Assessing Non-Intrusive Vulnerability Scanning Methodologies for Detecting Web Application Vulnerabilities on Large Scale
Elwin Shaji, Narayanan Subramanian · 2021 International Conference on System, Computation, Automation and Networking (ICSCAN) · 2021
The online presence of organizations is increasing at a rapid pace with the major adaptation of work from home. Organizations have new digital infrastructure being added to their digital portfolio on a regular basis. The threats that organizations face are also increasing at an alarming rate. It is crucial in such a scenario to safeguard and test the new and growing digital infrastructure without causing any interruption to the services provided by these organizations. Through this paper, we would like to inspect six non-intrusive detection methodologies which are useful in the identification of web application vulnerabilities without hampering the organization’s service model. The dataset that was used for real-world analysis consisted of government agencies and reputable organizations. We have assessed these vulnerabilities on the criterion of the statistical probability of finding these vulnerabilities on the dataset. We were able to identify 44 sub-domain takeover vulnerability in 1628 domains (0.02%), 263 cryptographic vulnerabilities (0.17%) and 167 open port vulnerabilities (0.10%) in 1538 domains, and 10,491 GitHub API Leaks were found within 27 organization’s GitHub repository, 3 Cross-Origin Resource Sharing (CORS) misconfigurations in 1213 domains (0.002%) and 0 Wayback machine API leaks from 800 domains.