CONFIRM: Evaluating Compatibility and Relevance of Control-flow Integrity Protections for Modern Software

Xiaoyang Xu, Masoud Ghaffarinia, Wenhao Wang, Kevin W. Hamlen, Zhiqiang Lin
2019 USENIX Security Symposium  
CONFIRM (CONtrol-Flow Integrity Relevance Metrics) is a new evaluation methodology and microbenchmarking suite for assessing compatibility, applicability, and relevance of control-flow integrity (CFI) protections for preserving the intended semantics of software while protecting it from abuse. Although CFI has become a mainstay of protecting certain classes of software from code-reuse attacks, and continues to be improved by ongoing research, its ability to preserve intended program
more » ... ies (semantic transparency) of diverse, mainstream software products has been under-studied in the literature. This is in part because although CFI solutions are evaluated in terms of performance and security, there remains no standard regimen for assessing compatibility. Researchers must often therefore resort to anecdotal assessments, consisting of tests on homogeneous software collections with limited variety (e.g., GNU Coreutils), or on CPU benchmarks (e.g., SPEC) whose limited code features are not representative of large, mainstream software products. Reevaluation of CFI solutions using CONFIRM reveals that there remain significant unsolved challenges in securing many large classes of software products with CFI, including software for market-dominant OSes (e.g., Windows) and code employing certain ubiquitous coding idioms (e.g., eventdriven callbacks and exceptions). An estimated 47% of CFIrelevant code features with high compatibility impact remain incompletely supported by existing CFI algorithms, or receive weakened controls that leave prevalent threats unaddressed (e.g., return-oriented programming attacks). Discussion of these open problems highlights issues that future research must address to bridge these important gaps between CFI theory and practice.
dblp:conf/uss/XuGWHL19 fatcat:cosrdv25rbeyrbjneyj4h5yfd4