Related papers: Adaptive Grey-Box Fuzz-Testing with Thompson Sampl…

Security vulnerabilities in Internet-of-Things devices, mobile platforms, and autonomous systems remain critical. Traditional mutation-based fuzzers -- while effectively explore code paths -- primarily perform byte- or bit-level edits…

To ensure the reliability of DNN systems and address the test generation problem for neural networks, this paper proposes a fuzzing test generation technique based on many-objective optimization algorithms. Traditional fuzz testing employs…

Grammar-based fuzzing is a technique used to find software vulnerabilities by injecting well-formed inputs generated following rules that encode application semantics. Most grammar-based fuzzers for network protocols rely on human experts…

Fuzzing has become the de facto standard technique for finding software vulnerabilities. However, even state-of-the-art fuzzers are not very efficient at finding hard-to-trigger software bugs. Most popular fuzzers use evolutionary guidance…

Collaborative fuzzing combines multiple individual fuzzers and dynamically chooses appropriate combinations for different programs. Unlike individual fuzzers that rely on specific assumptions, collaborative fuzzing relaxes assumptions on…

Large language models (LLMs) have recently experienced tremendous popularity and are widely used from casual conversations to AI-driven programming. However, despite their considerable success, LLMs are not entirely reliable and can give…

Fuzzing is a promising technique for detecting security vulnerabilities. Newly developed fuzzers are typically evaluated in terms of the number of bugs found on vulnerable programs/binaries. However,existing corpora usually do not capture…

Database Management System (DBMS) fuzzing is an automated testing technique aimed at detecting errors and vulnerabilities in DBMSs by generating, mutating, and executing test cases. It not only reduces the time and cost of manual testing…

Gray-box fuzzing is widely used for testing embedded systems (ESes). State-of-the-art (SOTA) gray-box fuzzers test ES firmware in fully emulated environments without real peripherals. They emulate missing peripherals to achieve decent code…

Generation-based fuzzing is a software testing approach which is able to discover different types of bugs and vulnerabilities in software. It is, however, known to be very time consuming to design and fine tune classical fuzzers to achieve…

Directed greybox fuzzing (DGF) focuses on efficiently reaching specific program locations or triggering particular behaviors, making it essential for tasks like vulnerability detection and crash reproduction. However, existing methods often…

Fuzz testing is often automated, but also frequently augmented by experts who insert themselves into the workflow in a greedy search for bugs. In this paper, we propose Homo in Machina, or HM-fuzzing, in which analyses guide the manual…

Seed scheduling is a prominent factor in determining the yields of hybrid fuzzing. Existing hybrid fuzzers schedule seeds based on fixed heuristics that aim to predict input utilities. However, such heuristics are not generalizable as there…

Machine learning models are notoriously difficult to interpret and debug. This is particularly true of neural networks. In this work, we introduce automated software testing techniques for neural networks that are well-suited to discovering…

Software testing is becoming a critical part of the development cycle of embedded devices, enabling vulnerability detection. A well-studied approach of software testing is fuzz-testing (fuzzing), during which mutated input is sent to an…

Computer programs are not executed in isolation, but rather interact with the execution environment which drives the program behaviors. Software validation methods thus need to capture the effect of possibly complex environmental…

Testing ultra-large microservices-based FinTech systems presents significant challenges, including restricted access to production environments, complex dependencies, and stringent security constraints. We propose SandBoxFuzz, a scalable…

Greybox fuzzing is the de-facto standard to discover bugs during development. Fuzzers execute many inputs to maximize the amount of reached code. Recently, Directed Greybox Fuzzers (DGFs) propose an alternative strategy that goes beyond…

Service fingerprinting (i.e. the identification of network services and other applications on computing systems) is an essential part of penetration tests. The main contribution of this paper is a study on the improvement of fingerprinting…

Fuzzing is one of the most effective approaches to finding software flaws. However, applying it to microcontroller firmware incurs many challenges. For example, rehosting-based solutions cannot accurately model peripheral behaviors and thus…