Description
Node.js is an extremely popular development framework for web applications. The appeal of its event-driven, asynchronous flow and the convenience of JavaScript as its programming language have driven its rapid growth, and it is currently deployed by leading companies in retail, finance, and other important sectors. However, the tools currently available for Node.js developers to secure their applications against malicious attackers are notably scarce. While there has been a substantial amount of security tools created for web applications in many other languages such as PHP and Java, very little exists for Node.js applications. This could compromise private information belonging to companies such as PayPal and WalMart. We propose a tool to statically analyze Node.js web applications for five popular vulnerabilites: cross-site scripting, SQL injection, server-side request forgery, command injection, and code injection. We base our tool off of JSAI, a platform created to parse client-side JavaScript for security risks. JSAI is novel because of its configuration capabilities, which allow a user to choose between various analysis options at runtime in order to select the most thorough analysis with the least amount of processing time. We contribute to the development of our tool by rigorously analyzing and documenting vulnerable functions and objects in Node.js that are relevant to the vulnerabilities we have selected. We intend to use this documentation to build a robust Node.js static analysis tool and we hope that other developers will also incorporate this analysis into their Node.js security projects.
Details
Title
- TSCAN: Toward a Static and Customizable Analysis for Node.js
Contributors
- Wasserman, Jonathan Kanter (Author)
- Doupe, Adam (Thesis director)
- Ahn, Gail-Joon (Committee member)
- Zhao, Ziming (Committee member)
- School of Historical, Philosophical and Religious Studies (Contributor)
- Computer Science and Engineering Program (Contributor)
- Barrett, The Honors College (Contributor)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2017-05
Resource Type
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