Daniel Genkin

Microarchitectural website-fingerprinting attacks use timing information to leak the browsing habits of a victim to co-resident attackers. Microarchitectural leakage in these attacks often comprises multiple sources. While most published attacks claim to identify the cause of leakage, these claims are not always well supported. Thus, so far the question of how to determine what leaks remains mostly unanswered. In this work, we develop a framework for identifying and measuring the contribution of leakage sources to the overall observations the attacker makes. Experimenting with three website-fingerprinting attacks in the literature, we qualitatively identify four main classes of leakage sources: core contention, interrupts, frequency scaling, and cache eviction. We demonstrate cases where we can completely mitigate leakage by controlling these sources. We then show that enabling each of the sources individually leaks enough to allow website-fingerprinting attacks. In the quantitative analysis, we use the correlation between events related to each source and the measured timing in the attacks as a metric to determine the relative contribution of each source to the specific attack. Our work provides insights into the leakage sources of coarse-grained microarchitectural attacks, aiding the design of secure processor systems as well as more effective attacks and defenses.

How will future microarchitectures impact the security of existing cryptographic implementations? As we cannot keep reducing the size of transistors, chip vendors have started developing new microarchitectural optimizations to speed up computation. A recent study (Sanchez Vicarte et al., ISCA 2021) suggests that these optimizations might open the Pandora's box of microarchitectural attacks. However, there is little guidance on how to evaluate the security impact of future optimization proposals. To help chip vendors explore the impact of microarchitectural optimizations on cryptographic implementations, we develop (i) an expressive domain-specific language, called LmSpec, that allows them to specify the leakage model for the given optimization and (ii) a testing framework, called LmTest, to automatically detect leaks under the specified leakage model within the given implementation. Using this framework, we conduct an empirical study of 18 proposed microarchitectural optimizations on 25 implementations of eight cryptographic primitives in five popular libraries. We find that every implementation would contain secret-dependent leaks, sometimes sufficient to recover a victim's secret key, if these optimizations were realized. Ironically, some leaks are possible only because of coding idioms used to prevent leaks under the standard constant-time model.

Over the past few years, the high-end CPU market is undergoing a transformational change. Moving away from using x86 as the sole architecture for high performance devices, we have witnessed the introduction of heavy-weight Arm CPUs computing devices. Among these, perhaps the most influential was the introduction of Apple's M-series architecture, aimed at completely replacing Intel CPUs in the Apple ecosystem. However, while significant effort has been invested analyzing x86 CPUs, the Apple ecosystem remains largely unexplored. In this paper, we set out to investigate the resilience of the Apple ecosystem to speculative side-channel attacks. We first establish the basic toolkit needed for mounting side-channel attacks, such as the structure of caches and CPU speculation depth. We then tackle Apple's degradation of the timer resolution in both native and browser-based code. Remarkably, we show that distinguishing cache misses from cache hits can be done without time measurements, replacing timing based primitives with timerless counterparts based on race conditions. Finally, we use our distinguishing primitive to construct eviction sets and mount Spectre attacks, all while avoiding the use of timers. We then evaluate Safari's side-channel resilience. We bypass the compressed 35-bit addressing and the value poisoning countermeasures, creating a primitive that can speculatively read and leak any 64-bit address within Safari's rendering process. Combining this with a new method for consolidating websites from different domains into the same renderer process, we demonstrate end-to-end attacks leaking sensitive information, such as passwords, inbox content, and locations from popular services such as Google.

Although power LEDs have been integrated in various devices that perform cryptographic operations for decades, the cryptanalysis risk they pose has not yet been investigated. In this paper, we present optical cryptanalysis, a new form of cryptanalytic side-channel attack, in which secret keys are extracted by using a photodiode to measure the light emitted by a device's power LED and analyzing subtle fluctuations in the light intensity during cryptographic operations. We analyze the optical leakage of power LEDs of various consumer devices and the factors that affect the optical SNR. We then demonstrate end-to-end optical cryptanalytic attacks against a range of consumer devices (smartphone, smartcard, and Raspberry Pi, along with their USB peripherals) and recover secret keys (RSA, ECDSA, SIKE) from prior and recent versions of popular cryptographic libraries (GnuPG, Libgcrypt, PQCrypto-SIDH) from a maximum distance of 25 meters.

Over the last two decades, the danger of sharing resources between programs has been repeatedly highlighted. Multiple side-channel attacks, which seek to exploit shared components for leaking information, have been devised, mostly targeting shared caching components. In response, the research community has proposed multiple cache designs that aim at curbing the source of side channels. With multiple competing designs, there is a need for assessing the level of security against side-channel attacks that each design offers. Several metrics have been suggested for performing such evaluations. However, these tend to be limited both in terms of the potential adversaries they consider and in the applicability of the metric to real-world attacks, as opposed to attack techniques. Moreover, all existing metrics implicitly assume that a single metric can encompass the nuances of side-channel security. In this work we propose CacheFX, a flexible framework for assessing and evaluating the resilience of cache designs to side-channel attacks. CacheFX allows the evaluator to implement various cache designs, victims, and attackers, as well as to exercise them for assessing the leakage of information via the cache. To demonstrate the power of CacheFX, we implement multiple cache designs and replacement algorithms, and devise three evaluation metrics that measure different aspects of the caches: (1) the entropy induced by a memory access; (2) the complexity of building an eviction set; (3) protection against cryptographic attacks; Our experiments highlight that different security metrics give different insights to designs, making a comprehensive analysis mandatory. For instance, while eviction-set building was fastest for randomized skewed caches, these caches featured lower eviction entropy and higher practical attack complexity. Our experiments show that all non-partitioned designs allow for effective cryptographic attacks. However, in state-of-the-art secure caches, eviction-based attacks are more difficult to mount than occupancy-based attacks, highlighting the need to consider the latter in cache design.