Related papers: Socialz: Multi-Feature Social Fuzz Testing

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…

Protocol fuzzing is a scalable and cost-effective technique for identifying security vulnerabilities in deployed Internet of Things devices. During their operational phase, IoT devices often run lightweight servers to handle user…

4G and 5G represent the current cellular communication standards utilized daily by billions of users for various applications. Consequently, ensuring the security of 4G and 5G network implementations is critically important. This paper…

Deep learning (DL) frameworks serve as the backbone for a wide range of artificial intelligence applications. However, bugs within DL frameworks can cascade into critical issues in higher-level applications, jeopardizing reliability and…

Software fuzzing is a strong testing technique that has become the de facto approach for automated software testing and software vulnerability detection in the industry. The random nature of fuzzing makes monitoring and understanding the…

Large Language Models (LLMs) increasingly exhibit over-refusal - erroneously rejecting benign queries due to overly conservative safety measures - a critical functional flaw that undermines their reliability and usability. Current methods…

Autonomous driving has become real; semi-autonomous driving vehicles in an affordable price range are already on the streets, and major automotive vendors are actively developing full self-driving systems to deploy them in this decade.…

This paper presents a scalable, practical approach to quantifying information leaks in software; these errors are often overlooked and downplayed, but can seriously compromise security mechanisms such as address space layout randomisation…

Deep Learning (DL) library bugs affect downstream DL applications, emphasizing the need for reliable systems. Generating valid input programs for fuzzing DL libraries is challenging due to the need for satisfying both language…

Cryptographic protocols form the backbone of modern security systems, yet vulnerabilities persist within their implementations. Traditional testing techniques, including fuzzing, have struggled to effectively identify vulnerabilities in…

The widespread adoption of microservices has fundamentally transformed how modern software systems are designed, deployed, operated and maintained. However, well-known microservice properties (e.g., dynamic scalability and decentralized…

Compilers constitute the foundational root-of-trust in software supply chains; however, their immense complexity inevitably conceals critical defects. Recent research has attempted to leverage historical bugs to design new mutation…

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…

Library fuzzing is essential for hardening the software supply chain, but adopting it at scale remains expensive. Practitioners still spend substantial effort on environment setup, struggle to generate harnesses that respect intricate API…

Taint-style vulnerabilities comprise a majority of fuzzer discovered program faults. These vulnerabilities usually manifest as memory access violations caused by tainted program input. Although fuzzers have helped uncover a majority of…

As autonomous driving systems (ADS) advance towards higher levels of autonomy, orchestrating their safety verification becomes increasingly intricate. This paper unveils ScenarioFuzz, a pioneering scenario-based fuzz testing methodology.…

Code reuse in software development frequently facilitates the spread of vulnerabilities, making the scope of affected software in CVE reports imprecise. Traditional methods primarily focus on identifying reused vulnerability code within…

Fuzz testing has been used to find bugs in programs since the 1990s, but despite decades of dedicated research, there is still no consensus on which fuzzing techniques work best. One reason for this is the paucity of ground truth: bugs in…

SpecFuzz is the first tool that enables dynamic testing for speculative execution vulnerabilities (e.g., Spectre). The key is a novel concept of speculation exposure: The program is instrumented to simulate speculative execution in software…

Testing a program's capability to effectively handling errors is a significant challenge, given that program errors are relatively uncommon. To solve this, Software Fault Injection (SFI)-based fuzzing integrates SFI and traditional fuzzing,…