Software Vulnerabilities Using Artificial Intelligence

Software serves as a cornerstone in the functionality of devices and systems that seamlessly integrate into our daily lives. However, the complexity of these systems, often developed by multiple programmers, leaves room for inadvertent errors in the code. These errors, known as software vulnerabilities, represent flaws or defects in the software's construction that malicious actors can exploit to gain unauthorized access or privileges within the system. Despite advancements in understanding vulnerabilities, the prevalence of reported vulnerabilities continues to rise, emphasizing the critical importance of software security research. In response to this growing concern, there is a pressing need for tools to assist programmers in identifying and mitigating vulnerabilities during the code development process. As part of our ongoing research paper into detection of vulnerabilities, along with methods for their prevention and detection. Furthermore, we delve into recent advancements in utilizing machine learning techniques to enhance vulnerability detection across various types of software vulnerabilities. We have tested on real data set and the results are better than existing models.