Biblio

In this paper, we present a combinatorial testing methodology for automated black-box security testing of complex web applications. The focus of our work is the identification of Cross-site Scripting (XSS) vulnerabilities. We introduce a new modelling scheme for test case generation of XSS attack vectors consisting of locally optimized attack models. The modelling approach takes into account the response and behavior of the web application and is particularly efficient when used in conjunction with combinatorial testing. In addition to the modelling scheme, we present a research prototype of a security testing tool called XSSInjector, which executes attack vectors generated from our methodology against web applications. The tool also employs a newly developed test oracle for detecting XSS which allow us to precisely identify whether injected JavaScript is actually executed and thus eliminate false positives. Our testing methodology is sufficiently generic to be applied to any web application that returns HTML code. We describe the foundations of our approach and validate it via an extensive case study using a verification framework and real world web applications. In particular, we have found several new critical vulnerabilities in popular forum software, library management systems and gallery packages.

Many web applications are vulnerable to Cross Site Scripting (XSS) attacks enabling attackers to steal sensitive information and commit frauds. Much research in this area have focused on detecting vulnerable web pages using static and dynamic program analysis. The best practice to prevent XSS vulnerabilities is to encode untrusted dynamic content. However, a common programming error is the use of a wrong type of encoder to sanitize untrusted data, leaving the application vulnerable. We propose a new approach that can automatically fix this common type of XSS vulnerability in many situations. This approach is integrated into the software maintenance life cycle through unit testing. Vulnerable codes are refactored to reflect the suggested encoder and then verified using an attack evaluating mechanism to find a proper repair. Evaluation of this approach has been conducted on an open source medical record application with over 200 web pages written in JSP.

The inappropriate use of features intended to improve usability and interactivity of web applications has resulted in the emergence of various threats, including Cross-Site Scripting(XSS) attacks. In this work, we developed ETSS Detector, a generic and modular web vulnerability scanner that automatically analyzes web applications to find XSS vulnerabilities. ETSS Detector is able to identify and analyze all data entry points of the application and generate specific code injection tests for each one. The results shows that the correct filling of the input fields with only valid information ensures a better effectiveness of the tests, increasing the detection rate of XSS attacks.