[38;5;12m                                                                                [39m[38;2;255;187;0m[1m[4mAwesome Fuzzing [0m[38;5;14m[1m[4m![0m[38;2;255;187;0m[1m[4mAwesome[0m[38;5;14m[1m[4m (https://awesome.re/badge.svg)[0m[38;2;255;187;0m[1m[4m (https://awesome.re)[0m

[38;5;11m[1m▐[0m[38;5;12m [39m[38;5;14m[1mFuzzing[0m[38;5;12m [39m[38;5;12m(https://en.wikipedia.org/wiki/Fuzzing)[39m[38;5;12m [39m[38;5;12mor[39m[38;5;12m [39m[38;5;12mfuzz[39m[38;5;12m [39m[38;5;12mtesting[39m[38;5;12m [39m[38;5;12mis[39m[38;5;12m [39m[38;5;12man[39m[38;5;12m [39m[38;5;12mautomated[39m[38;5;12m [39m[38;5;12msoftware[39m[38;5;12m [39m[38;5;12mtesting[39m[38;5;12m [39m[38;5;12mtechnique[39m[38;5;12m [39m[38;5;12mthat[39m[38;5;12m [39m[38;5;12minvolves[39m[38;5;12m [39m[38;5;12mproviding[39m[38;5;12m [39m[38;5;12minvalid,[39m[38;5;12m [39m[38;5;12munexpected,[39m[38;5;12m [39m[38;5;12mor[39m[38;5;12m [39m[38;5;12mrandom[39m[38;5;12m [39m[38;5;12mdata[39m[38;5;12m [39m[38;5;12mas[39m[38;5;12m [39m[38;5;12minputs[39m[38;5;12m [39m[38;5;12mto[39m[38;5;12m [39m[38;5;12ma[39m[38;5;12m [39m[38;5;12mcomputer[39m[38;5;12m [39m[38;5;12mprogram.[39m[38;5;12m [39m[38;5;12mThe[39m[38;5;12m [39m[38;5;12mprogram[39m[38;5;12m [39m[38;5;12mis[39m[38;5;12m [39m[38;5;12mthen[39m[38;5;12m [39m[38;5;12mmonitored[39m[38;5;12m [39m[38;5;12mfor[39m[38;5;12m [39m
[38;5;11m[1m▐[0m[38;5;12m [39m[38;5;12mexceptions[39m[38;5;12m [39m[38;5;12msuch[39m[38;5;12m [39m[38;5;12mas[39m[38;5;12m [39m[38;5;12mcrashes,[39m[38;5;12m [39m[38;5;12mfailing[39m[38;5;12m [39m[38;5;12mbuilt-in[39m[38;5;12m [39m[38;5;12mcode[39m[38;5;12m [39m[38;5;12massertions,[39m[38;5;12m [39m[38;5;12mor[39m[38;5;12m [39m[38;5;12mpotential[39m[38;5;12m [39m[38;5;12mmemory[39m[38;5;12m [39m[38;5;12mleaks.[39m[38;5;12m [39m[38;5;12mTypically,[39m[38;5;12m [39m[38;5;12mfuzzers[39m[38;5;12m [39m[38;5;12mare[39m[38;5;12m [39m[38;5;12mused[39m[38;5;12m [39m[38;5;12mto[39m[38;5;12m [39m[38;5;12mtest[39m[38;5;12m [39m[38;5;12mprograms[39m[38;5;12m [39m[38;5;12mthat[39m[38;5;12m [39m[38;5;12mtake[39m[38;5;12m [39m[38;5;12mstructured[39m[38;5;12m [39m[38;5;12minputs.[39m[38;5;12m [39m

[38;5;12mA curated list of references to awesome Fuzzing for security testing. Additionally there is a collection of freely available academic papers, tools and so on.[39m

[38;5;12mYour favorite tool or your own paper is not listed? Fork and create a Pull Request to add it![39m


[38;2;255;187;0m[4mContents[0m

[38;5;12m- [39m[38;5;14m[1mBooks[0m[38;5;12m (#books)[39m
[38;5;12m- [39m[38;5;14m[1mPapers[0m[38;5;12m (#papers)[39m
[38;5;12m- [39m[38;5;14m[1mTools[0m[38;5;12m (#tools)[39m
[38;5;12m- [39m[38;5;14m[1mPlatform[0m[38;5;12m (#platform)[39m


[38;2;255;187;0m[4mBooks[0m
[38;5;12m- [39m[38;5;14m[1mFuzzing-101[0m[38;5;12m (https://github.com/antonio-morales/Fuzzing101)[39m
[38;5;12m- [39m[38;5;14m[1mThe Fuzzing Book[0m[38;5;12m (https://www.fuzzingbook.org/) (2019)[39m
[38;5;12m- [39m[38;5;14m[1mThe Art, Science, and Engineering of Fuzzing: A Survey[0m[38;5;12m (https://ieeexplore.ieee.org/document/8863940) (2019) - [39m
[38;5;12mActually, this document is a paper, but it contains more important and essential content than any other book.[39m
[38;5;12m- [39m[38;5;14m[1mFuzzing for Software Security Testing and Quality Assurance, 2nd Edition[0m[38;5;12m (https://www.amazon.com/Fuzzing-Software-Security-Testing-Assurance/dp/1608078507/) (2018)[39m
[38;5;12m- [39m[38;5;14m[1mFuzzing: Brute Force Vulnerability Discovery, 1st Edition[0m[38;5;12m (https://www.amazon.com/Fuzzing-Brute-Force-Vulnerability-Discovery/dp/0321446119/) (2007)[39m
[38;5;12m- [39m[38;5;14m[1mOpen Source Fuzzing Tools, 1st Edition[0m[38;5;12m (https://www.amazon.com/Open-Source-Fuzzing-Tools-Rathaus/dp/1597491950/) (2007)[39m


[38;2;255;187;0m[4mTalks[0m
[38;5;12m- [39m[38;5;14m[1mFuzzing Labs - Patrick Ventuzelo[0m[38;5;12m (https://www.youtube.com/channel/UCGD1Qt2jgnFRjrfAITGdNfQ), Youtube[39m
[38;5;12m- [39m[38;5;14m[1mEffective File Format Fuzzing[0m[38;5;12m (https://youtu.be/qTTwqFRD1H8), Black Hat Europe 2016[39m
[38;5;12m- [39m[38;5;14m[1mAdventures in Fuzzing[0m[38;5;12m (https://www.youtube.com/watch?v=SngK4W4tVc0), NYU Talk 2018[39m
