Related papers: ConFuzzius: A Data Dependency-Aware Hybrid Fuzzer …

Fuzzing is a popular technique for finding software bugs. However, the performance of the state-of-the-art fuzzers leaves a lot to be desired. Fuzzers based on symbolic execution produce quality inputs but run slow, while fuzzers based on…

Smart contracts are immutable, verifiable, and autonomous pieces of code that can be deployed and ran on blockchain networks like Ethereum. Due to the immutability nature of blockchain, no change is possible on a deployed smart contract or…

Smart contracts are pieces of code that reside inside the blockchains and can be triggered to execute any transaction when specifically predefined conditions are satisfied. Being commonly used for commercial transactions in blockchain makes…

Coverage-guided Greybox Fuzzing (CGF) is one of the most successful and widely-used techniques for bug hunting. Two major approaches are adopted to optimize CGF: (i) to reduce search space of inputs by inferring relationships between input…

Security vulnerabilities play a vital role in network security system. Fuzzing technology is widely used as a vulnerability discovery technology to reduce damage in advance. However, traditional fuzzing techniques have many challenges, such…

Coverage guided fuzzing (CGF) is an effective testing technique which has detected hundreds of thousands of bugs from various software applications. It focuses on maximizing code coverage to reveal more bugs during fuzzing. However, a…

Fuzzing continues to be the most effective method for identifying security vulnerabilities in software. In the context of fuzz testing, the fuzzer supplies varied inputs to fuzz targets, which are designed to comprehensively exercise…

Blockchain has become particularly popular due to its promise to support business-critical services in very different domains (e.g., retail, supply chains, healthcare). Blockchain systems rely on complex middleware, like Ethereum or…

Blockchain recently became very popular due to its use in cryptocurrencies and potential application in various domains (e.g., retail, healthcare, insurance). The smart contract is a key part of blockchain systems and specifies an agreement…

Some smart contracts violate decentralization principles by defining privileged accounts that manage other users' assets without permission, introducing centralization risks that have caused financial losses. Existing methods, however, face…

BACKGROUND: Software engineers must be vigilant in preventing and correcting vulnerabilities and other critical bugs. In servicing this need, numerous tools and techniques have been developed to assist developers. Fuzzers, by autonomously…

The rapid growth of Ethereum has made it more important to quickly and accurately detect smart contract vulnerabilities. While machine-learning-based methods have shown some promise, many still rely on rule-based preprocessing designed by…

A flurry of fuzzing tools (fuzzers) have been proposed in the literature, aiming at detecting software vulnerabilities effectively and efficiently. To date, it is however still challenging to compare fuzzers due to the inconsistency of the…

Multi-robot swarms play an essential role in complex missions including battlefield reconnaissance, agricultural pest monitoring, as well as disaster search and rescue. Unfortunately, given the complexity of swarm algorithms, logical…

We present a coverage-guided testing algorithm for distributed systems implementations. Our main innovation is the use of an abstract formal model of the system that is used to define coverage. Such abstract models are frequently developed…

Fuzzers and static analyzers find many bugs but struggle with logic bugs in mature codebases. Triggering such a bug often requires multi-step reasoning that produces no distinctive execution feedback, and variants can appear across…

Large Language Models (LLMs) have gained widespread use in various applications due to their powerful capability to generate human-like text. However, prompt injection attacks, which involve overwriting a model's original instructions with…

Mutation-based fuzzing is popular and effective in discovering unseen code and exposing bugs. However, only a few studies have concentrated on quantifying the importance of input bytes, which refers to the degree to which a byte contributes…

How to search for bugs in 1,000 programs using a pre-existing fuzzer and a standard PC? We consider this problem and show that a well-designed strategy that determines which programs to fuzz and for how long can greatly impact the number of…

Fuzzing is an automated application vulnerability detection method. For genetic algorithm-based fuzzing, it can mutate the seed files provided by users to obtain a number of inputs, which are then used to test the objective application in…