Litcius/Paper detail

Plundervolt: Software-based Fault Injection Attacks against Intel SGX

Kit Murdock, David Oswald, Flavio D. Garcia, J. Bulck, Daniel Gruss, F. Piessens

2020Zenodo (CERN European Organization for Nuclear Research)32 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

Fault injectionOperating systemComputer scienceSoftwareFault (geology)Embedded systemGeologySeismologyPhysical Unclonable Functions (PUFs) and Hardware SecuritySecurity and Verification in ComputingAdvanced Malware Detection Techniques