[38;5;12m- [39m[38;5;14m[1mFuzzing with AFL[0m[38;5;12m (https://www.youtube.com/watch?v=DFQT1YxvpDo), NDC Conferences 2018[39m

[38;2;255;187;0m[4mPapers[0m
[38;5;12mTo achieve a well-defined scope, I have chosen to include publications on fuzzing in the last proceedings of 4[39m
[38;5;12mtop major security conferences and others from Jan 2008 to Jul 2019.[39m
[38;5;12mIt includes (i) Network and Distributed System Security Symposium (NDSS), (ii) IEEE Symposium on[39m
[38;5;12mSecurity and Privacy (S&P), (iii) USENIX Security Symposium (USEC), and (iv) ACM Conference on Computer and Communications Security (CCS).[39m


[38;2;255;187;0m[4mThe Network and Distributed System Security Symposium (NDSS)[0m
[38;5;12m- [39m[38;5;14m[1mSemantic-Informed Driver Fuzzing Without Both the Hardware Devices and the Emulators, 2022[0m[38;5;12m (https://www.ndss-symposium.org/wp-content/uploads/2022-345-paper.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mMobFuzz: Adaptive Multi-objective Optimization in Gray-box Fuzzing, 2022[0m[38;5;12m (https://www.ndss-symposium.org/wp-content/uploads/2022-314-paper.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mContext-Sensitive and Directional Concurrency Fuzzing for Data-Race Detection, 2022[0m[38;5;12m (https://www.ndss-symposium.org/wp-content/uploads/2022-296-paper.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mEMS: History-Driven Mutation for Coverage-based Fuzzing, 2022[0m[38;5;12m (https://www.ndss-symposium.org/wp-content/uploads/2022-162-paper.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mWINNIE : Fuzzing Windows Applications with Harness Synthesis and Fast Cloning, 2021[0m[38;5;12m (https://taesoo.kim/pubs/2021/jung:winnie.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mReinforcement Learning-based Hierarchical Seed Scheduling for Greybox Fuzzing, 2021[0m[38;5;12m (https://www.cs.ucr.edu/~heng/pubs/afl-hier.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mPGFUZZ: Policy-Guided Fuzzing for Robotic Vehicles, 2021[0m[38;5;12m (https://beerkay.github.io/papers/Berkay2021PGFuzzNDSS.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mFavocado: Fuzzing Binding Code of JavaScript Engines Using Semantically Correct Test Cases, 2021[0m[38;5;12m (https://www.ndss-symposium.org/wp-content/uploads/ndss2021_6A-2_24224_paper.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mHFL: Hybrid Fuzzing on the Linux Kernel, 2020[0m[38;5;12m (https://www.unexploitable.systems/publication/kimhfl/)[39m
[38;5;12m-[39m[38;5;12m [39m[38;5;14m[1mHotFuzz:[0m[38;5;14m[1m [0m[38;5;14m[1mDiscovering[0m[38;5;14m[1m [0m[38;5;14m[1mAlgorithmic[0m[38;5;14m[1m [0m[38;5;14m[1mDenial-of-Service[0m[38;5;14m[1m [0m[38;5;14m[1mVulnerabilities[0m[38;5;14m[1m [0m[38;5;14m[1mThrough[0m[38;5;14m[1m [0m[38;5;14m[1mGuided[0m[38;5;14m[1m [0m[38;5;14m[1mMicro-Fuzzing,[0m[38;5;14m[1m [0m[38;5;14m[1m2020[0m[38;5;12m [39m
[38;5;12m(https://www.researchgate.net/publication/339164746_HotFuzz_Discovering_Algorithmic_Denial-of-Service_Vulnerabilities_Through_Guided_Micro-Fuzzing)[39m
[38;5;12m- [39m[38;5;14m[1mHYPER-CUBE: High-Dimensional Hypervisor Fuzzing, 2020[0m[38;5;12m (https://www.syssec.ruhr-uni-bochum.de/media/emma/veroeffentlichungen/2020/02/07/Hyper-Cube-NDSS20.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mNot All Coverage Measurements Are Equal: Fuzzing by Coverage Accounting for Input Prioritization, 2020[0m[38;5;12m (https://www.ndss-symposium.org/wp-content/uploads/2020/02/24422.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mCodeAlchemist: Semantics-Aware Code Generation to Find Vulnerabilities in JavaScript Engines, 2019[0m[38;5;12m (https://daramg.gift/paper/han-ndss2019.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mPeriScope: An Effective Probing and Fuzzing Framework for the Hardware-OS Boundary, 2019[0m[38;5;12m (https://people.cs.kuleuven.be/~stijn.volckaert/papers/2019_NDSS_PeriScope.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mREDQUEEN: Fuzzing with Input-to-State Correspondence, 2019[0m[38;5;12m (https://www.syssec.ruhr-uni-bochum.de/media/emma/veroeffentlichungen/2018/12/17/NDSS19-Redqueen.