Enhancing Smart Contract Security Through DevSecOps: An Adaptive Approach for Vulnerability Detection

Abstract

Smart contracts are central to decentralized applications but are often vulnerable to security flaws, both during development and in deployment. Due to their immutable nature, any vulnerabilities introduced are permanent and exploitable, highlighting the need for a secure, structured development lifecycle. This study proposes an adaptive DevSecOps approach tailored to blockchain applications, drawing on established practices and gray literature. By embedding security into Continuous Integration and Continuous Delivery (CI/CD), the model ensures continuous protection from development through deployment. At its core is an adaptive cognitive security framework that automates vulnerability detection using techniques like static analysis, fuzzing, and symbolic execution. It also streamlines secure provisioning across various environments. To further enhance security, Agentic AI is integrated into the pipeline. These autonomous agents monitor code, infrastructure, and behavior in real-time, learning from past incidents, detecting threats, applying patches, and adapting CI/CD workflows dynamically. Experimental results validate the model’s effectiveness, showing significant improvements in the security and reliability of smart contracts. This approach offers a scalable, proactive solution for securing blockchain systems in a rapidly evolving threat landscape.