SoCFuzzer: SoC Vulnerability Detection using Cost Function enabled Fuzz Testing

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Abstract

The modern System-on-Chips (SoCs), with numerous complex and heterogeneous intellectual properties (IPs), and the inclusion of highly-sensitive assets, become the target of malicious attacks. However, security verification of these SoCs remains behind compared to the advances in functional verification, mostly because it is difficult to formally define the accurate threat model(s). Few recent studies have investigated the possibility of engaging fuzz testing for hardware-oriented vulnerability detection. However, they suffer from several limitations, i.e., lack of cross-layer co-verification, the need for expert knowledge, and the inability to capture detailed hardware interactions. In this paper, we propose SoCFuzzer, an automated SoC verification assisted by fuzz testing for detecting SoC security vulnerabilities. Unlike the previous HW-oriented fuzz testing studies, which mostly rely on traditional (code) coverage-based metrics, in SoCFuzzer, we develop (i) generic evaluation metrics for fuzzing the hardware domain, and (ii) security-oriented cost function. This relieves designers of making correlations between coverage metrics, test data, and possible vulnerabilities. The SoCFuzzer cost functions are defined high level, allowing us to follow the gray-box model, which requires less detailed and interactive information from the design-under-test. Our experiments on an open-source RISCV based SoC show the efficiency of these metrics and cost functions on fuzzing for generating cornerstone inputs to trigger the vulnerability conditions with faster convergence.