Smart Contracts and Security: A Comprehensive Survey of Vulnerabilities, Detection Techniques, and Mitigation Strategies

Abstract

Smart contracts are autonomous programs executed on blockchain platforms such as Ethereum. They facilitate the development of decentralized applications but also introduce significant risks. Since the code of a deployed smart contract is immutable and often controls valuable digital assets, any security vulnerability can lead to severe and irreversible consequences. This paper presents a comprehensive survey of smart-contract vulnerability detection systems, synthesizing findings from over 108 tools across static analysis, formal verification, dynamic fuzzing, machine learning, symbolic execution, and runtime monitoring. A vulnerability taxonomy is organized spanning coding, design, and environmental weaknesses (e.g., reentrancy, arithmetic errors, access-control faults, timestamp dependence, and misuse of pseudo-randomness). Rather than conducting new empirical evaluations, this survey synthesizes performance metrics reported in the literature and proposes a KPI-based framework for comparing tools. However, direct quantitative comparisons are limited by heterogeneous evaluation contexts, datasets, and tool versions across studies. Techniques are contextualized with real attack exemplars, tool capabilities are summarized, and trade-offs among accuracy, scalability, and coverage are highlighted. Open challenges are identified—including compositional reasoning for multi-contract interactions, uncovering businesslogic errors, and balancing precision with throughput—and design guidance is distilled for practitioners. Overall, while detection capabilities have improved substantially, securing smart contracts remains an active frontier that calls for hybrid, multilayer defenses and continuous innovation.