The introduction of blockchain technology has brought about significant changes in different industries, with smart contracts playing a crucial role in decentralized apps (dApps). Self-executing contracts, which include an agreement's terms, enable, verify, and enforce contract negotiation or execution without the involvement of intermediaries. Smart contracts, despite their promise, have brought forth a new set of security concerns, making their security a matter of utmost importance. The purpose of this survey is to offer a thorough assessment of the existing condition of smart contract security, emphasizing common weaknesses, methods of attack, and measures for prevention and reduction of risk. The survey initially explores the architectural and operational features of smart contracts, specifically focusing on their application on blockchain platforms such as Ethereum. We methodically classify and examine prevalent vulnerabilities, such as reentrancy attacks, integer overflow and underflow, and unchecked call return values. We illustrate each category with real-world examples, highlighting the potential consequences of these vulnerabilities [4, 5]. Next, we scrutinize various security strategies and tools developed to address these vulnerabilities. We are evaluating the usefulness of static analysis, formal verification, and symbolic execution in discovering and mitigating security issues [6, 8]. In addition, we assess the impact of automated tools like Mythril, Oyente, and Slither, in conjunction with manual auditing procedures, on improving the security of smart contracts [7]. The survey explores current progress in the creation of safe smart contracts, focusing on best practices in secure coding, deployment, and the incorporation of strong security frameworks [9]. We highlight the significance of thorough security audits and the use of industry standards to enhance the security stance of smart contracts [3]. Ultimately, the survey highlights developing patterns and areas for future investigation in the realm of smart contract security. New programming languages designed to prioritize security are being made, machine learning techniques are being used to find outliers, and quantum-resistant algorithms are being looked into to protect smart contracts from future flaws [10]. This study seeks to consolidate current knowledge and identify areas of research that require further investigation. Its purpose is to serve as a helpful reference for researchers, developers, and security practitioners. The primary goal is to cultivate a deeper understanding of smart contract security and advance the creation of decentralized systems that are more safe and robust.