverage last-level caches (LLCs) shared across cores to leak information between security domains (e.g., tenants in a cloud). Our approach dynamically manages physical memory pages shared between security domains to disable sharing of LLC lines, thus preventing "Flush-Reload" side channels via LLCs. It also manages cacheability of memory pages to thwart cross-tenant "Prime-Probe" attacks in LLCs. We have implemented our approach as a memory management subsystem called CacheBar within the Linux kernel to intervene on such side channels across container boundaries, as containers are a common method for enforcing tenant isolation in Platform-as-a-Service (PaaS) clouds. Through formal verification, principled analysis, and empirical evaluation, we show that CacheBar achieves strong security with small performance overheads for PaaS workloads

Leveraging Programmable Data Plane For Compressing Forwarding Tables

The Forwarding Information Base (FIB) resides in the data plane of a routing device and is used to forward packets to a next-hop, based on packets\u27 destination IP addresses. The constant growth of a FIB forces network operators to spend more resources on maintaining memory with line-rate Longest Prefix Match (LPM) lookup in a FIB, namely, expensive and energy-hungry Ternary Content-Addressable Memory (TCAM) chips. In this work, we review two different approaches used to mitigate the FIB overflow problem. First, we investigate FIB aggregation, i.e., merging adjacent or overlapping routes with the same next-hop while preserving the forwarding behavior of a FIB. We propose a near-optimal algorithm, FIB Aggregation with Quick Selections (FAQS), that minimizes the FIB churn and speeds BGP update processing by more than twice. In the meantime, FAQS preserves a high compression ratio (at most 73\%). FAQS handles BGP updates incrementally, without the need of re-aggregating the entire FIB table. Second, we investigate FIB (or route) caching, when TCAM holds only a portion of a FIB that carries most of the traffic. We leverage the emerging concept of the programmable data plane to propose a Programmable FIB Caching Architecture (PFCA), that allows cache-victim selection at the line rate and significantly reduces the FIB churn compared to FIB aggregation. PFCA achieves 99.8% cache-hit ratio with only 3.3\% of the FIB placed in a FIB cache. Finally, we extend PFCA\u27s design with a novel approach of integrating incremental FIB aggregation and FIB caching. Such integration needed to overcome cache hiding challenge when a less specific prefix in a cache hides a more specific prefix in a secondary FIB table, which leads to incorrect LPM matching at the cache. In Combined FIB Caching and Aggregation (CFCA), cache-hit ratio is maximized up to 99.94% with only 2.5\% entries of the FIB, while the total number of route changes in TCAM is reduced by more than 40\% compared to low-churn FIB aggregation techniques

When a Patch is Not Enough - HardFails: Software-Exploitable Hardware Bugs

In this paper, we take a deep dive into microarchitectural security from a hardware designer's perspective by reviewing the existing approaches to detect hardware vulnerabilities during the design phase. We show that a protection gap currently exists in practice that leaves chip designs vulnerable to software-based attacks. In particular, existing verification approaches fail to detect specific classes of vulnerabilities, which we call HardFails: these bugs evade detection by current verification techniques while being exploitable from software. We demonstrate such vulnerabilities in real-world SoCs using RISC-V to showcase and analyze concrete instantiations of HardFails. Patching these hardware bugs may not always be possible and can potentially result in a product recall. We base our findings on two extensive case studies: the recent Hack@DAC 2018 hardware security competition, where 54 independent teams of researchers competed world-wide over a period of 12 weeks to catch inserted security bugs in SoC RTL designs, and an in-depth systematic evaluation of state-of-the-art verification approaches. Our findings indicate that even combinations of techniques will miss high-impact bugs due to the large number of modules with complex interdependencies and fundamental limitations of current detection approaches. We also craft a real-world software attack that exploits one of the RTL bugs from Hack@DAC that evaded detection and discuss novel approaches to mitigate the growing problem of cross-layer bugs at design time