JCOMIX: a Search-based Tool to Detect XML Injection Vulnerabilities inWeb Applications

A search-based tool to detect XML injection vulnerabilities in web applications

Conference Paper (2019)
Author(s)

Dimitri Stallenberg (Student TU Delft)

Annibale Panichella (TU Delft - Software Engineering)

Research Group
Software Engineering
Copyright
© 2019 Dimitri Michel Stallenberg, A. Panichella
DOI related publication
https://doi.org/10.1145/3338906.3341178
More Info
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Publication Year
2019
Language
English
Copyright
© 2019 Dimitri Michel Stallenberg, A. Panichella
Research Group
Software Engineering
Pages (from-to)
1090-1094
ISBN (electronic)
978-1-4503-5572-8
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Input sanitization and validation of user inputs are well-established protection mechanisms for microservice architectures against XML injection attacks (XMLi). The effectiveness of the protection mechanisms strongly depends on the quality of the sanitization and validation rule sets (e.g., regular expressions) and, therefore, security analysts have to test them thoroughly. In this demo, we introduce JCOMIX, a penetration testing tool that generates XMLi attacks (test cases) exposing XML vulnerabilities in front-end web applications. JCOMIX implements various search algorithms, including random search (traditional fuzzing), genetic algorithms (GAs), and the more recent co-operative, co-evolutionary algorithm designed explicitly for the XMLi testing (COMIX). We also show the results of an empirical study showing the effectiveness of JCOMIX in testing an open-source front-end web application.

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