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mSend Hardest Problems My Way: Probabilistic Path Prioritization for Hybrid Fuzzing, 2019[0m[38;5;12m (https://www.cs.ucr.edu/~heng/pubs/digfuzz_ndss19.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mLife after Speech Recognition: Fuzzing Semantic Misinterpretation for Voice Assistant Applications, 2019[0m[38;5;12m (https://www.ndss-symposium.org/wp-content/uploads/2019/02/ndss2019_08-4_Zhang_paper.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mINSTRIM: Lightweight Instrumentation for Coverage-guided Fuzzing, 2018[0m[38;5;12m (https://www.ndss-symposium.org/wp-content/uploads/2018/07/bar2018_14_Hsu_paper.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mIoTFuzzer: Discovering Memory Corruptions in IoT Through App-based Fuzzing, 2018[0m[38;5;12m (http://wp.internetsociety.org/ndss/wp-content/uploads/sites/25/2018/02/ndss2018_01A-1_Chen_paper.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mWhat You Corrupt Is Not What You Crash: Challenges in Fuzzing Embedded Devices, 2018[0m[38;5;12m (http://s3.eurecom.fr/docs/ndss18_muench.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mEnhancing Memory Error Detection for Large-Scale Applications and Fuzz Testing, 2018[0m[38;5;12m (https://lifeasageek.github.io/papers/han:meds.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mVuzzer: Application-aware evolutionary fuzzing, 2017[0m[38;5;12m (https://www.ndss-symposium.org/ndss2017/ndss-2017-programme/vuzzer-application-aware-evolutionary-fuzzing/)[39m
[38;5;12m- [39m[38;5;14m[1mDELTA: A Security Assessment Framework for Software-Defined Networks, 2017[0m[38;5;12m (https://www.ndss-symposium.org/wp-content/uploads/2017/09/ndss201702A-1LeePaper.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mDriller: Augmenting Fuzzing Through Selective Symbolic Execution, 2016[0m[38;5;12m (https://cancer.shtech.org/wiki/uploads/2016---NDSS---driller-augmenting-fuzzing-through-selective-symbolic-execution.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mAutomated Whitebox Fuzz Testing, 2008[0m[38;5;12m (https://www.ndss-symposium.org/wp-content/uploads/2017/09/Automated-Whitebox-Fuzz-Testing-paper-Patrice-Godefroid.pdf)[39m


[38;2;255;187;0m[4mIEEE Symposium on Security and Privacy (IEEE S&P)[0m
[38;5;12m- [39m[38;5;14m[1mPATA: Fuzzing with Path Aware Taint Analysis, 2022[0m[38;5;12m (http://www.wingtecher.com/themes/WingTecherResearch/assets/papers/sp22.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mJigsaw: Efficient and Scalable Path Constraints Fuzzing, 2022[0m[38;5;12m (https://www.cs.ucr.edu/~csong/oakland22-jigsaw.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mFuzzUSB: Hybrid Stateful Fuzzing of USB Gadget Stacks, 2022[0m[38;5;12m (https://github.com/purseclab/fuzzusb/blob/main/paper/fuzzusb.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mEffective Seed Scheduling for Fuzzing with Graph Centrality Analysis, 2022[0m[38;5;12m (https://arxiv.org/pdf/2203.12064.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mBEACON : Directed Grey-Box Fuzzing with Provable Path Pruning, 2022[0m[38;5;12m (https://qingkaishi.github.io/public_pdfs/SP22.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mSTOCHFUZZ: Sound and Cost-effective Fuzzing of Stripped Binaries by Incremental and Stochastic Rewriting, 2021[0m[38;5;12m (https://www.cs.purdue.edu/homes/zhan3299/res/SP21b.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mOne Engine to Fuzz 'em All: Generic Language Processor Testing with Semantic Validation, 2021[0m[38;5;12m (https://huhong789.github.io/papers/polyglot-oakland2021.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mNTFUZZ: Enabling Type-Aware Kernel Fuzzing on Windows with Static Binary Analysis, 2021[0m[38;5;12m (https://softsec.kaist.ac.kr/~jschoi/data/oakland2021.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mDIFUZZRTL: Differential Fuzz Testing to Find CPU Bugs, 2021[0m[38;5;12m (https://lifeasageek.github.io/papers/jaewon-difuzzrtl.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mDIANE: Identifying Fuzzing Triggers in Apps to Generate Under-constrained Inputs for IoT Devices, 2021[0m[38;5;12m (https://conand.me/publications/redini-diane-2021.