Publications related to Fuzzing

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 ...

Berkeley2023

Arvin: Greybox Fuzzing Using Approximate Dynamic CFG Analysis

Mathias Josef Payer, Sirus Shahini

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) ...

Berkeley2023

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

AIFORE: Smart Fuzzing Based on Automatic Input Format Reverse Engineering

Mathias Josef Payer, Zhiyao Feng, Chunmin Zhang, Ji Shi

Knowledge of a program's input format is essential for effective input generation in fuzzing. Automated input format reverse engineering represents an attractive but challenging approach to learning the format. In this paper, we address several challenges ...

Berkeley2023

VIDEZZO: Dependency-aware Virtual Device Fuzzing

Mathias Josef Payer, Flavio Toffalini, Qiang Liu

A virtual machine interacts with its host environment through virtual devices, driven by virtual device messages, e.g., I/O operations. By issuing crafted messages, an adversary can exploit a vulnerability in a virtual device to escape the virtual machine, ...

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 ...

New York2022

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

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Fuzzing

To Infinity, and Beyond (Coverage)

FISHFUZZ: Catch Deeper Bugs by Throwing Larger Nets

Arvin: Greybox Fuzzing Using Approximate Dynamic CFG Analysis

GLeeFuzz: FuzzingWebGL Through Error Message Guided Mutation

DatAFLow: Toward a Data-Flow-Guided Fuzzer

TEEzz: Fuzzing Trusted Applications on COTS Android Devices

AIFORE: Smart Fuzzing Based on Automatic Input Format Reverse Engineering

VIDEZZO: Dependency-aware Virtual Device Fuzzing

MINERVA: Browser API Fuzzing with Dynamic Mod-Ref Analysis

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

Graph Chatbot

Chat with Graph Search

TEEzz: Fuzzing Trusted Applications on COTS Android Devices

DatAFLow: Toward a Data-Flow-Guided Fuzzer

GLeeFuzz: FuzzingWebGL Through Error Message Guided Mutation

FISHFUZZ: Catch Deeper Bugs by Throwing Larger Nets

To Infinity, and Beyond (Coverage)

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

VIDEZZO: Dependency-aware Virtual Device Fuzzing

Arvin: Greybox Fuzzing Using Approximate Dynamic CFG Analysis

AIFORE: Smart Fuzzing Based on Automatic Input Format Reverse Engineering

MINERVA: Browser API Fuzzing with Dynamic Mod-Ref Analysis