Assessing the Effectiveness of Binary-Level CFI Techniques
CoRR(2024)
Abstract
Memory corruption is an important class of vulnerability that can be
leveraged to craft control flow hijacking attacks. Control Flow Integrity (CFI)
provides protection against such attacks. Application of type-based CFI
policies requires information regarding the number and type of function
arguments. Binary-level type recovery is inherently speculative, which
motivates the need for an evaluation framework to assess the effectiveness of
binary-level CFI techniques compared with their source-level counterparts,
where such type information is fully and accurately accessible. In this work,
we develop a novel, generalized and extensible framework to assess how the
program analysis information we get from state-of-the-art binary analysis tools
affects the efficacy of type-based CFI techniques. We introduce new and
insightful metrics to quantitatively compare source independent CFI policies
with their ground truth source aware counterparts. We leverage our framework to
evaluate binary-level CFI policies implemented using program analysis
information extracted from the IDA Pro binary analyzer and compared with the
ground truth information obtained from the LLVM compiler, and present our
observations.
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