Dongwei Xiao (The Hong Kong University of Science and Technology), Zhibo Liu (The Hong Kong University of Science and Technology), Yiteng Peng (The Hong Kong University of Science and Technology), Shuai Wang (The Hong Kong University of Science and Technology)

Zero-knowledge (ZK) proofs have been increasingly popular in privacy-preserving applications and blockchain systems. To facilitate handy and efficient ZK proof generation for normal users, the industry has designed domain-specific languages (DSLs) and ZK compilers. Given a program in ZK DSL, a ZK compiler compiles it into a circuit, which is then passed to the prover and verifier for ZK checking. However, the correctness of ZK compilers is not well studied, and recent works have shown that de facto ZK compilers are buggy, which can allow malicious users to generate invalid proofs that are accepted by the verifier, causing security breaches and financial losses in cryptocurrency.

In this paper, we propose MTZK, a metamorphic testing framework to test ZK compilers and uncover incorrect compilations. Our approach leverages deliberately designed metamorphic relations (MRs) to mutate ZK compiler inputs. This way, ZK compilers can be automatically tested for compilation correctness using inputs and mutated variants. We propose a set of design considerations and optimizations to deliver an efficient and effective testing framework. In the evaluation of four industrial ZK compilers, we successfully uncovered 21 bugs, out of which the developers have promptly patched 15. We also show possible exploitations of the uncovered bugs to demonstrate their severe security implications.

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Jacob Hopkins (Texas A&M University - Corpus Christi), Carlos Rubio-Medrano (Texas A&M University - Corpus Christi), Cori Faklaris (University of North Carolina at Charlotte)

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Jiayi Lin (The University of Hong Kong), Qingyu Zhang (The University of Hong Kong), Junzhe Li (The University of Hong Kong), Chenxin Sun (The University of Hong Kong), Hao Zhou (The Hong Kong Polytechnic University), Changhua Luo (The University of Hong Kong), Chenxiong Qian (The University of Hong Kong)

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Weili Wang (Southern University of Science and Technology), Honghan Ji (ByteDance Inc.), Peixuan He (ByteDance Inc.), Yao Zhang (ByteDance Inc.), Ye Wu (ByteDance Inc.), Yinqian Zhang (Southern University of Science and Technology)

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