Towards Automatic Exploit Generation for Identifying Re-Entrancy Attacks on Cross-Contract

Abstract

The core of Ethereum is a smart contract, which enables developers to create blockchain-based applications in a secure and inexpensive manner. Everyone has access to the source code of Ethereum-based smart contracts. The smart contract has become a target for numerous attackers due to its transparency. Since 2015, when the first Ethereum block was discovered, many security incidents have occurred. Several code analysis methods have been developed for detecting the re-entrancy vulnerability of smart contracts. However, Existing strategies for detecting cross-contract vulnerability tend to experience both false negative and false positive results. To enhance the re-entrancy detection technique of existing works, we propose a challenge to enhance re-entrancy detection technique for Ethereum blockchain smart cross-contract. We proposed multi-agent deep reinforcement learning fuzzing to provide an exploit generator on cross-contract. We will discover a novel solution for enhancing re-entrancy detection techniques for cross-contract by integrating all these systems.