Related papers: AFL-ICP: Enhancing Industrial Control Protocol Rel…

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…

Industrial control systems (ICS) are vital to modern infrastructure but increasingly vulnerable to cybersecurity threats, particularly through weaknesses in their communication protocols. This paper presents MALF (Multi-Agent LLM Fuzzing…

Fuzzing has proven to be very effective for discovering certain classes of software flaws, but less effective in helping developers process these discoveries. Conventional crash-based fuzzers lack enough information about failures to…

Industrial control systems (ICSs) are types of cyber-physical systems in which programs, written in languages such as ladder logic or structured text, control industrial processes through sensing and actuating. Given the use of ICSs in…

Coverage-based graybox fuzzer (CGF), such as AFL has gained great success in vulnerability detection thanks to its ease-of-use and bug-finding power. Since some code fragments such as memory allocation are more vulnerable than others,…

Grey-box fuzzers such as American Fuzzy Lop (AFL) are popular tools for finding bugs and potential vulnerabilities in programs. While these fuzzers have been able to find vulnerabilities in many widely used programs, they are not efficient;…

Networked Programmable Logic Controllers (PLCs) are proprietary industrial devices utilized in critical infrastructure that execute control logic applications in complex proprietary runtime environments that provide standardized access to…

Modern compilers, such as LLVM, are complex pieces of software. Due to their complexity, manual testing is unlikely to suffice, yet formal verification is difficult to scale. End-to-end fuzzing can be used, but it has difficulties in…

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…

Traditional database fuzzing techniques primarily focus on syntactic correctness and general SQL structures, leaving critical yet obscure DBMS features, such as system-level modes (e.g., GTID), programmatic constructs (e.g., PROCEDURE),…

Fuzzing is a widely used software security testing technique that is designed to identify vulnerabilities in systems by providing invalid or unexpected input. Continuous fuzzing systems like OSS-FUZZ have been successful in finding security…

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…

Emulation-based fuzzers enable testing binaries without source code, and facilitate testing embedded applications where automated execution on the target hardware architecture is difficult and slow. The instrumentation techniques added to…

Recent research has shown that hardware fuzzers can effectively detect security vulnerabilities in modern processors. However, existing hardware fuzzers do not fuzz well the hard-to-reach design spaces. Consequently, these fuzzers cannot…

Fuzzing is a highly effective automated testing method for uncovering software vulnerabilities. Despite advances in fuzzing techniques, such as coverage-guided greybox fuzzing, many fuzzers struggle with coverage plateaus caused by fuzz…

Softwarization and virtualization in 5G and beyond require rigorous testing against vulnerabilities and unintended emergent behaviors for critical infrastructure and network security assurance. Formal methods operates efficiently in…

The ever-increasing complexity of design specifications for processors and intellectual property (IP) presents a formidable challenge for early bug detection in the modern IC design cycle. The recent advancements in hardware fuzzing have…

Softwarization and virtualization in 5G and beyond necessitate thorough testing to ensure the security of critical infrastructure and networks, requiring the identification of vulnerabilities and unintended emergent behaviors from protocol…

Despite its effectiveness in uncovering software defects, American Fuzzy Lop (AFL), one of the best grey-box fuzzers, is inefficient when fuzz-testing source-unavailable programs. AFL's binary-only fuzzing mode, QEMU-AFL, is typically 2-5X…

Fuzzing is an effective technique for discovering software vulnerabilities by generating random test inputs and executing them against the target program. However, fuzzing large and complex programs remains challenging due to difficulties…