Vetting browser extensions for security vulnerabilities with VEX

Author:

Bandhakavi Sruthi1,Tiku Nandit1,Pittman Wyatt1,King Samuel T.1,Madhusudan P.1,Winslett Marianne1

Affiliation:

1. University of Illinois at Urbana, Champaign

Abstract

The browser has become the de facto platform for everyday computation and a popular target for attackers of computer systems. Among the many potential attacks that target or exploit browsers, vulnerabilities in browser extensions have received relatively little attention. Currently, extensions are vetted by manual inspection, which is time consuming and subject to human error. In this paper, we present VEX, a framework for applying static information flow analysis to JavaScript code to identify security vulnerabilities in browser extensions. We describe several patterns of flows that can lead to privilege escalations in Firefox extensions. VEX analyzes Firefox extensions for such flow patterns using high-precision, context-sensitive, flow-sensitive static analysis. We subject 2460 browser extensions to the analysis, and VEX finds 5 of the 18 previously known vulnerabilities and 7 previously unknown vulnerabilities.

Funder

Office of Naval Research

Air Force Office of Scientific Research

National Science Foundation

Division of Computer and Network Systems

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science

Cited by 49 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. npm-follower: A Complete Dataset Tracking the NPM Ecosystem;Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering;2023-11-30

2. Wemint:Tainting Sensitive Data Leaks in WeChat Mini-Programs;2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE);2023-09-11

3. FProbe: The Flow-Centric Detection and a Large-Scale Measurement of Browser Fingerprinting;2023 32nd International Conference on Computer Communications and Networks (ICCCN);2023-07

4. From Manifest V2 to V3: A Study on the Discoverability of Chrome Extensions;Lecture Notes in Computer Science;2023

5. A Study on the Design of Pandora's Box Web Application Using Design Thinking approach;2022 6th International Conference on Software and e-Business;2022-12-09

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3