Cache refinement type for side-channel detection of cryptographic software

Cache side-channel attacks exhibit severe threats to software security and privacy, especially for cryptosystems. In this paper, we propose CaType, a novel refinement type-based tool for detecting cache side channels in crypto software. Compared to previous works, CaType provides the following advan...

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Bibliographic Details
Main Authors: Jiang, Ke, Bao, Yuyan, Wang, Shuai, Liu, Zhibo, Zhang, Tianwei
Other Authors: School of Computer Science and Engineering
Format: Conference or Workshop Item
Language:English
Published: 2023
Subjects:
Online Access:https://hdl.handle.net/10356/165415
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Institution: Nanyang Technological University
Language: English
Description
Summary:Cache side-channel attacks exhibit severe threats to software security and privacy, especially for cryptosystems. In this paper, we propose CaType, a novel refinement type-based tool for detecting cache side channels in crypto software. Compared to previous works, CaType provides the following advantages: (1) For the first time CaType analyzes cache side channels using refinement type over x86 assembly code. It reveals several significant and effective enhancements with refined types, including bit-level granularity tracking, distinguishing different effects of variables, precise type inferences, and high scalability. (2) CaType is the first static analyzer for crypto libraries in consideration of blinding-based defenses. (3) From the perspective of implementation, CaType uses cache layouts of potential vulnerable control-flow branches rather than cache states to suppress false positives. We evaluate CaType in identifying side channel vulnerabilities in real-world crypto software, including RSA, ElGamal, and (EC)DSA from OpenSSL and Libgcrypt. CaType captures all known defects, detects previously-unknown vulnerabilities, and reveals several false positives of previous tools. In terms of performance, CaType is 16X faster than CacheD and 131X faster than CacheS when analyzing the same libraries. These evaluation results confirm the capability of CaType in identifying side channel defects with great precision, efficiency, and scalability.