In this project, I explore a simple method for detecting blockchain scams through profiling smart contract code. By identifying repeated patterns in malicious smart contracts, I systematically group similar contracts into "code families," making it easier to spot frequent vulnerabilities and fraudulent activities. My early tests successfully identified multiple malicious contracts with clear vulnerabilities, highlighting the effectiveness of this profiling approach in enhancing blockchain security. Looking ahead, I plan to integrate advanced predictive techniques and enhance processing efficiency to further protect users from blockchain scams.