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Dynamic frequency and voltage scaling features have been introduced to manage ever-growing heat and power consumption in modern processors. Design restrictions ensure frequency and voltage are adjusted as a pair, based on the current load, because for each frequency there is only a certain voltage range where the processor can operate correctly. For this purpose, many processors (including the widespread Intel Core series) expose privileged software interfaces to dynamically regulate processor frequency and operating voltage. In this paper, we demonstrate that these privileged interfaces can be reliably exploited to undermine the system’s security. We present the Plundervolt attack, in which a privileged software adversary abuses an undocumented Intel Core voltage scaling interface to corrupt the integrity of Intel SGX enclave computations. Plundervolt carefully controls the processor’s supply voltage during an enclave computation, inducing predictable faults within the processor package. Consequently, even Intel SGX’s memory encryption/authentication technology cannot protect against Plundervolt. In multiple case studies, we show how the induced faults in enclave computations can be leveraged in real-world attacks to recover keys from cryptographic algorithms (including the AES-NI instruction set extension) or to induce memory safety vulnerabilities into bug-free enclave code. We finally discuss why mitigating Plundervolt is not trivial, requiring trusted computing base recovery through microcode updates or hardware changes.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 157 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
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