Related papers: Nyx-Net: Network Fuzzing with Incremental Snapshot…

Network attacks have become a major security concern for organizations worldwide and have also drawn attention in the academics. Recently, researchers have applied neural networks to detect network attacks with network logs. However, public…

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…

Fingerprinting of services and operating systems is an essential part of penetration tests. In order to successfully penetrate the computing system's security measurements, preexisting fingerprinting methods are described and the paradigm…

Exponential growth in embedded systems is driving the research imperative to develop fuzzers to automate firmware testing to uncover software bugs and security vulnerabilities. But, employing fuzzing techniques in this context present a…

Automatic test generation typically aims to generate inputs that explore new paths in the program under test in order to find bugs. Existing work has, therefore, focused on guiding the exploration toward program parts that are more likely…

Following the advent of the American Fuzzy Lop (AFL), fuzzing had a surge in popularity, and modern day fuzzers range from simple blackbox random input generators to complex whitebox concolic frameworks that are capable of deep program…

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…

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…

Since the advent of AFL, the use of mutational, feedback directed, grey-box fuzzers has become critical in the automated detection of security vulnerabilities. A great deal of research currently goes into their optimisation, including…

PHP, a dominant scripting language in web development, powers a vast range of websites, from personal blogs to major platforms. While existing research primarily focuses on PHP application-level security issues like code injection, memory…

Cyber-physical systems (CPSs) in critical infrastructure face a pervasive threat from attackers, motivating research into a variety of countermeasures for securing them. Assessing the effectiveness of these countermeasures is challenging,…

Few-shot learning is challenging due to the limited data and labels. Existing algorithms usually resolve this problem by pre-training the model with a considerable amount of annotated data which shares knowledge with the target domain.…

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…

In the evolving landscape of integrated circuit (IC) design, the increasing complexity of modern processors and intellectual property (IP) cores has introduced new challenges in ensuring design correctness and security. The recent…

Deep learning powers critical applications such as autonomous driving, healthcare, and finance, where the correctness of underlying libraries is essential. Bugs in widely used deep learning APIs can propagate to downstream systems, causing…

Fuzzing -- testing programs with random inputs -- has become the prime technique to detect bugs and vulnerabilities in programs. To generate inputs that cover new functionality, fuzzers require execution feedback from the program -- for…

Coverage-guided fuzzers are powerful automated bug-finding tools. They mutate program inputs, observe coverage, and save any input that hits an unexplored path for future mutation. Unfortunately, without knowledge of input formats--for…

Vulnerable software represents a tremendous threat to modern information systems. Vulnerabilities in widespread applications may be used to spread malware, steal money and conduct target attacks. To address this problem, developers and…

Modern fuzzers scale to large, real-world software but often fail to exercise the program states developers consider most fragile or security-critical. Such states are typically deep in the execution space, gated by preconditions, or…

Fuzzing and symbolic execution are popular techniques for finding vulnerabilities and generating test-cases for programs. Fuzzing, a blackbox method that mutates seed input values, is generally incapable of generating diverse inputs that…