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Automatic Creation of SQL Injection and Cross-Site Scripting Attacks

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dc.contributor Michael Ernst en_US
dc.contributor Program Analysis en_US Kiezun, Adam en_US Guo, Philip J. en_US Jayaraman, Karthick en_US Ernst, Michael D. en_US 2008-09-25T19:00:06Z 2008-09-25T19:00:06Z 2008-09-10
dc.identifier local: MIT-CSAIL-TR-2008-054
dc.description.abstract We present a technique for finding security vulnerabilitiesin Web applications. SQL Injection (SQLI) and cross-sitescripting (XSS) attacks are widespread forms of attackin which the attacker crafts the input to the application toaccess or modify user data and execute malicious code. Inthe most serious attacks (called second-order, or persistent,XSS), an attacker can corrupt a database so as to causesubsequent users to execute malicious code.This paper presents an automatic technique for creatinginputs that expose SQLI and XSS vulnerabilities. The techniquegenerates sample inputs, symbolically tracks taintsthrough execution (including through database accesses),and mutates the inputs to produce concrete exploits. Oursis the first analysis of which we are aware that preciselyaddresses second-order XSS attacks.Our technique creates real attack vectors, has few falsepositives, incurs no runtime overhead for the deployed application,works without requiring modification of applicationcode, and handles dynamic programming-languageconstructs. We implemented the technique for PHP, in a toolArdilla. We evaluated Ardilla on five PHP applicationsand found 68 previously unknown vulnerabilities (23 SQLI,33 first-order XSS, and 12 second-order XSS). en_US
dc.format.extent 11 p. en_US
dc.relation.ispartofseries Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory en_US
dc.subject reliability en_US
dc.subject dynamic analysis en_US
dc.subject dynamic taint en_US
dc.title Automatic Creation of SQL Injection and Cross-Site Scripting Attacks en_US
dc.identifier.citation en_US

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