International Association
for Cryptologic Research

With the growing prevalence of software-based cryptographic implementations in high-level languages, understanding the role of architectural and micro-architectural components in side-channel security is critical. The role of compilers in case of software implementations towards contribution to side-channel leaks is not investigated. While timing-based side-channel leakage due to compiler effects has been extensively studied, the impact of compiler optimizations on power-based leakage remains underexplored, primarily due to challenges in isolating the architectural power component. In this work, we present ARCHER, an architecture-level tool for side-channel analysis and root cause identification of cryptographic software on RISC-V processors. ARCHER integrates two key functionalities: (1) Side-Channel Analysis using TVLA and its variants to detect leakage, and (2) Data Flow Analysis to track intermediate values and explain observed leaks. ARCHER supports pre-silicon analysis of high-level and assembly code, offering algorithm-agnostic insights through interactive visualizations and detailed reports on execution statistics, leakage points, and their causes. Using ARCHER, we analyze binary transformations across five optimization levels (-O0, -O1, -O2, -O3, -Os) to isolate the architectural effects of compiler optimizations from the micro-architectural influences of the target device. This study, spanning both unprotected and masked AES implementations, reveals actionable insights into how optimizations affect power-based leakage. Notably, we identify a previously undocumented vulnerability in the ShiftRow operation of masked AES, introduced by compiler optimizations. This vulnerability, confirmed through correlation analysis on simulated power traces, is validated on physical hardware using an ASIC implementation of the PicoRV32 core, confirming that architectural-level vulnerabilities translate to real-world leakage. To enhance practical applicability, we introduce two dataflow metrics, remanence and revive, for predicting side-channel leakage based on binary transformations. These metrics, coupled with ARCHER’s analysis and visualization capabilities, provide designers with effective tools to assess and mitigate power-based side-channel vulnerabilities at the software optimization stage, advancing the security of cryptographic implementations in resource-constrained environments.