ZKScan
Static analysis for on-chain zero-knowledge verifiers
Anik Tahabilder, M M Imran, Changxin Bai, Qiang Zhu, Shiyong Lu
IEEE 4th International Conference on Artificial Intelligence, Blockchain and Internet of Things (AIBThings), 2026. Accepted.
Problem
An application relies on its verifier contract to reject invalid proofs. Verifier-specific mistakes can sit outside the focus of both circuit analyzers and general smart-contract vulnerability tools.
Approach
ZKScan organizes ten detection rules into five vulnerability classes for Groth16, PLONK, and FFLONK verifiers. Intraprocedural Yul dataflow tracks precompile return values to reduce alerts caused by checks that occur later in the code.
Research contribution
A set of vulnerability classes specific to verifier contracts, a static analyzer that checks for them, and an evaluation on synthetic, audit-derived, and mainnet contracts.
Authorship
Coauthor with Anik Tahabilder (first author), Changxin Bai, Qiang Zhu, and Shiyong Lu.
Evaluation evidence
The paper evaluates 74 contracts across three datasets. On the 20-contract audit-derived dataset, it reports 94% recall (17/18) and 77% precision (17/22). Ground-truth findings are concentrated in a small set of contracts, and the paper reports uncertainty intervals. Raw alerts on mainnet contracts are signals for review, not verified exploits.
Scope & limitations
The evaluation uses historical contract versions and does not claim active zero-day vulnerabilities. Rule-based analysis has limited coverage beyond its supported patterns and cannot establish complete verifier correctness or resolve trusted-setup governance issues from code alone.
Citation
Anik Tahabilder, M M Imran, Changxin Bai, Qiang Zhu, Shiyong Lu. “ZKScan: A Static Analyzer for Smart Contract Based Zero-Knowledge Proof Verifiers on Blockchains.” IEEE 4th International Conference on Artificial Intelligence, Blockchain and Internet of Things (AIBThings), 2026. Accepted.
BibTeX
@inproceedings{zkscan2026,
title = {ZKScan: A Static Analyzer for Smart Contract Based Zero-Knowledge Proof Verifiers on Blockchains},
author = {Anik Tahabilder and M M Imran and Changxin Bai and Qiang Zhu and Shiyong Lu},
booktitle = {IEEE 4th International Conference on Artificial Intelligence, Blockchain and Internet of Things (AIBThings)},
year = {2026},
note = {Accepted},
}Contact
If you'd like to talk about a research collaboration, a faculty position, or an industry research role in blockchain security, email me.
mmimran@wayne.edu