Tommaso Frassetto (Technical University of Darmstadt), Patrick Jauernig (Technical University of Darmstadt), David Koisser (Technical University of Darmstadt), Ahmad-Reza Sadeghi (Technical University of Darmstadt)

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 BlockInsulation and CFGInsulation, 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 BlockInsulation, CFGInsulation, and existing metrics. Lastly, we describe l+tCFI, our implementation that combines NumCFI and an existing label-based policy, with a performance overhead of just 1.27%.

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Ioanna Tzialla (New York University), Abhiram Kothapalli (Carnegie Mellon University), Bryan Parno (Carnegie Mellon University), Srinath Setty (Microsoft Research)

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Jianfeng Li (The Hong Kong Polytechnic University), Shuohan Wu (The Hong Kong Polytechnic University), Hao Zhou (The Hong Kong Polytechnic University), Xiapu Luo (The Hong Kong Polytechnic University), Ting Wang (Penn State), Yangyang Liu (The Hong Kong Polytechnic University), Xiaobo Ma (Xi'an Jiaotong University)

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Zifeng Kang (Johns Hopkins University), Song Li (Johns Hopkins University), Yinzhi Cao (Johns Hopkins University)

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