DepthStAr: Deep Strange Arguments Detection

Michael Berlin, Oded Margalit, Gera Weiss

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


We present a tool for detecting a new type of bad smell in software code and describe how it was used to find critical security bugs, some of which exist in Linux code for many years and are still present in current distributions. Our tool applies state-of-the-art formal methods and static analysis techniques to scan the execution paths of programs. In this scan, the tool detects conditions that may lead to calling certain functions with strange combinations of arguments, called Abnormal Argument Case (AAC) in this paper. These conditions are presented to the developers as they often point at potential bugs and security vulnerabilities. The paper explains how the tool works and describes an empirical evaluation of its performance.

Original languageEnglish
Title of host publicationCyber Security Cryptography and Machine Learning - 5th International Symposium, CSCML 2021, Proceedings
EditorsShlomi Dolev, Oded Margalit, Benny Pinkas, Alexander Schwarzmann
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages15
ISBN (Print)9783030780852
StatePublished - 1 Jul 2021
Event5th International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2021 - Be'er Sheva, Israel
Duration: 8 Jul 20219 Jul 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12716 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference5th International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2021
CityBe'er Sheva

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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