相关论文: DIAR: Removing Uninteresting Bytes from Seeds in S…

Hardware-level memory vulnerabilities severely threaten computing systems. However, hardware patching is inefficient or difficult postfabrication. We investigate the effectiveness of hardware fuzzing in detecting hardware memory…

The emerging data-intensive applications are increasingly dependent on data-intensive scalable computing (DISC) systems, such as Apache Spark, to process large data. Despite their popularity, DISC applications are hard to test. In recent…

A fuzzer provides randomly generated inputs to a targeted software to expose erroneous behavior. To efficiently detect defects, generated inputs should conform to the structure of the input format and thus, grammars can be used to generate…

The security research on Windows has received little attention in the academic circle. Most of the new methods are usually designed for Linux system, and are difficult to transplant to Windows. Fuzzing for Windows programs always suffering…

This paper introduces Pythia, the first fuzzer that augments grammar-based fuzzing with coverage-guided feedback and a learning-based mutation strategy for stateful REST API fuzzing. Pythia uses a statistical model to learn common usage…

In modern software development, vulnerability detection is crucial due to the inevitability of bugs and vulnerabilities in complex software systems. Effective detection and elimination of these vulnerabilities during the testing phase are…

In recent years, there has been a notable surge in attention towards hardware security, driven by the increasing complexity and integration of processors, SoCs, and third-party IPs aimed at delivering advanced solutions. However, this…

Ensuring the correctness of compiler optimizations is critical, but existing fuzzers struggle to test optimizations effectively. First, most fuzzers use optimization pipelines (heuristics-based, fixed sequences of passes) as their harness.…

Fuzz testing is a crucial component of software security assessment, yet its effectiveness heavily relies on valid fuzz drivers and diverse seed inputs. Recent advancements in Large Language Models (LLMs) offer transformative potential for…

Fuzzing is one of the most popular and widely used techniques to find vulnerabilities in any application. Fuzzers are fast enough, but they still spend a good portion of time to restart a crashed application and then fuzz it from the…

Real-world programs expecting structured inputs often has a format-parsing stage gating the deeper program space. Neither a mutation-based approach nor a generative approach can provide a solution that is effective and scalable. Large…

Correctness and robustness are essential for logic synthesis applications, but they are often only tested with a limited set of benchmarks. Moreover, when the application fails on a large benchmark, the debugging process may be tedious and…

Buffer-overruns are a prevalent vulnerability in software libraries and applications. Fuzz testing is one of the effective techniques to detect vulnerabilities in general. Greybox fuzzers such as AFL automatically generate a sequence of…

Generating the hash values of short subsequences, called seeds, enables quickly identifying similarities between genomic sequences by matching seeds with a single lookup of their hash values. However, these hash values can be used only for…

Fuzzing is an effective bug-finding technique but it struggles with complex systems like JavaScript engines that demand precise grammatical input. Recently, researchers have adopted language models for context-aware mutation in fuzzing to…

Modern processor advancements have introduced security risks, particularly in the form of microarchitectural timing attacks. High-profile attacks such as Meltdown and Spectre have revealed critical flaws, compromising the entire system's…

In company with the data explosion over the past decade, deep neural network (DNN) based software has experienced unprecedented leap and is becoming the key driving force of many novel industrial applications, including many safety-critical…

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…

Side-channel attacks allow an adversary to uncover secret program data by observing the behavior of a program with respect to a resource, such as execution time, consumed memory or response size. Side-channel vulnerabilities are difficult…

Widely observed data scaling laws, in which error falls off as a power of the training size, demonstrate the diminishing returns of unselective data expansion. Hence, data governance is proposed to downsize datasets through pruning…