AI Empowered DevSecOps Security for Next Generation Development

In DevSecOps, development phase advancement goes through various effective solutions, but efficient bug detection, reliability, accurate reports, and user-friendly solution are still lacking. The existing tools raising a false alarm and somewhere no alarm at all at potential threats are no rare sight. Still, there has been no advancement towards a practical solution that could solve the issue mentioned above. In this paper, we have developed a state-of-the-art approach to the problem by leveraging artificial intelligence, enabling us to facilitate the analysis detection and generate more advanced reporting. In particular, we have integrated Machine Learning with DevSecOps to minimize false error rates. The proposed approach determines debugging errors in less time. Moreover, it provides beginner-friendly analysis for developers to accomplish by our precisely tailored machine learning models trained on the data-set derived from SEI CERT Standard.