Confuzzion: a Java Virtual Machine Fuzzer for Type Confusion VulnerabilitiesShow others and affiliations
2021 (English)In: 2021 IEEE 21st International Conference on Software Quality, Reliability and Security (QRS), IEEE, 2021, p. 586-597Conference paper, Published paper (Refereed)
Abstract [en]
Current Java Virtual Machine (JVM) fuzzersaim at generating syntactically valid Java programs, without targeting any particular use of the standard Java library. While effective, such fuzzers fail to discover specific kinds of bugs or vulnerabilities, such as type confusion, that are related to the standard API usage. To deal with this issue, we introduce amutation-based feedback-guided black-box JVM fuzzer, called CONFUZZION. CONFUZZION, as the name suggests, targets security-relevant object-oriented flaws with a particular focus on type confusion vulnerabilities. We show that in less than 4 hours, on commodity hardware and without any predefined initialization seed, CONFUZZION automatically generates Java programs that reveal JVM vulnerabilities, i.e., the Common Vulnerabilities and Exposures CVE-2017-3272. We also show that state-of-the-art fuzzers or even traditional automatic testing techniques are not capable of detecting such faults, even after 48 hours of execution in the same environment. To the best of our knowledge, CONFUZZION is the first fuzzer able to detect JVM type confusion vulnerabilities.
Place, publisher, year, edition, pages
IEEE, 2021. p. 586-597
Series
IEEE International Conference on Software Quality Reliability and Security, ISSN 2693-9185, E-ISSN 2693-9177
Keywords [en]
Fuzzing, vulnerability, Java Virtual Machine
National Category
Computer Sciences Software Engineering
Identifiers
URN: urn:nbn:se:umu:diva-198707DOI: 10.1109/qrs54544.2021.00069ISI: 000814747000059Scopus ID: 2-s2.0-85136119401ISBN: 978-1-6654-5813-9 (electronic)ISBN: 978-1-6654-5814-6 (print)OAI: oai:DiVA.org:umu-198707DiVA, id: diva2:1688766
Conference
21st IEEE International Conference on Software Quality, Reliability and Security (QRS), Hainan, China, December 06-10, 2021
Funder
Knut and Alice Wallenberg FoundationWallenberg AI, Autonomous Systems and Software Program (WASP)
Note
At the time this research was conducted Alexandre Bartel was at the University of Luxembourg and the University of Copenhagen.
2022-08-192022-08-192024-07-02Bibliographically approved