CacheD: Identifying Cache-Based Timing Channels in Production Software

Side-channel attacks recover secret information by analyzing the physical implementation of cryptosystems based on non-functional computational characteristics, e.g. time, power, and memory usage. Among all wellknown side channels, cache-based timing channels are notoriously severe, leading to practical attacks against certain implementations of theoretically secure crypto algorithms, such as RSA, ElGamal and AES. Such attacks target the hierarchical design of the modern computer memory system, where different memory access patterns of a program can bring observable timing difference. In this work, we propose a novel technique to help software developers identify potential vulnerabilities that can lead to cache-based timing attacks. Our technique leverages symbolic execution and constraint solving to detect potential cache differences at each program point. We adopt a cache model that is general enough to capture various threat models that are employed in practical timing attacks. Our modeling and analysis are based on the formulation of cache access at different program locations along execution traces. We have implemented the proposed technique as a practical tool named CacheD (Cache Difference), and evaluated CacheD towards multiple real-world cryptosystems. CacheD takes less than 17 CPU hours to analyze 9 widely used cryptographic algorithm implementations with over 120 million instructions in total. The evaluation results show that our technique can accurately identify vulnerabilities reported by previous research. Moreover, we have successfully discovered previously unknown issues in two widely used cryptosystems, OpenSSL and Botan.