Related papers: UNIFUZZ: A Holistic and Pragmatic Metrics-Driven P…
Nowadays automated dynamic analysis frameworks for continuous testing are in high demand to ensure software safety and satisfy the security development lifecycle (SDL) requirements. The security bug hunting efficiency of cutting-edge hybrid…
Most software that runs on computers undergoes processing by compilers. Since compilers constitute the fundamental infrastructure of software development, their correctness is paramount. Over the years, researchers have invested in…
A greybox fuzzer is an automated software testing tool that generates new test inputs by applying randomly chosen mutators (e.g., flipping a bit or deleting a block of bytes) to a seed input in random order and adds all coverage-increasing…
Objective: Machine learning (ML) models are increasingly used to generate electrical stimulation patterns in neuroprosthetic devices such as visual prostheses. While these models promise precise and personalized control, they also introduce…
Simulation-based testing is essential for evaluating the safety of Autonomous Driving Systems (ADSs). Comprehensive evaluation requires testing across diverse scenarios that can trigger various types of violations under different…
In the past few years, several attacks against the vulnerabilities of EOSIO smart contracts have caused severe financial losses to this prevalent blockchain platform. As a lightweight test-generation approach, grey-box fuzzing can open up…
This paper proposes a new approach to multi-sensor data fusion. It suggests that aggregation of data from multiple sensors can be done more efficiently when we consider information about sensors' different characteristics. Similar to most…
In recent years, REST API fuzzing has emerged to explore errors on a cloud service. Its performance highly depends on the sequence construction and request generation. However, existing REST API fuzzers have trouble generating long…
Fuzzing, a widely-used technique for bug detection, has seen advancements through Large Language Models (LLMs). Despite their potential, LLMs face specific challenges in fuzzing. In this paper, we identified five major challenges of…
As the complexities of processors keep increasing, the task of effectively verifying their integrity and security becomes ever more daunting. The intricate web of instructions, microarchitectural features, and interdependencies woven into…
Programmable Logic Controllers are used for smart homes, in production processes or to control critical infrastructures. Modern industrial devices in the control level are often communicating over proprietary protocols on top of TCP/IP with…
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…
Timing vulnerabilities in processors have emerged as a potent threat. As processors are the foundation of any computing system, identifying these flaws is imperative. Recently fuzzing techniques, traditionally used for detecting software…
Network applications are routinely under attack. We consider the problem of developing an effective and efficient fuzzer for the recently ratified QUIC network protocol to uncover security vulnerabilities. QUIC offers a unified transport…
Ever-increasing design complexity of System-on-Chips (SoCs) led to significant verification challenges. Unlike software, bugs in hardware design are vigorous and eternal i.e., once the hardware is fabricated, it cannot be repaired with any…
Recent years have witnessed a wide array of results in software testing, exploring different approaches and methodologies ranging from fuzzers to symbolic engines, with a full spectrum of instances in between such as concolic execution and…
The purpose of continuous fuzzing platforms is to enable fuzzing for software projects via \emph{fuzz harnesses} -- but as the projects continue to evolve, are these harnesses updated in lockstep, or do they run out of date? If these…
Context: Exhaustive fuzzing of modern JavaScript engines is infeasible due to the vast number of program states and execution paths. Coverage-guided fuzzers waste effort on low-risk inputs, often ignoring vulnerability-triggering ones that…
Fuzzing technologies have evolved at a fast pace in recent years, revealing bugs in programs with ever increasing depth and speed. Applications working with complex formats are however more difficult to take on, as inputs need to meet…
A popular metric to evaluate the performance of fuzzers is branch coverage. However, we argue that focusing solely on covering many different branches (i.e., the richness) is not sufficient since the majority of the covered branches may…