Awesome Fuzzing
Fuzzing or fuzz
testing is an automated software testing technique that involves
providing invalid, unexpected, or random data as inputs to a computer
program. The program is then monitored for exceptions such as crashes,
failing built-in code assertions, or potential memory leaks. Typically,
fuzzers are used to test programs that take structured inputs.
A curated list of references to awesome Fuzzing for security testing.
Additionally there is a collection of freely available academic papers,
tools and so on.
Your favorite tool or your own paper is not listed? Fork and create a Pull
Request to add it!
Contents
Books
Talks
Papers
To achieve a well-defined scope, I have chosen to include publications on
fuzzing in the last proceedings of 4 top major security conferences and
others from Jan 2008 to Jul 2019. It includes (i) Network and Distributed
System Security Symposium (NDSS), (ii) IEEE Symposium on Security and
Privacy (S&P), (iii) USENIX Security Symposium (USEC), and (iv) ACM
Conference on Computer and Communications Security (CCS).
The Network and Distributed System Security Symposium (NDSS)
-
HFL: Hybrid Fuzzing on the Linux Kernel, 2020
-
HotFuzz: Discovering Algorithmic Denial-of-Service Vulnerabilities
Through Guided Micro-Fuzzing, 2020
-
HYPER-CUBE: High-Dimensional Hypervisor Fuzzing, 2020
-
Not All Coverage Measurements Are Equal: Fuzzing by Coverage
Accounting for Input Prioritization, 2020
-
CodeAlchemist: Semantics-Aware Code Generation to Find
Vulnerabilities in JavaScript Engines, 2019
-
PeriScope: An Effective Probing and Fuzzing Framework for the
Hardware-OS Boundary, 2019
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REDQUEEN: Fuzzing with Input-to-State Correspondence, 2019
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Send Hardest Problems My Way: Probabilistic Path Prioritization for
Hybrid Fuzzing, 2019
-
Life after Speech Recognition: Fuzzing Semantic Misinterpretation for
Voice Assistant Applications, 2019
-
INSTRIM: Lightweight Instrumentation for Coverage-guided Fuzzing,
2018
-
IoTFuzzer: Discovering Memory Corruptions in IoT Through App-based
Fuzzing, 2018
-
What You Corrupt Is Not What You Crash: Challenges in Fuzzing
Embedded Devices, 2018
-
Enhancing Memory Error Detection for Large-Scale Applications and
Fuzz Testing, 2018
-
Vuzzer: Application-aware evolutionary fuzzing, 2017
-
DELTA: A Security Assessment Framework for Software-Defined Networks,
2017
-
Driller: Augmenting Fuzzing Through Selective Symbolic Execution,
2016
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Automated Whitebox Fuzz Testing, 2008
IEEE Symposium on Security and Privacy (IEEE S&P)
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Fuzzing JavaScript Engines with Aspect-preserving Mutation, 2020
-
IJON: Exploring Deep State Spaces via Fuzzing, 2020
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Krace: Data Race Fuzzing for Kernel File Systems, 2020
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Pangolin:Incremental Hybrid Fuzzing with Polyhedral Path Abstraction,
2020
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RetroWrite: Statically Instrumenting COTS Binaries for Fuzzing and
Sanitization, 2020
-
Full-speed Fuzzing: Reducing Fuzzing Overhead through Coverage-guided
Tracing, 2019
-
Fuzzing File Systems via Two-Dimensional Input Space Exploration,
2019
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NEUZZ: Efficient Fuzzing with Neural Program Smoothing, 2019
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Razzer: Finding Kernel Race Bugs through Fuzzing, 2019
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Angora: Efficient Fuzzing by Principled Search, 2018
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CollAFL: Path Sensitive Fuzzing, 2018
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T-Fuzz: fuzzing by program transformation, 2018
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Skyfire: Data-Driven Seed Generation for Fuzzing, 2017
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Program-Adaptive Mutational Fuzzing, 2015
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TaintScope: A checksum-aware directed fuzzing tool for automatic
software vulnerability detection, 2010
USENIX Security
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FANS: Fuzzing Android Native System Services via Automated Interface
Analysis, 2020
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Analysis of DTLS Implementations Using Protocol State Fuzzing,
2020
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EcoFuzz: Adaptive Energy-Saving Greybox Fuzzing as a Variant of the
Adversarial Multi-Armed Bandit, 2020
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Fuzzing Error Handling Code using Context-Sensitive Software Fault
Injection, 2020
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FuzzGen: Automatic Fuzzer Generation, 2020
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ParmeSan: Sanitizer-guided Greybox Fuzzing, 2020
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SpecFuzz: Bringing Spectre-type vulnerabilities to the surface,
2020
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FuzzGuard: Filtering out Unreachable Inputs in Directed Grey-box
Fuzzing through Deep Learning, 2020
-
Montage: A Neural Network Language Model-Guided JavaScript Engine
Fuzzer, 2020
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GREYONE: Data Flow Sensitive Fuzzing, 2020
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Fuzzification: Anti-Fuzzing Techniques, 2019
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AntiFuzz: Impeding Fuzzing Audits of Binary Executables, 2019
