Visible to the public Gelato: Feedback-driven and Guided Security Analysis of Client-side Web Applications

TitleGelato: Feedback-driven and Guided Security Analysis of Client-side Web Applications
Publication TypeConference Paper
Year of Publication2022
AuthorsHassanshahi, Behnaz, Lee, Hyunjun, Krishnan, Paddy
Conference Name2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)
KeywordsBrowsers, compositionality, Conferences, Crawlers, Human Behavior, JavaScript, Metrics, Production, program analysis, pubcrawl, resilience, Resiliency, security, Software, Web Browser Security, web security
AbstractModern web applications are getting more sophisticated by using frameworks that make development easy, but pose challenges for security analysis tools. New analysis techniques are needed to handle such frameworks that grow in number and popularity. In this paper, we describe Gelato that addresses the most crucial challenges for a security-aware client-side analysis of highly dynamic web applications. In particular, we use a feedback-driven and state-aware crawler that is able to analyze complex framework-based applications automatically, and is guided to maximize coverage of security-sensitive parts of the program. Moreover, we propose a new lightweight client-side taint analysis that outperforms the state-of-the-art tools, requires no modification to browsers, and reports non-trivial taint flows on modern JavaScript applications. Gelato reports vulnerabilities with higher accuracy than existing tools and achieves significantly better coverage on 12 applications of which three are used in production.
NotesISSN: 1534-5351
DOI10.1109/SANER53432.2022.00079
Citation Keyhassanshahi_gelato_2022