Global Journal of Computer Science and Technology, D: Neural & Artificial Intelligence, Volume 23 Issue 2

In this simplified bank smart contract, users can deposit and withdraw Ether from their accounts. The contract also has a function called ‘toggleLock’, which allows the contract owner to lock or unlock the contract to prevent further deposits and withdrawals. The re-entrancy vulnerability exists in the ‘withdraw’ function. Here's how it can be exploited. 1. An attacker deploys a malicious contract with a `fallback` function that performs a reentrant call to the `withdraw` function of the ‘SimpleBank’ contract 2. The attacker then calls the ‘startAttack’ function of the ‘MaliciousContract,’ initiating the reentrancy attack. 3. The `withdraw` function of the ‘SimpleBank’ contract transfers ‘1’ ether to the attacker's contract. However, before the `withdraw` function completes its execution, the fallback function of the attacker's contract is triggered again due to the reentrancy call. 4. The re-entrant fallback function continues to call the `withdraw` function of the `SimpleBank` contract, resulting in multiple withdrawals of 1 ether each, even though the attacker's balance in the `SimpleBank` contract is already zero. Prevention Artificial Intelligence (AI) holds the potential to enhance the security of smart contracts by identifying and mitigating reentrancy vulnerabilities. One approach involves utilizing AI-powered tools to detect such vulnerabilities in smart contracts at the EVM bytecode level. Researchers have examined a large dataset of real-world smart contracts, allowing them to identify patterns of false positives and design effective path filters to eliminate them. Another approach employs AI- based fuzz testing to automatically generate inputs that simulate attacks on smart contracts. Subsequently, the execution logs are analyzed to determine the presence and intent of any re-entrancy processes. These AI-driven methods contribute to improving the accuracy and efficiency of detecting and preventing reentrancy vulnerabilities in smart contracts. Overflow and Underflow Integer overflow and underflow vulnerabilities pose significant risks in the realm of blockchain-based applications, especially concerning smart contracts responsible for managing value transfers and storing sensitive data. These specific vulnerabilities are a subset of the general vulnerabilities we previously addressed. Smart contracts, being self-executing agreements governed by code, find widespread deployment on blockchain platforms such as Ethereum. A simplified bank smart contract implemented in Solidity with potential integer overflow and underflow vulnerabilities. Global Journal of Computer Science and Technology Volume XXIII Issue II Version I 60 ( ) Year 2023 D Strengthening Smart Contracts: An AI-Driven Security Exploration © 2023 Global Journals ii.