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mFuzzing JavaScript Engines with Aspect-preserving Mutation, 2020[0m[38;5;12m (https://jakkdu.github.io/pubs/2020/park:die.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mIJON: Exploring Deep State Spaces via Fuzzing, 2020[0m[38;5;12m (https://www.syssec.ruhr-uni-bochum.de/media/emma/veroeffentlichungen/2020/02/27/IJON-Oakland20.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mKrace: Data Race Fuzzing for Kernel File Systems, 2020[0m[38;5;12m (https://www.cc.gatech.edu/~mxu80/pubs/xu:krace.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mPangolin:Incremental Hybrid Fuzzing with Polyhedral Path Abstraction, 2020[0m[38;5;12m (https://qingkaishi.github.io/public_pdfs/SP2020.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mRetroWrite: Statically Instrumenting COTS Binaries for Fuzzing and Sanitization, 2020[0m[38;5;12m (https://www.semanticscholar.org/paper/RetroWrite%3A-Statically-Instrumenting-COTS-Binaries-Dinesh-Burow/845cafb153b0e4b9943c6d9b6a7e42c14845a0d6)[39m
[38;5;12m- [39m[38;5;14m[1mFull-speed Fuzzing: Reducing Fuzzing Overhead through Coverage-guided Tracing, 2019[0m[38;5;12m (https://www.computer.org/csdl/proceedings-article/sp/2019/666000b122/19skgbGVFEQ)[39m
[38;5;12m- [39m[38;5;14m[1mFuzzing File Systems via Two-Dimensional Input Space Exploration, 2019[0m[38;5;12m (https://www.computer.org/csdl/proceedings-article/sp/2019/666000a594/19skfLYOpaw)[39m
[38;5;12m- [39m[38;5;14m[1mNEUZZ: Efficient Fuzzing with Neural Program Smoothing, 2019[0m[38;5;12m (https://www.computer.org/csdl/proceedings-article/sp/2019/666000a900/19skg5XghG0)[39m
[38;5;12m- [39m[38;5;14m[1mRazzer: Finding Kernel Race Bugs through Fuzzing, 2019[0m[38;5;12m (https://www.computer.org/csdl/proceedings-article/sp/2019/666000a296/19skfwZLirm)[39m
[38;5;12m- [39m[38;5;14m[1mAngora: Efficient Fuzzing by Principled Search, 2018[0m[38;5;12m (http://web.cs.ucdavis.edu/~hchen/paper/chen2018angora.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mCollAFL: Path Sensitive Fuzzing, 2018[0m[38;5;12m (http://chao.100871.net/papers/oakland18.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mT-Fuzz: fuzzing by program transformation, 2018[0m[38;5;12m (https://nebelwelt.net/publications/files/18Oakland.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mSkyfire: Data-Driven Seed Generation for Fuzzing, 2017[0m[38;5;12m (https://www.ieee-security.org/TC/SP2017/papers/42.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mProgram-Adaptive Mutational Fuzzing, 2015[0m[38;5;12m (https://softsec.kaist.ac.kr/~sangkilc/papers/cha-oakland15.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mTaintScope: A checksum-aware directed fuzzing tool for automatic software vulnerability detection, 2010[0m[38;5;12m (https://ieeexplore.ieee.org/abstract/document/5504701)[39m



[38;2;255;187;0m[4mUSENIX Security[0m
[38;5;12m- [39m[38;5;14m[1mStateFuzz: System Call-Based State-Aware Linux Driver Fuzzing, 2022[0m[38;5;12m (https://www.usenix.org/system/files/sec22-zhao-bodong.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mFIXREVERTER: A Realistic Bug Injection Methodology for Benchmarking Fuzz Testing, 2022[0m[38;5;12m (https://www.usenix.org/system/files/sec22-zhang-zenong.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mSGXFuzz: Efficiently Synthesizing Nested Structures for SGX Enclave Fuzzing, 2022[0m[38;5;12m (https://www.usenix.org/system/files/sec22-cloosters.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mAmpFuzz: Fuzzing for Amplification DDoS Vulnerabilities, 2022[0m[38;5;12m (https://www.usenix.org/system/files/sec22-krupp.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mStateful Greybox Fuzzing, 2022[0m[38;5;12m (https://www.usenix.org/system/files/sec22-ba.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mBrakTooth: Causing Havoc on Bluetooth Link Manager via Directed Fuzzing, 2022[0m[38;5;12m (https://www.usenix.org/system/files/sec22-garbelini.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mFuzzing Hardware Like Software, 2022[0m[38;5;12m (https://www.usenix.org/system/files/sec22-trippel.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mDrifuzz: Harvesting Bugs in Device Drivers from Golden Seeds, 2022[0m[38;5;12m (https://www.usenix.org/system/files/sec22-shen-zekun.