FuzzGen: Automatic Fuzzer Generation

Arvin: Greybox Fuzzing Using Approximate Dynamic CFG Analysis

Fuzzing has emerged as the most broadly used testing technique to discover bugs. Effective fuzzers rely on coverage to prioritize inputs that exercise new program areas. Edge-based code coverage of the Program Under Test (PUT) is the most commonly used cov ...

ASSOC COMPUTING MACHINERY2023

GLeeFuzz: FuzzingWebGL Through Error Message Guided Mutation

Mathias Josef Payer, Hui Peng

WebGL is a set of standardized JavaScript APIs for GPU accelerated graphics. Security of the WebGL interface is paramount because it exposes remote and unsandboxed access to the underlying graphics stack (including the native GL libraries and GPU drivers) ...

Usenix Assoc2023

FISHFUZZ: Catch Deeper Bugs by Throwing Larger Nets

Mathias Josef Payer, Flavio Toffalini, Han Zheng, Yuqing Zhang, Jiayuan Zhang

Fuzzers effectively explore programs to discover bugs. Greybox fuzzers mutate seed inputs and observe their execution. Whenever a seed reaches new behavior (e.g., new code or higher execution frequency), it is stored for further mutation. Greybox fuzzers d ...

Usenix Assoc2023

TEEzz: Fuzzing Trusted Applications on COTS Android Devices

Mathias Josef Payer, Marcel Busch

Security and privacy-sensitive smartphone applications use trusted execution environments (TEEs) to protect sensitive operations from malicious code. By design, TEEs have privileged access to the entire system but expose little to no insight into their inn ...

IEEE COMPUTER SOC2023

MINERVA: Browser API Fuzzing with Dynamic Mod-Ref Analysis

Mathias Josef Payer, Yu Jiang, Chijin Zhou

Browser APIs are essential to the modern web experience. Due to their large number and complexity, they vastly expand the attack surface of browsers. To detect vulnerabilities in these APIs, fuzzers generate test cases with a large amount of random API inv ...

Assoc Computing Machinery2022

One Fuzz Doesn’t Fit All: Optimizing Directed Fuzzing via Target-tailored Program State Restriction

Mathias Josef Payer

Fuzzing is the de-facto default technique to discover software flaws, randomly testing programs to discover crashing test cases. Yet, a particular scenario may only care about specific code regions (for, e.g., bug reproduction, patch or regression testing) ...

ASSOC COMPUTING MACHINERY2022

Interactive Digital Engagement With Visual Artworks and Cultural Artefacts Enhances User Aesthetic Experiences in the Laboratory and Museum

Martin Vetterli, Loïc Arnaud Baboulaz, Christine Mohr, Pierre Gabioud

Digital technologies reshape the way we interact with our environment, including with artworks. Advanced computational imaging solutions allow having extremely high-resolution digital reproductions of artworks outside museums, presumably increasing artwork ...

TAYLOR & FRANCIS INC2022

Seed Selection for Successful Fuzzing

Mathias Josef Payer

Mutation-based greybox fuzzing-unquestionably the most widely-used fuzzing technique-relies on a set of non-crashing seed inputs (a corpus) to bootstrap the bug-finding process. When evaluating a fuzzer, common approaches for constructing this corpus inclu ...

ASSOC COMPUTING MACHINERY2021

The COUGHVID crowdsourcing dataset: A corpus for the study of large-scale cough analysis algorithms

David Atienza Alonso, Tomas Teijeiro Campo, Lara Orlandic

Overview Cough audio signal classification has been successfully used to diagnose a variety of respiratory conditions, and there has been significant interest in leveraging Machine Learning (ML) to provide widespread COVID-19 screening. Th ...

Zenodo2021

FuzzGen: Automatic Fuzzer Generation

Arvin: Greybox Fuzzing Using Approximate Dynamic CFG Analysis

GLeeFuzz: FuzzingWebGL Through Error Message Guided Mutation

FISHFUZZ: Catch Deeper Bugs by Throwing Larger Nets

TEEzz: Fuzzing Trusted Applications on COTS Android Devices

Towards Novel Evaluation Methods for Social Dialog Systems

MINERVA: Browser API Fuzzing with Dynamic Mod-Ref Analysis

One Fuzz Doesn’t Fit All: Optimizing Directed Fuzzing via Target-tailored Program State Restriction

Interactive Digital Engagement With Visual Artworks and Cultural Artefacts Enhances User Aesthetic Experiences in the Laboratory and Museum

Seed Selection for Successful Fuzzing

The COUGHVID crowdsourcing dataset: A corpus for the study of large-scale cough analysis algorithms

Graph Chatbot

Arvin: Greybox Fuzzing Using Approximate Dynamic CFG Analysis

GLeeFuzz: FuzzingWebGL Through Error Message Guided Mutation

FISHFUZZ: Catch Deeper Bugs by Throwing Larger Nets

TEEzz: Fuzzing Trusted Applications on COTS Android Devices

Towards Novel Evaluation Methods for Social Dialog Systems

MINERVA: Browser API Fuzzing with Dynamic Mod-Ref Analysis

One Fuzz Doesn’t Fit All: Optimizing Directed Fuzzing via Target-tailored Program State Restriction

Interactive Digital Engagement With Visual Artworks and Cultural Artefacts Enhances User Aesthetic Experiences in the Laboratory and Museum

Seed Selection for Successful Fuzzing

The COUGHVID crowdsourcing dataset: A corpus for the study of large-scale cough analysis algorithms