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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 serverside, 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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The term 'Session Fixation vulnerability' subsumes issues in Web applications that under certain circumstances enable the adversary to perform a Session Hijacking attack through controlling the victim's session identifier value. A successful attack allows the attacker to fully impersonate the victim towards the vulnerable Web application. We analyse the vulnerability pattern and identify its root cause in the separation of concerns between the application logic, which is responsible for the authentication processes, and the framework support, which handles the task of session tracking. Based on this result, we present and discuss three distinct server-side measures for mitigating Session Fixation vulnerabilities. Each of our countermeasures is tailored to suit a specific real-life scenario that might be encountered by the operator of a vulnerable Web application.

No abstract