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mFuzzOrigin: Detecting UXSS vulnerabilities in Browsers through Origin Fuzzing, 2022[0m[38;5;12m (https://www.usenix.org/system/files/sec22-kim.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mTheHuzz: Instruction Fuzzing of Processors Using Golden-Reference Models for Finding Software-Exploitable Vulnerabilities, 2022[0m[38;5;12m (https://www.usenix.org/system/files/sec22-kande.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mMundoFuzz: Hypervisor Fuzzing with Statistical Coverage Testing and Grammar Inference, 2022[0m[38;5;12m (https://www.usenix.org/system/files/sec22-myung.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mFuzzware: Using Precise MMIO Modeling for Effective Firmware Fuzzing, 2022[0m[38;5;12m (https://www.usenix.org/system/files/sec22-scharnowski.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mSyzScope: Revealing High-Risk Security Impacts of Fuzzer-Exposed Bugs in Linux kernel, 2022[0m[38;5;12m (https://www.usenix.org/system/files/sec22-zou.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mMorphuzz: Bending (Input) Space to Fuzz Virtual Devices, 2022[0m[38;5;12m (https://www.usenix.org/system/files/sec22-bulekov.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mBreaking Through Binaries: Compiler-quality Instrumentation for Better Binary-only Fuzzing, 2021[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity21/presentation/nagy)[39m
[38;5;12m- [39m[38;5;14m[1mICSFuzz: Manipulating I/Os and Repurposing Binary Code to Enable Instrumented Fuzzing in ICS Control Applications, 2021[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity21/presentation/tychalas)[39m
[38;5;12m- [39m[38;5;14m[1mAndroid SmartTVs Vulnerability Discovery via Log-Guided Fuzzing, 2021[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity21/presentation/aafer)[39m
[38;5;12m- [39m[38;5;14m[1mConstraint-guided Directed Greybox Fuzzing, 2021[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity21/presentation/lee-gwangmu)[39m
[38;5;12m- [39m[38;5;14m[1mNyx: Greybox Hypervisor Fuzzing using Fast Snapshots and Affine Types, 2021[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity21/presentation/schumilo)[39m
[38;5;12m- [39m[38;5;14m[1mUNIFUZZ: A Holistic and Pragmatic Metrics-Driven Platform for Evaluating Fuzzers, 2021[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity21/presentation/li-yuwei)[39m
[38;5;12m- [39m[38;5;14m[1mFANS: Fuzzing Android Native System Services via Automated Interface Analysis, 2020[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity20/presentation/liu)[39m
[38;5;12m- [39m[38;5;14m[1mAnalysis of DTLS Implementations Using Protocol State Fuzzing, 2020[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity20/presentation/fiterau-brostean)[39m
[38;5;12m- [39m[38;5;14m[1mEcoFuzz: Adaptive Energy-Saving Greybox Fuzzing as a Variant of the Adversarial Multi-Armed Bandit, 2020[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity20/presentation/yue)[39m
[38;5;12m- [39m[38;5;14m[1mFuzzing Error Handling Code using Context-Sensitive Software Fault Injection, 2020[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity20/presentation/jiang)[39m
[38;5;12m- [39m[38;5;14m[1mFuzzGen: Automatic Fuzzer Generation, 2020[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity20/presentation/ispoglou)[39m
[38;5;12m- [39m[38;5;14m[1mParmeSan: Sanitizer-guided Greybox Fuzzing, 2020[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity20/presentation/osterlund)[39m
[38;5;12m- [39m[38;5;14m[1mSpecFuzz: Bringing Spectre-type vulnerabilities to the surface, 2020[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity20/presentation/oleksenko)[39m
[38;5;12m- [39m[38;5;14m[1mFuzzGuard: Filtering out Unreachable Inputs in Directed Grey-box Fuzzing through Deep Learning, 2020[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity20/presentation/zong)[39m
[38;5;12m- [39m[38;5;14m[1mMontage: A Neural Network Language Model-Guided JavaScript Engine Fuzzer, 2020[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity20/presentation/lee-suyoung)[39m
