Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-25347
Publication type: Article in scientific journal
Type of review: Peer review (publication)
Title: Automating the detection of access control vulnerabilities in web applications
Authors: Rennhard, Marc
Kushnir, Malte
Favre, Olivier
Esposito, Damiano
Zahnd, Valentin
et. al: No
DOI: 10.1007/s42979-022-01271-1
10.21256/zhaw-25347
Published in: SN Computer Science
Volume(Issue): 3
Issue: 5
Page(s): 376
Issue Date: 2022
Publisher / Ed. Institution: Springer
ISSN: 2661-8907
Language: English
Subjects: Automated testing; Web application security testing; Access control testing; Black box security testing; Dynamic web application security testing
Subject (DDC): 005: Computer programming, programs and data
Abstract: The importance of automated and reproducible security testing of web applications is growing, driven by increasing security requirements, short software development cycles, and constraints with respect to time and budget. Existing automated security testing tools are already well suited to detect some types of vulnerabilities, e.g., SQL injection or cross-site scripting vulnerabilities. However, other vulnerability types are much harder to uncover in an automated way. One important representative of this type are access control vulnerabilities, which are highly relevant in practice as they can grant unauthorized users access to security-critical data or functions in web applications. In this paper, a practical solution to automatically detect HTTP GET request-based access control vulnerabilities in web applications is presented. The solution is based on previously proposed ideas, which are extended with novel approaches to enable completely automated access control testing with minimal configuration effort, which in turn enables frequent and reproducible testing. An evaluation with seven web applications based on different technologies demonstrates the general applicability of the solution and that it can automatically uncover most access control vulnerabilities while keeping the number of false positives low.
URI: https://digitalcollection.zhaw.ch/handle/11475/25347
Fulltext version: Published version
License (according to publishing contract): CC BY 4.0: Attribution 4.0 International
Departement: School of Engineering
Organisational Unit: Institute of Applied Information Technology (InIT)
Published as part of the ZHAW project: FASTscan: Fully Automated Security Testing with scanmeter
Appears in collections:Publikationen School of Engineering

Files in This Item:
File Description SizeFormat 
2022_Rennhard-etal_Automating-detection-access-control-vulnerabilities.pdf1.46 MBAdobe PDFThumbnail
View/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.