Cache Refinement Type for Side-Channel Detection of Cryptographic Software

TL;DR

This paper introduces CaType, a static analysis tool using refinement types over x86 assembly to detect cache side-channel vulnerabilities in cryptographic software, offering high precision, scalability, and effectiveness.

Contribution

CaType is the first to analyze cache side channels with refinement types on assembly code, considering blinding defenses and using cache layouts to reduce false positives.

Findings

CaType detects all known vulnerabilities in tested crypto software.

CaType finds previously unknown side-channel vulnerabilities.

CaType is significantly faster than existing tools, with 16X and 131X speed improvements.

Abstract

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.