[38;5;12m- [39m[38;5;14m[1mGREYONE: Data Flow Sensitive Fuzzing, 2020[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity20/presentation/gan)[39m
[38;5;12m- [39m[38;5;14m[1mFuzzification: Anti-Fuzzing Techniques, 2019[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity19/presentation/jung)[39m
[38;5;12m- [39m[38;5;14m[1mAntiFuzz: Impeding Fuzzing Audits of Binary Executables, 2019[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity19/presentation/guler)[39m
[38;5;12m- [39m[38;5;14m[1mCharm: Facilitating Dynamic Analysis of Device Drivers of Mobile Systems, 2018[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity18/presentation/talebi)[39m
[38;5;12m- [39m[38;5;14m[1mMoonShine: Optimizing OS Fuzzer Seed Selection with Trace Distillation, 2018[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity18/presentation/pailoor)[39m
[38;5;12m- [39m[38;5;14m[1mQSYM : A Practical Concolic Execution Engine Tailored for Hybrid Fuzzing, 2018[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity18/presentation/yun)[39m
[38;5;12m- [39m[38;5;14m[1mOSS-Fuzz - Google's continuous fuzzing service for open source software, 2017[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity17/technical-sessions/presentation/serebryany)[39m
[38;5;12m- [39m[38;5;14m[1mkAFL: Hardware-Assisted Feedback Fuzzing for OS Kernels, 2017[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity17/technical-sessions/presentation/schumilo)[39m
[38;5;12m- [39m[38;5;14m[1mProtocol State Fuzzing of TLS Implementations, 2015[0m[38;5;12m (https://www.usenix.org/conference/usenixsecurity15/technical-sessions/presentation/de-ruiter)[39m
[38;5;12m- [39m[38;5;14m[1mOptimizing Seed Selection for Fuzzing, 2014[0m[38;5;12m (https://softsec.kaist.ac.kr/~sangkilc/papers/rebert-usenixsec14.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mDowsing for overflows: a guided fuzzer to find buffer boundary violations, 2013[0m[38;5;12m (http://enigma.usenix.org/sites/default/files/sec13_proceedings_interior.pdf#page=57)[39m
[38;5;12m- [39m[38;5;14m[1mFuzzing with Code Fragments, 2012[0m[38;5;12m (https://www.usenix.org/system/files/conference/usenixsecurity12/sec12-final73.pdf)[39m


[38;2;255;187;0m[4mACM Conference on Computer and Communications Security (ACM CCS)[0m
[38;5;12m- [39m[38;5;14m[1mFuzz on the Beach: Fuzzing Solana Smart Contracts, 2023[0m[38;5;12m (https://arxiv.org/pdf/2309.03006.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mNestFuzz: Enhancing Fuzzing with Comprehensive Understanding of Input Processing Logic, 2023[0m[38;5;12m (https://secsys.fudan.edu.cn/_upload/article/files/56/ed/788960544d56a38258aca7d3c8b5/216e599a-d6f6-4308-aa0b-ef45166a8431.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mProfile-Driven System Optimizations for Accelerated Greybox Fuzzing, 2023[0m[38;5;12m (https://users.cs.utah.edu/~snagy/papers/23CCS.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mHopper: Interpretative Fuzzing for Libraries, 2023[0m[38;5;12m (https://arxiv.org/pdf/2309.03496.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mGreybox Fuzzing of Distributed Systems, 2023[0m[38;5;12m (https://arxiv.org/pdf/2305.02601.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mSpecDoctor: Differential Fuzz Testing to Find Transient Execution Vulnerabilities, 2022[0m[38;5;12m (https://compsec.snu.ac.kr/papers/jaewon-specdoctor.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mSFuzz: Slice-based Fuzzing for Real-Time Operating Systems, 2022[0m[38;5;12m (https://huhong789.github.io/papers/chen:sfuzz.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mMC^2: Rigorous and Efficient Directed Greybox Fuzzing, 2022[0m[38;5;12m (https://arxiv.org/pdf/2208.14530.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mLibAFL: A Framework to Build Modular and Reusable Fuzzers, 2022[0m[38;5;12m (https://www.s3.eurecom.fr/docs/ccs22_fioraldi.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mJIT-Picking: Differential Fuzzing of JavaScript Engines, 2022[0m[38;5;12m (https://publications.cispa.saarland/3773/1/2022-CCS-JIT-Fuzzing.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mDriveFuzz: Discovering Autonomous Driving Bugs through Driving Quality-Guided Fuzzing, 2022[0m[38;5;12m (https://chungkim.io/doc/ccs22-drivefuzz.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mSoFi: Reflection-Augmented Fuzzing for JavaScript Engines, 2021[0m[38;5;12m (https://dl.acm.org/doi/pdf/10.1145/3460120.3484823)[39m