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Charm: Facilitating Dynamic Analysis of Device Drivers of Mobile
Systems, 2018
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MoonShine: Optimizing OS Fuzzer Seed Selection with Trace
Distillation, 2018
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QSYM : A Practical Concolic Execution Engine Tailored for Hybrid
Fuzzing, 2018
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OSS-Fuzz - Google’s continuous fuzzing service for open source
software, 2017
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kAFL: Hardware-Assisted Feedback Fuzzing for OS Kernels, 2017
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Protocol State Fuzzing of TLS Implementations, 2015
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Optimizing Seed Selection for Fuzzing, 2014
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Dowsing for overflows: a guided fuzzer to find buffer boundary
violations, 2013
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Fuzzing with Code Fragments, 2012
ACM Conference on Computer and Communications Security (ACM CCS)
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Intriguer: Field-Level Constraint Solving for Hybrid Fuzzing, 2019
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Learning to Fuzz from Symbolic Execution with Application to Smart
Contracts, 2019
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Matryoshka: fuzzing deeply nested branches, 2019
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Evaluating Fuzz Testing, 2018
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Hawkeye: Towards a Desired Directed Grey-box Fuzzer, 2018
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IMF: Inferred Model-based Fuzzer, 2017
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SemFuzz: Semantics-based Automatic Generation of Proof-of-Concept
Exploits, 2017
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AFL-based Fuzzing for Java with Kelinci, 2017
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Designing New Operating Primitives to Improve Fuzzing Performance,
2017
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Directed Greybox Fuzzing, 2017
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SlowFuzz: Automated Domain-Independent Detection of Algorithmic
Complexity Vulnerabilities, 2017
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DIFUZE: Interface Aware Fuzzing for Kernel Drivers, 2017
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Systematic Fuzzing and Testing of TLS Libraries, 2016
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Coverage-based Greybox Fuzzing as Markov Chain, 2016
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eFuzz: A Fuzzer for DLMS/COSEM Electricity Meters, 2016
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Scheduling Black-box Mutational Fuzzing, 2013
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Taming compiler fuzzers, 2013
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SAGE: whitebox fuzzing for security testing, 2012
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Grammar-based whitebox fuzzing, 2008
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Taint-based directed whitebox fuzzing, 2009
ArXiv (Fuzzing with Artificial Intelligence & Machine Learning)
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MEUZZ: Smart Seed Scheduling for Hybrid Fuzzing, 2020
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A Review of Machine Learning Applications in Fuzzing, 2019
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Evolutionary Fuzzing of Android OS Vendor System Services, 2019
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MoonLight: Effective Fuzzing with Near-Optimal Corpus Distillation,
2019
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Coverage-Guided Fuzzing for Deep Neural Networks, 2018
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DLFuzz: Differential Fuzzing Testing of Deep Learning Systems,
2018
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TensorFuzz: Debugging Neural Networks with Coverage-Guided Fuzzing,
2018
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NEUZZ: Efficient Fuzzing with Neural Program Learning, 2018
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EnFuzz: From Ensemble Learning to Ensemble Fuzzing, 2018
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REST-ler: Automatic Intelligent REST API Fuzzing, 2018
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Deep Reinforcement Fuzzing, 2018
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Not all bytes are equal: Neural byte sieve for fuzzing, 2017
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Faster Fuzzing: Reinitialization with Deep Neural Models, 2017
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Learn&Fuzz: Machine Learning for Input Fuzzing, 2017
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Complementing Model Learning with Mutation-Based Fuzzing, 2016
The others
Information about the various open source tools you can use to leverage
fuzz testing. ### General-purpose -
radamsa - A general-purpose
fuzzer. - zzuf - A
transparent application input fuzzer. ### Binary -
American fuzzy lop - A
security-oriented fuzzer that employs a novel type of compile-time
instrumentation and genetic algorithms to automatically discover clean,
interesting test cases that trigger new internal states in the targeted
binary. -
WinAFL - A fork
of AFL for fuzzing Windows binaries. -
libFuzzer - A library
for coverage-guided fuzz testing.
