Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
9-2017
Abstract
JoanAudit is a static analysis tool to assist security auditors in auditing Web applications and Web services for common injection vulnerabilities during software development. It automatically identifies parts of the program code that are relevant for security and generates an HTML report to guide security auditors audit the source code in a scalable way. JoanAudit is configured with various security-sensitive input sources and sinks relevant to injection vulnerabilities and standard sanitization procedures that prevent these vulnerabilities. It can also automatically fix some cases of vulnerabilities in source code — cases where inputs are directly used in sinks without any form of sanitization — by using standard sanitization procedures. Our evaluation shows that by using JoanAudit, security auditors are required to inspect only 1% of the total code for auditing common injection vulnerabilities. The screen-cast demo is available at https://github.com/julianthome/joanaudit.
Keywords
Security auditing, static analysis, vulnerability, automated code fixing
Discipline
Programming Languages and Compilers | Software Engineering
Research Areas
Cybersecurity
Publication
Proceedings of 2017 11th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering, Paderborn, Germany, September 4–8
First Page
1004
Last Page
1008
Identifier
10.1145/3106237.3122822
City or Country
Paderborn, Germany
Citation
THOME, Julian; SHAR, Lwin Khin; BIANCULLI, Domenico; and BRIAND, Lionel.
JoanAudit: A tool for auditing common injection vulnerabilities. (2017). Proceedings of 2017 11th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering, Paderborn, Germany, September 4–8. 1004-1008.
Available at: https://ink.library.smu.edu.sg/sis_research/4776
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1145/3106237.3122822