Visible to the public Detecting Input Sanitization Errors in Scala

TitleDetecting Input Sanitization Errors in Scala
Publication TypeConference Paper
Year of Publication2019
AuthorsAshouri, Mohammadreza
Conference Name2019 Seventh International Symposium on Computing and Networking Workshops (CANDARW)
Date PublishedNov. 2019
PublisherIEEE
ISBN Number978-1-7281-5268-4
Keywordscompositionality, data deletion, Data Sanitization, dynamic taint analyzer, Error, Functional programming, high-level language, Human Behavior, human factors, Input Sanitization, input sanitization errors, object-oriented programming, privacy, program diagnostics, programming languages, pubcrawl, resilience, Resiliency, Scala applications, Scala Compiler, Scala programming language, Scalability, ScalaTaint, security of data, sensitive sink methods, static types, taint analysis
Abstract

Scala programming language combines object-oriented and functional programming in one concise, high-level language, and the language supports static types that help to avoid bugs in complex programs. This paper proposes a dynamic taint analyzer called ScalaTaint for Scala applications. The analyzer traces the propagation of malicious inputs from untrusted sources to sensitive sink methods in programs that can be exploited by adversaries. In this work, we evaluated the accuracy of ScalaTaint with a security benchmark suite including 7 projects in Scala. As a result, our analyzer could report 49 vulnerabilities within 753,372 lines of code. Moreover, the result of our performance measurement on ScalaBench shows 67% runtime overhead that demonstrates the usefulness and efficiently of our technique in comparison with similar tools.

URLhttps://ieeexplore.ieee.org/document/8951588
DOI10.1109/CANDARW.2019.00062
Citation Keyashouri_detecting_2019