[38;5;12m- [39m[38;5;14m[1mT-Reqs: HTTP Request Smuggling with Differential Fuzzing, 2021[0m[38;5;12m (https://bahruz.me/papers/ccs2021treqs.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mV-SHUTTLE: Scalable and Semantics-Aware Hypervisor Fuzzing, 2021[0m[38;5;12m (https://nesa.zju.edu.cn/download/ppt/pgn_slides_V-SHUTTLE.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mSame Coverage, Less Bloat: Accelerating Binary-only Fuzzing with Coverage-preserving Coverage-guided Tracing, 2021[0m[38;5;12m (https://people.cs.vt.edu/snagy2/papers/21CCS.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mHyperFuzzer: An Efficient Hybrid Fuzzer For Virtual CPUs, 2021[0m[38;5;12m (https://www.microsoft.com/en-us/research/uploads/prod/2021/09/hyperfuzzer-ccs21.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mRegression Greybox Fuzzing, 2021[0m[38;5;12m (https://mboehme.github.io/paper/CCS21.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mHardware Support to Improve Fuzzing Performance and Precision, 2021[0m[38;5;12m (https://gts3.org/assets/papers/2021/ding:snap.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mSNIPUZZ: Black-box Fuzzing of IoT Firmware via Message Snippet Inference, 2021[0m[38;5;12m (https://arxiv.org/pdf/2105.05445.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mFREEDOM: Engineering a State-of-the-Art DOM Fuzzer, 2020[0m[38;5;12m (https://gts3.org/assets/papers/2020/xu:freedom.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mIntriguer: Field-Level Constraint Solving for Hybrid Fuzzing, 2019[0m[38;5;12m (https://dl.acm.org/citation.cfm?id=3354249)[39m
[38;5;12m- [39m[38;5;14m[1mLearning to Fuzz from Symbolic Execution with Application to Smart Contracts, 2019[0m[38;5;12m (https://files.sri.inf.ethz.ch/website/papers/ccs19-ilf.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mMatryoshka: fuzzing deeply nested branches, 2019[0m[38;5;12m (https://web.cs.ucdavis.edu/~hchen/paper/chen2019matryoshka.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mEvaluating Fuzz Testing, 2018[0m[38;5;12m (http://www.cs.umd.edu/~mwh/papers/fuzzeval.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mHawkeye: Towards a Desired Directed Grey-box Fuzzer, 2018[0m[38;5;12m (https://chenbihuan.github.io/paper/ccs18-chen-hawkeye.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mIMF: Inferred Model-based Fuzzer, 2017[0m[38;5;12m (http://daramg.gift/paper/han-ccs2017.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mSemFuzz: Semantics-based Automatic Generation of Proof-of-Concept Exploits, 2017[0m[38;5;12m (https://www.informatics.indiana.edu/xw7/papers/p2139-you.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mAFL-based Fuzzing for Java with Kelinci, 2017[0m[38;5;12m (https://dl.acm.org/citation.cfm?id=3138820)[39m
[38;5;12m- [39m[38;5;14m[1mDesigning New Operating Primitives to Improve Fuzzing Performance, 2017[0m[38;5;12m (http://iisp.gatech.edu/sites/default/files/images/designing_new_operating_primitives_to_improve_fuzzing_performance_vt.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mDirected Greybox Fuzzing, 2017[0m[38;5;12m (https://dl.acm.org/citation.cfm?id=3134020)[39m
[38;5;12m- [39m[38;5;14m[1mSlowFuzz: Automated Domain-Independent Detection of Algorithmic Complexity Vulnerabilities, 2017[0m[38;5;12m (https://arxiv.org/pdf/1708.08437.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mDIFUZE: Interface Aware Fuzzing for Kernel Drivers, 2017[0m[38;5;12m (https://acmccs.github.io/papers/p2123-corinaA.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mSystematic Fuzzing and Testing of TLS Libraries, 2016[0m[38;5;12m (https://www.nds.rub.de/media/nds/veroeffentlichungen/2016/10/19/tls-attacker-ccs16.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mCoverage-based Greybox Fuzzing as Markov Chain, 2016[0m[38;5;12m (https://ieeexplore.ieee.org/abstract/document/8233151)[39m
