Description
The web application environment is the platform with the most user contact points and security incident types, and vulnerability analysis using various automated tools has been performed for a long time. However, we realized that these tools have limitations and are not very helpful to manual diagnosticians. Therefore, we planned to create a tool that can provide manual diagnosticians with useful information in advance from a manual perspective to reduce time spent. In this presentation, we will share how we conducted research to predict vulnerabilities while developing a web vulnerability manual analysis tool and what Python modules were utilized.