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Harshvadan Mihir

Publications and source records attributed to Harshvadan Mihir.

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CRAFT: Characterizing and Root-Causing Fault Injection Threats at Pre-Silicon

Fault injection attacks (FIA) pose significant security threats to embedded systems as they exploit weaknesses across multiple layers, including system software, instruction set architecture (ISA), microarchitecture, and physical hardware. Early detection and understanding of how physical faults propagate to system-level behavior are essential to safeguarding cyberinfrastructure. This work introduces CRAFT, a framework that combines pre-silicon analysis with post-silicon validation to systematically uncover and analyze fault injection vulnerabilities. Our study, conducted on a RISC-V soft-core processor (cv32e40x) reveals two novel vulnerabilities. First, we demonstrate a method to induce instruction skips by glitching the clock (single-glitch attack), which prevents critical values from being loaded from memory, thus disrupting program execution. Second, we show a technique that converts a fetched legal instruction into an illegal one mid-execution, diverting control flow in a manner exploitable by attackers. Notably, we identified a specific timing window in which the processor fails to detect these illegal control-flow diversions, allowing silent, undetected corruption of the program state. By simulating 9248 FIA scenarios at pre-silicon and conducting root-cause analysis of the RISC-V pipeline, we trace the faults to a previously unreported vulnerability in a pipeline register shared between the instruction fetch and decode stages. Our approach reduced the search space for post-silicon experiments by 97.31%, showing pre-silicon advantages for post-silicon testing. Finally, we validate our identified exploit cases on real hardware (FPGA).

cs.CR

Honest to a Fault: Root-Causing Fault Attacks with Pre-Silicon RISC Pipeline Characterization

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 present 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 a novel vulnerability through controlled clock glitch parameters, specifically targeting the RISC-V decode stage.

cs.CR