Fault injection attacks represent a class of threats that can compromise embedded systems across multiple layers of abstraction, such as system software, instruction set architecture (ISA), microarchitecture, and physical implementation. Early detection of these vulnerabilities and understanding their root causes, along with their propagation from the physical layer to the system software, is critical to secure the cyberinfrastructure. This work presents a comprehensive methodology for conducting controlled fault injection attacks at the pre-silicon level and an analysis of the underlying system for root-causing behavior. As the driving application, we use the clock glitch attacks in AI/ML applications for critical misclassification. Our study aims to characterize and diagnose the impact of faults within the RISC-V instruction set and pipeline stages, while tracing fault propagation from the circuit level to the AI/ML application software. This analysis resulted in discovering two new vulnerabilities through controlled clock glitch parameters. First, we reveal a novel method for causing instruction skips, thereby preventing the loading of critical values from memory. This can cause disruption and affect program continuity and correctness. Second, we demonstrate an attack that converts legal instructions into illegal ones, thereby diverting control flow in a manner exploitable by attackers. Our work underscores the complexity of fault injection attack exploits and emphasizes the importance of preemptive security analysis.
View on arXiv@article{malik2025_2503.03877,
title={ CRAFT: Characterizing and Root-Causing Fault Injection Threats at Pre-Silicon },
author={ Arsalan Ali Malik and Harshvadan Mihir and Aydin Aysu },
journal={arXiv preprint arXiv:2503.03877},
year={ 2025 }
}