Prescriptive Safety-Checks through Automated Proofs for Control-Flow Integrity
Carnegie Mellon University Electrical and Computer Engineering PhD Dissertation, November 2016.
Electrical and Computer Engineering
Carnegie Mellon University
Pittsburgh, PA 15213
Embedded software today is pervasive: they can be found everywhere, from coffee makers and medical devices, to cars and aircraft. Embedded software today is also open and connected to the Internet, exposing them to external attacks that can cause its Control-Flow Integrity (CFI) to be violated. Control-Flow Integrity is an important safety property of software, which ensures that the behavior of the software is not inadvertently changed. The violation of CFI in software can cause unintended behaviors, and can even lead to catastrophic incidents in safety-critical systems.
This dissertation develops a two-part approach for CFI: (i) prescribing source-code safetychecks, that prevent the root-causes of CFI, that programmers can insert themselves, and (ii) formally proving CFI for the machine-code of programs with source-code safety-checks. First, our prescribed safety-checks, when applied, prevent the root-causes of CFI, thereby enabling software to recover from CFI violations in a customizable way. In addition, our prescribed safety-checks are visible to programmers, empowering them to ensure that the behavior of their software is not inadvertently changed by the prescribed safety-checks. However, programmer-inserted safety-checks may be incomplete. Thus, current techniques for proving CFI, which assume that safety-checks are complete, may not work. Second, this dissertation develops a logic approach that automates formal proofs of CFI for the machine-code of software containing both source-code CFI safety-checks and system calls. We extend an existing trustworthy Hoare logic with new proof rules, proof tactics, and a novel proof-search algorithm, which exploit the principle of local reasoning for safety properties to automatically generate CFI proofs for the machine-code of programs compiled with our prescribed source-code safety-checks.
To the best of our knowledge, our approach to CFI is the first to combine programmer-visible source-code enforcement mechanisms for CFI–enabling programmers to customize them and observe that their software is not inadvertently changed–with machine-code proofs of CFI that can be automated, and that does not require a trusted or verified compiler to ensure its proven properties hold in machine-code.
We evaluate our CFI approach on realistic embedded software. We evaluate our approach on the MiBench and WCET benchmarks, implementations of common file utilities, and programs interfacing with hardware inputs and outputs on the Raspberry Pi single-board-computer. The variety of our target programs, and our ability to support useful features such as file and hardware inputs and outputs, demonstrate the wide applicability of our approach.
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