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XSSDS: Server-Side Detection of Cross-Site Scripting Attacks

Martin Johns, Björn Engelmann, Joachim Posegga

Open publisher page 103 citations

Abstract

Cross-site scripting (XSS) has emerged to one of the most prevalent type of security vulnerabilities. While the reason for the vulnerability primarily lies on the server-side, the actual exploitation is within the victim's Web browser on the client-side. Therefore, an operator of a Web application has only very limited evidence of XSS issues. In this paper, we propose a passive detection system to identify successful XSS attacks. Based on a prototypical implementation, we examine our approach's accuracy and verify its detection capabilities. We compiled a data-set of 500.000 individual HTTP request/response-pairs from 95 popular web applications for this, in combination with both real word and manually crafted XSS-exploits; our detection approach results in a total of zero false negatives for all tests, while maintaining an excellent false positive rate for more than 80% of the examined Web applications.

About this research paper

What this paper is about

Cross-site scripting (XSS) has emerged to one of the most prevalent type of security vulnerabilities. While the reason for the vulnerability primarily lies on the server-side, the actual exploitation is within the victim's Web browser on the client-side. Therefore, an operator of a Web application has only very limited evidence of XSS issues. In this paper, we propose a passive detection system to identify successful XSS attacks. Based on a prototypical implementation, we examine our approach's accuracy and verify its detection capabilities. We compiled a data-set of 500.000 individual HTTP request/response-pairs from 95 popular web applications for this, in combination with both real word and manually crafted XSS-exploits; our detection approach results in a total of zero false negatives for all tests, while maintaining an excellent false positive rate for more than 80% of the examined Web applications.

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OpenAlex reports 103 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Cross-site scripting (XSS) has emerged to one of the most prevalent type of security vulnerabilities. While the reason for the vulnerability primarily lies on the server-side, the actual exploitation is within the victim's Web browser on the client-side. Therefore, an operator of a Web application has only very limited evidence of XSS issues. In this paper, we propose a passive detection system to identify successful XSS attacks. Based on a prototypical implementation, we examine our approach's accuracy and verify its detection capabilities. We compiled a data-set of 500.000 individual HTTP request/response-pairs from 95 popular web applications for this, in combination with both real word and manually crafted XSS-exploits; our detection approach results in a total of zero false negatives for all tests, while maintaining an excellent false positive rate for more than 80% of the examined Web applications.

Key concepts: Cross-site scripting, Computer science, Client-side, Scripting language, Exploit, Computer security, Server-side, Web application

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