Automatic Detection and Risk Assessment of Session Management Vulnerabilities in Web Applications

Abstract

The session management mechanism is a source of several threats to the security of web applications. While lots of web-based software vulnerabilities are due to weaknesses in session management design and implementation, existing methods and tools still have considerable limitations to fully detect those vulnerabilities. In this paper, a black-box method is presented to detect session management vulnerabilities by analyzing browser-server traffic. We have identified some features in the traffic related to the security of session management. The features are either dependent on or independent of languages and programming frameworks. They are the leaves of our constructed attack tree upon which we assess the total risk of session vulnerabilities for a web application. Our simple yet effective idea results in more accurate detection of session vulnerabilities compared to well-known vulnerability scanners. Our experimental evaluations on several case studies confirm the effectiveness of our approach in terms of its vulnerability detection as well as in its risk assessment.