D-Helix: A Generic Decompiler Testing Framework Using Symbolic Differentiation

Muqi Zou, Arslan Khan, Ruoyu Wu, Han Gao, Antonio Bianchi, and Dave (Jing) Tian, Purdue University

Decompilers, one of the widely used security tools, transform low-level binary programs back into their high-level source representations, such as C/C++. While state-of-the-art decompilers try to generate more human-readable outputs, for instance, by eliminating goto statements in their decompiled code, the correctness of a decompilation process is largely ignored due to the complexity of decompilers, e.g., involving hundreds of heuristic rules. As a result, outputs from decompilers are often not accurate, which affects the effectiveness of downstream security tasks.

In this paper, we propose D-HELIX, a generic decompiler testing framework that can automatically vet the decompilation correctness on the function level. D-HELIX uses RECOMPILER to compile the decompiled code at the functional level. It then uses SYMDIFF to compare the symbolic model of the original binary with the one of the decompiled code, detecting potential errors introduced by the decompilation process. D-HELIX further provides TUNER to help debug the incorrect decompilation via toggling decompilation heuristic rules automatically. We evaluated D-HELIX on Ghidra and angr using 2,004 binaries and object files ending up with 93K decompiled functions in total. D-HELIX detected 4,515 incorrectly decompiled functions, reproduced 8 known bugs, found 17 distinct previously unknown bugs within these two decompilers, and fixed 7 bugs automatically.

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