MicroWalk: A Framework for Finding Side Channels in Binaries

TL;DR

MicroWalk is a new framework that uses dynamic binary analysis and mutual information to detect microarchitectural side-channel leakages in binaries, even without source code, demonstrated on cryptographic libraries.

Contribution

We introduce MicroWalk, a novel framework combining dynamic binary instrumentation and mutual information analysis for automated leakage detection in binaries.

Findings

Identified previously unknown leakages in cryptographic libraries.

Analyzed 15 implementations with 112 million instructions in 105 minutes.

Demonstrated effectiveness in locating microarchitectural leakages.

Abstract

Microarchitectural side channels expose unprotected software to information leakage attacks where a software adversary is able to track runtime behavior of a benign process and steal secrets such as cryptographic keys. As suggested by incremental software patches for the RSA algorithm against variants of side-channel attacks within different versions of cryptographic libraries, protecting security-critical algorithms against side channels is an intricate task. Software protections avoid leakages by operating in constant time with a uniform resource usage pattern independent of the processed secret. In this respect, automated testing and verification of software binaries for leakage-free behavior is of importance, particularly when the source code is not available. In this work, we propose a novel technique based on Dynamic Binary Instrumentation and Mutual Information Analysis to efficiently locate and quantify memory based and control-flow based microarchitectural leakages. We develop a software framework named \tool~for side-channel analysis of binaries which can be extended to support new classes of leakage. For the first time, by utilizing \tool, we perform rigorous leakage analysis of two widely-used closed-source cryptographic libraries: \emph{Intel IPP} and \emph{Microsoft CNG}. We analyze $15$ different cryptographic implementations consisting of $112$ million instructions in about $105$ minutes of CPU time. By locating previously unknown leakages in hardened implementations, our results suggest that \tool~can efficiently find microarchitectural leakages in software binaries.