ConFuzzius: A Data Dependency-Aware Hybrid Fuzzer for Smart Contracts

in European Symposium on Security and Privacy, Vienna 7-11 September 2021 (2021, September)

Smart contracts are Turing-complete programs that are executed across a blockchain. Unlike traditional programs, once deployed, they cannot be modified. As smart contracts carry more value, they become ... [more ▼]

Smart contracts are Turing-complete programs that are executed across a blockchain. Unlike traditional programs, once deployed, they cannot be modified. As smart contracts carry more value, they become more of an exciting target for attackers. Over the last years, they suffered from exploits costing millions of dollars due to simple programming mistakes. As a result, a variety of tools for detecting bugs have been proposed. Most of these tools rely on symbolic execution, which may yield false positives due to over-approximation. Recently, many fuzzers have been proposed to detect bugs in smart contracts. However, these tend to be more effective in finding shallow bugs and less effective in finding bugs that lie deep in the execution, therefore achieving low code coverage and many false negatives. An alternative that has proven to achieve good results in traditional programs is hybrid fuzzing, a combination of symbolic execution and fuzzing. In this work, we study hybrid fuzzing on smart contracts and present ConFuzzius, the first hybrid fuzzer for smart contracts. ConFuzzius uses evolutionary fuzzing to exercise shallow parts of a smart contract and constraint solving to generate inputs that satisfy complex conditions that prevent evolutionary fuzzing from exploring deeper parts. Moreover, ConFuzzius leverages dynamic data dependency analysis to efficiently generate sequences of transactions that are more likely to result in contract states in which bugs may be hidden. We evaluate the effectiveness of ConFuzzius by comparing it with state-of-the-art symbolic execution tools and fuzzers for smart contracts. Our evaluation on a curated dataset of 128 contracts and a dataset of 21K real-world contracts shows that our hybrid approach detects more bugs than state-of-the-art tools (up to 23%) and that it outperforms existing tools in terms of code coverage (up to 69%). We also demonstrate that data dependency analysis can boost bug detection up to 18%. [less ▲]

Leveraging eBPF to preserve user privacy for DNS, DoT, and DoH queries

in Proceedings of the 15th International Conference on Availability, Reliability and Security (2020, August)

The Domain Name System (DNS), a fundamental protocol that controls how users interact with the Internet, inadequately provides protection for user privacy. Recently, there have been advancements in the ... [more ▼]

The Domain Name System (DNS), a fundamental protocol that controls how users interact with the Internet, inadequately provides protection for user privacy. Recently, there have been advancements in the field of DNS privacy and security in the form of the DNS over TLS (DoT) and DNS over HTTPS (DoH) protocols. The advent of these protocols and recent advancements in large-scale data processing have drastically altered the threat model for DNS privacy. Users can no longer rely on traditional methods, and must instead take active steps to ensure their privacy. In this paper, we demonstrate how the extended Berkeley Packet Filter (eBPF) can assist users in maintaining their privacy by leveraging eBPF to provide privacy across standard DNS, DoH, and DoT communications. Further, we develop a method that allows users to enforce application-specific DNS servers. Our method provides users with control over their DNS network traffic and privacy without requiring changes to their applications while adding low overhead. [less ▲]

Dependability Assessment of the Android OS Through Fault Injection

in IEEE Transaction on Reliability (2019)

The reliability of mobile devices is a challenge for vendors since the mobile software stack has significantly grown in complexity. In this article, we study how to assess the impact of faults on the ... [more ▼]

The reliability of mobile devices is a challenge for vendors since the mobile software stack has significantly grown in complexity. In this article, we study how to assess the impact of faults on the quality of user experience in the Android mobile OS through fault injection. We first address the problem of identifying a realistic fault model for the Android OS, by providing developers a set of lightweight and systematic guidelines for fault modeling. Then, we present an extensible fault injection tool (AndroFIT) to apply such fault model on actual, commercial Android devices. Finally, we present a large fault injection experimentation on three Android products from major vendors and point out several reliability issues and opportunities for improving the Android OS. [less ▲]

Evolutionary Fuzzing of Android OS Vendor System Services

in Empirical Software Engineering (2019)

Android devices are shipped in several flavors by more than 100 manufacturer partners, which extend the Android “vanilla” OS with new system services and modify the existing ones. These proprietary ... [more ▼]

Android devices are shipped in several flavors by more than 100 manufacturer partners, which extend the Android “vanilla” OS with new system services and modify the existing ones. These proprietary extensions expose Android devices to reliability and security issues. In this paper, we propose a coverage-guided fuzzing platform (Chizpurfle) based on evolutionary algorithms to test proprietary Android system services. A key feature of this platform is the ability to profile coverage on the actual, unmodified Android device, by taking advantage of dynamic binary re-writing techniques. We applied this solution to three high-end commercial Android smartphones. The results confirmed that evolutionary fuzzing is able to test Android OS system services more efficiently than blind fuzzing. Furthermore, we evaluate the impact of different choices for the fitness function and selection algorithm. [less ▲]

Analyzing the Context of Bug-Fixing Changes in the OpenStack Cloud Computing Platform

in 2019 IEEE 30th International Symposium on Software Reliability Engineering (ISSRE) (2019)

Chizpurfle: A Gray-Box Android Fuzzer for Vendor Service Customizations

in 2017 IEEE 28th International Symposium on Software Reliability Engineering (ISSRE) (2017)

The software aging and rejuvenation repository: Http://openscience.us/repo/software-aging/

in 2015 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW) (2015)

Improving Usability of Fault Injection

in 2014 IEEE International Symposium on Software Reliability Engineering Workshops (2014)