Levi Taiji Li (University of Utah), Ningyu He (Peking University), Haoyu Wang (Huazhong University of Science and Technology), Mu Zhang (University of Utah)

In this paper, we propose VETEOS, a static vetting tool for the "Groundhog Day" vulnerabilities in EOSIO contracts. In a "Groundhog Day" attack, culprits leverage the distinctive rollback issue in EOSIO contracts, which allows them to persistently execute identical contract code with varying inputs. By using the information exposed in prior executions, these attackers unlawfully amass insights about the target contract, thereby figuring out a reliable method to generate unauthorized profits. To tackle this problem, we formally define this unique vulnerability as a control and data dependency problem, and develop a custom static analysis tool, VETEOS, that can precisely discover such bugs directly from EOSIO WebAssembly (WASM) bytecode. VETEOS has detected 735 new vulnerabilities in the wild and outperforms the state-of-the-art EOSIO contract analyzer.

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Hao Zhou (The Hong Kong Polytechnic University), Shuohan Wu (The Hong Kong Polytechnic University), Chenxiong Qian (University of Hong Kong), Xiapu Luo (The Hong Kong Polytechnic University), Haipeng Cai (Washington State University), Chao Zhang (Tsinghua University)

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ShapFuzz: Efficient Fuzzing via Shapley-Guided Byte Selection

Kunpeng Zhang (Shenzhen International Graduate School, Tsinghua University), Xiaogang Zhu (Swinburne University of Technology), Xi Xiao (Shenzhen International Graduate School, Tsinghua University), Minhui Xue (CSIRO's Data61), Chao Zhang (Tsinghua University), Sheng Wen (Swinburne University of Technology)

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ORL-AUDITOR: Dataset Auditing in Offline Deep Reinforcement Learning

Linkang Du (Zhejiang University), Min Chen (CISPA Helmholtz Center for Information Security), Mingyang Sun (Zhejiang University), Shouling Ji (Zhejiang University), Peng Cheng (Zhejiang University), Jiming Chen (Zhejiang University), Zhikun Zhang (CISPA Helmholtz Center for Information Security and Stanford University)

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