An empirical study of information flows in real-world Javascript
Paper i proceeding, 2019

Information flow analysis prevents secret or untrusted data from flowing into public or trusted sinks. Existing mechanisms cover a wide array of options, ranging from lightweight taint analysis to heavyweight information flow control that also considers implicit flows. Dynamic analysis, which is particularly popular for languages such as JavaScript, faces the question whether to invest in analyzing flows caused by not executing a particular branch, so-called hidden implicit flows. This paper addresses the questions how common different kinds of flows are in real-world programs, how important these flows are to enforce security policies, and how costly it is to consider these flows. We address these questions in an empirical study that analyzes 56 real-world JavaScript programs that suffer from various security problems, such as code injection vulnerabilities, denial of service vulnerabilities, memory leaks, and privacy leaks. The study is based on a state-of-the-art dynamic information flow analysis and a formalization of its core. We find that implicit flows are expensive to track in terms of permissiveness, label creep, and runtime overhead. We find a lightweight taint analysis to be sufficient for most of the studied security problems, while for some privacy-related code, observable tracking is sometimes required. In contrast, we do not find any evidence that tracking hidden implicit flows reveals otherwise missed security problems. Our results help security analysts and analysis designers to understand the cost-benefit tradeoffs of information flow analysis and provide empirical evidence that analyzing information flows in a cost-effective way is a relevant problem.

Information flow control

Taint tracking

JavaScript

Implicit flow

Författare

Cristian Alexandru Staicu

Technische Universität Darmstadt

Daniel Schoepe

Chalmers, Data- och informationsteknik, Informationssäkerhet

Musard Balliu

Kungliga Tekniska Högskolan (KTH)

Michael Pradel

Technische Universität Darmstadt

Andrei Sabelfeld

Chalmers, Data- och informationsteknik, Informationssäkerhet

Proceedings of the ACM Conference on Computer and Communications Security

15437221 (ISSN)

45-59

14th ACM SIGSAC Workshop on Programming Languages and Analysis for Security, PLAS 2019, co-located with the 26th ACM Conference on Computer and Communications Security, ACM CCS 2019
London, United Kingdom,

Ämneskategorier

Annan data- och informationsvetenskap

Datavetenskap (datalogi)

Datorsystem

DOI

10.1145/3338504.3357339

Mer information

Senast uppdaterat

2019-12-19