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NDSS2022顶会

CFInsight: A Comprehensive Metric for CFI Policies

Tommaso Frassetto, Patrick Jauernig, David Koisser, Ahmad-Reza Sadeghi

出版方
2022年份
4顶会引用

摘要

—Software vulnerabilities are one of the major threats to computer security and have caused substantial damage over the past decades. Consequently, numerous techniques have been proposed to mitigate the risk of exploitation of vulnerable programs. One of the most relevant defense mechanisms is Control-Flow Integrity (CFI): multiple variants have been introduced and extensively discussed in academia as well as deployed in the industry. However, it is hard to compare the security guarantees of these implementations as existing metrics (such as AIR) do not consider the different usefulness to the attacker of different basic blocks, which are the fundamental components that constitute the code of any application. This paper introduces B LOCK I NSULATION and CFGI NSU - LATION , novel metrics designed to overcome this limitation by modeling the usefulness of basic blocks for an attacker trying to traverse the program’s control-flow graph. Moreover, we propose a new CFI policy generator, named NumCFI, which is orthogonal to existing policy generators and prevents the attacker from taking shortcuts from vulnerable code to a system call instruction. We evaluate NumCFI, as well as a number of other CFI policy generators, using B LOCK I NSULATION , CFGI NSULATION , and existing metrics. Lastly, we describe L + T CFI, our implementation that combines NumCFI and an existing label-based policy, with a performance overhead of just 1.27%.

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