Side-channel robustness analysis of masked assembly codes using a symbolic approach

Masking is a popular countermeasure against side-channel attacks, which randomizes secret data with random and uniform variables called masks. At software level, masking is usually added in the source code and its effectiveness needs to be verified. In this paper, we propose a symbolic method to verify side-channel robustness of masked programs. The analysis is performed at the assembly level since compilation and optimizations may alter the added protections. Our proposed method aims to verify that intermediate computations are statistically independent from secret variables using defined distribution inference rules. We verify the first round of a masked AES in 22 s and show that some secure algorithms or source codes are not leakage-free in their assembly implementations.