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Developing an in house vulnerability scanner for detecting Template Injection, XSS, and DOM-XSS vulnerabilities

Authors: Hauger, Marius; Jensen, Stig;

Developing an in house vulnerability scanner for detecting Template Injection, XSS, and DOM-XSS vulnerabilities

Abstract

Web applications are becoming an essential part of today's digital world. However, with the increase in the usage of web applications, security threats have also become more prevalent. Cyber attackers can exploit vulnerabilities in web applications to steal sensitive information or take control of the system. To prevent these attacks, web application security must be given due consideration. Existing vulnerability scanners fail to detect Template Injection, XSS, and DOM-XSS vulnerabilities effectively. To bridge this gap in web application security, a customized in-house scanner is needed to quickly and accurately identify these vulnerabilities, enhancing manual security assessments of web applications. This thesis focused on developing a modular and extensible vulnerability scanner to detect Template Injection, XSS, and DOM-based XSS vulnerabilities in web applications. Testing the scanner against other free and open-source solutions on the market showed that it outperformed them on Template injection vulnerabilities and nearly all on XSS-type vulnerabilities. While the scanner has limitations, focusing on specific injection vulnerabilities can result in better performance.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
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