{"id":182654,"date":"2008-03-13T00:00:00","date_gmt":"2009-10-31T09:51:52","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/candidate-talk-techniques-and-tools-for-engineering-secure-web-applications\/"},"modified":"2016-09-09T09:49:22","modified_gmt":"2016-09-09T16:49:22","slug":"candidate-talk-techniques-and-tools-for-engineering-secure-web-applications","status":"publish","type":"msr-video","link":"https:\/\/www.microsoft.com\/en-us\/research\/video\/candidate-talk-techniques-and-tools-for-engineering-secure-web-applications\/","title":{"rendered":"Candidate Talk: Techniques and Tools for Engineering Secure Web Applications"},"content":{"rendered":"
\n

Web applications enable much of today’s online business including banking,
\nshopping, university admissions, and various governmental activities.
\nAnyone with a web browser can access them, and the data they manage
\ntypically has significant value both to the users and to the service
\nproviders. Cross-site scripting (XSS) and SQL injection are classes of
\nattacks in which an attacker interacts with a client or database,
\nrespectively, through vulnerabilities in the server thereby gaining the
\ntrust level of the server. These classes of attacks are pervasive:
\nsince 2005, they have been the most frequently reported classes
\nof vulnerabilities. These vulnerabilities arise because web applications’
\nlayers (client, server, and database) communicate via unstructured strings,
\nand validating untrusted input for use in these commands is error-prone and
\nintroduces a challenging software engineering problem.<\/p>\n

In this talk, I will present a general characterization of these classes of
\ninput validation-based errors and a set of dynamic and static techniques to
\ndetect and prevent XSS and SQL injection attacks. Programmers usually do
\nnot specify their intentions explicitly regarding SQL query construction,
\nbut I will show how we can use principled techniques to characterize
\nprogrammer intentions. We can then prevent attack queries from being sent
\nto the database with a low-overhead, runtime check that precisely
\ndistinguishes legitimate queries from attacks. In order to help find bugs
\nearly in the software development process, I also pursued static analysis,
\nand I will describe a sound and precise analysis that scales to large,
\nreal-world web applications and found known and unknown SQL injection
\nvulnerabilities. I will further present how we extended this static
\nanalysis to the related but more difficult problem of XSS. I will conclude
\nthis talk by discussing future challenges in this domain.<\/p>\n<\/div>\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

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