DATA – Differential Address Trace Analysis: Finding Address-based Side-Channels in Binaries


Samuel Weiser, Graz University of Technology; Andreas Zankl, Fraunhofer AISEC; Raphael Spreitzer, Graz University of Technology; Katja Miller, Fraunhofer AISEC; Stefan Mangard, Graz University of Technology; Georg Sigl, Fraunhofer AISEC and Technical University of Munich


Cryptographic implementations are a valuable target for address-based side-channel attacks and should, thus, be protected against them. Countermeasures, however, are often incorrectly deployed or completely omitted in practice. Moreover, existing tools that identify information leaks in programs either suffer from imprecise abstraction or only cover a subset of possible leaks. We systematically address these limitations and propose a new methodology to test software for information leaks.

In this work, we present DATA, a differential address trace analysis framework that detects address-based side-channel leaks in program binaries. This accounts for attacks exploiting caches, DRAM, branch prediction, controlled channels, and likewise. DATA works in three phases. First, the program under test is executed to record several address traces. These traces are analyzed using a novel algorithm that dynamically re-aligns traces to increase detection accuracy. Second, a generic leakage test filters differences caused by statistically independent program behavior, e.g., randomization, and reveals true information leaks. The third phase classifies these leaks according to the information that can be obtained from them. This provides further insight to security analysts about the risk they pose in practice.

We use DATA to analyze OpenSSL and PyCrypto in a fully automated way. Among several expected leaks in symmetric ciphers, DATA also reveals known and previously unknown leaks in asymmetric primitives (RSA, DSA, ECDSA), and DATA identifies erroneous bug fixes of supposedly fixed constant-time vulnerabilities.

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@inproceedings {217537,
author = {Samuel Weiser and Andreas Zankl and Raphael Spreitzer and Katja Miller and Stefan Mangard and Georg Sigl},
title = {{DATA} {\textendash} Differential Address Trace Analysis: Finding Address-based Side-Channels in Binaries},
booktitle = {27th {USENIX} Security Symposium ({USENIX} Security 18)},
year = {2018},
isbn = {978-1-931971-46-1},
address = {Baltimore, MD},
pages = {603--620},
url = {},
publisher = {{USENIX} Association},