Tutorial from Google.
- Driller - An
implementation of the
driller paper. This implementation was built on top of AFL with angr being used as a
symbolic tracer. -
shellphish fuzzer - A
Python interface to AFL, allowing for easy injection of testcases and
other functionality. -
Eclipser - A
binary-based fuzz testing tool that improves upon classic coverage-based
fuzzing by leveraging a novel technique called grey-box concolic testing.
- Jazzer -
A coverage-guided, in-process fuzzer for the Java Virtual Machine. It is
based on libFuzzer and can be applied directly to compiled applications.
### Web, JavaScript -
jsfunfuzz -
JavaScript engine fuzzers. -
IFuzzer - An
Evolutionary Interpreter Fuzzer Using Genetic Programming. -
domato - DOM
fuzzer from
Google Project Zero.
Blog Post.
- fuzzilli - A
(coverage-)guided Javascript engine fuzzer, written by Samuel Groß. -
CodeAlchemist
- JavaScript engine fuzzer, written by KAIST SoftSec Lab. -
test-each - Repeat
tests using different inputs. -
gremlins.js -
gremlins.js is a monkey testing library written in JavaScript. ### Network
protocol -
dtls-fuzzer -
A Java tool which performs protocol state fuzzing of DTLS servers. -
T-Fuzz - T-Fuzz leverages
a coverage guided fuzzer to generate inputs. -
TLS-Attacker - A
Java-based framework for analyzing TLS libraries. -
DELTA - SDN Security
evaluation framework. -
boofuzz - Network
Protocol Fuzzing for Humans. Documentation is available at
http://boofuzz.readthedocs.io/, including nifty quickstart guides. -
LL-Fuzzer - An automated
NFC fuzzing framework for Android devices. -
tlsfuzzer - A SSL and
TLS protocol test suite and fuzzer. -
TumbleRF - A
framework that orchestrates the application of fuzzing techniques to RF
systems. - PULSAR - A
method for stateful black-box fuzzing of proprietary network protocols. -
SPIKE
- A fuzzer development framework like sulley, a predecessor of sulley. -
PROTOS - Security
testing of protocol implementations. ### Driver -
Charm - A system solution
that facilitates dynamic analysis of device drivers of mobile systems. ##
Platform - certfuzz - It
contains the source code for the CMU CERT Basic Fuzzing Framework (BFF)
and the CERT Failure Observation Engine (FOE). -
Peach Fuzzer Platform
- An automated security testing platform that prevents zero day attacks by
finding vulnerabilities in hardware and software systems. -
Blackhat USA 2018 AFL workshop training materials
- From @wrauner at
Samsung Research. - CI Fuzz -
A CI/CD-agnostic platform for feedback-based fuzz testing of both native
applications and Java web apps.
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License
To the extent possible under law, cpuu has waived all copyright and
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