[38;5;12m- [39m[38;5;14m[1meFuzz: A Fuzzer for DLMS/COSEM Electricity Meters, 2016[0m[38;5;12m (http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.817.5616&rep=rep1&type=pdf)[39m
[38;5;12m- [39m[38;5;14m[1mScheduling Black-box Mutational Fuzzing, 2013[0m[38;5;12m (https://softsec.kaist.ac.kr/~sangkilc/papers/woo-ccs13.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mTaming compiler fuzzers, 2013[0m[38;5;12m (https://www.cs.utah.edu/~regehr/papers/pldi13.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mSAGE: whitebox fuzzing for security testing, 2012[0m[38;5;12m (https://dl.acm.org/citation.cfm?id=2094081)[39m
[38;5;12m- [39m[38;5;14m[1mGrammar-based whitebox fuzzing, 2008[0m[38;5;12m (https://dl.acm.org/citation.cfm?id=1375607)[39m
[38;5;12m- [39m[38;5;14m[1mTaint-based directed whitebox fuzzing, 2009[0m[38;5;12m (https://dl.acm.org/citation.cfm?id=1555061)[39m


[38;2;255;187;0m[4mArXiv (Fuzzing with Artificial Intelligence & Machine Learning)[0m
[38;5;12m- [39m[38;5;14m[1mMEUZZ: Smart Seed Scheduling for Hybrid Fuzzing, 2020[0m[38;5;12m (https://arxiv.org/abs/2002.08568)[39m
[38;5;12m- [39m[38;5;14m[1mA Review of Machine Learning Applications in Fuzzing, 2019[0m[38;5;12m (https://arxiv.org/abs/1906.11133)[39m
[38;5;12m- [39m[38;5;14m[1mEvolutionary Fuzzing of Android OS Vendor System Services, 2019[0m[38;5;12m (https://arxiv.org/abs/1906.00621)[39m
[38;5;12m- [39m[38;5;14m[1mMoonLight: Effective Fuzzing with Near-Optimal Corpus Distillation, 2019[0m[38;5;12m (https://arxiv.org/abs/1905.13055)[39m
[38;5;12m- [39m[38;5;14m[1mCoverage-Guided Fuzzing for Deep Neural Networks, 2018[0m[38;5;12m (https://arxiv.org/abs/1809.01266)[39m
[38;5;12m- [39m[38;5;14m[1mDLFuzz: Differential Fuzzing Testing of Deep Learning Systems, 2018[0m[38;5;12m (https://arxiv.org/abs/1808.09413)[39m
[38;5;12m- [39m[38;5;14m[1mTensorFuzz: Debugging Neural Networks with Coverage-Guided Fuzzing, 2018[0m[38;5;12m (https://arxiv.org/abs/1807.10875)[39m
[38;5;12m- [39m[38;5;14m[1mNEUZZ: Efficient Fuzzing with Neural Program Learning, 2018[0m[38;5;12m (https://arxiv.org/abs/1807.05620)[39m
[38;5;12m- [39m[38;5;14m[1mEnFuzz: From Ensemble Learning to Ensemble Fuzzing, 2018[0m[38;5;12m (https://arxiv.org/abs/1807.00182)[39m
[38;5;12m- [39m[38;5;14m[1mREST-ler: Automatic Intelligent REST API Fuzzing, 2018[0m[38;5;12m (https://arxiv.org/abs/1806.09739)[39m
[38;5;12m- [39m[38;5;14m[1mDeep Reinforcement Fuzzing, 2018[0m[38;5;12m (https://arxiv.org/abs/1801.04589)[39m
[38;5;12m- [39m[38;5;14m[1mNot all bytes are equal: Neural byte sieve for fuzzing, 2017[0m[38;5;12m (https://arxiv.org/abs/1711.04596)[39m
[38;5;12m- [39m[38;5;14m[1mFaster Fuzzing: Reinitialization with Deep Neural Models, 2017[0m[38;5;12m (https://arxiv.org/abs/1711.02807)[39m
[38;5;12m- [39m[38;5;14m[1mLearn&Fuzz: Machine Learning for Input Fuzzing, 2017[0m[38;5;12m (https://arxiv.org/abs/1701.07232)[39m
[38;5;12m- [39m[38;5;14m[1mComplementing Model Learning with Mutation-Based Fuzzing, 2016[0m[38;5;12m (https://arxiv.org/abs/1611.02429)[39m

[38;2;255;187;0m[4mThe others[0m
[38;5;12m- [39m[38;5;14m[1mFuzzle: Making a Puzzle for Fuzzers, 2022[0m[38;5;12m (https://softsec.kaist.ac.kr/~sangkilc/papers/lee-ase22.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mIfuzzer: An evolutionary interpreter fuzzer using genetic programming, 2016[0m[38;5;12m (https://www.cs.vu.nl/~herbertb/download/papers/ifuzzer-esorics16.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mHybrid fuzz testing: Discovering software bugs via fuzzing and symbolic execution, 2012[0m[38;5;12m (https://pdfs.semanticscholar.org/488a/b1e313f5109153f2c74e3b5d86d41e9b4b71.pdf)[39m
[38;5;12m- [39m[38;5;14m[1mCall-Flow Aware API Fuzz Testing for Security of Windows Systems, 2008[0m[38;5;12m (https://www.computer.org/csdl/proceedings/iccsa/2008/3243/00/3243a019-abs.html)[39m
[38;5;12m- [39m[38;5;14m[1mFeedback-directed random test generation, 2007[0m[38;5;12m (https://dl.acm.org/citation.cfm?id=1248841)[39m
[38;5;12m- [39m[38;5;14m[1mMTF-Storm:a high performance fuzzer for Modbus/TCP, 2018[0m[38;5;12m (https://doi.org/10.1109/ETFA.2018.8502600)[39m
[38;5;12m- [39m[38;5;14m[1mA Modbus/TCP Fuzzer for testing internetworked industrial systems, 2015[0m[38;5;12m (https://doi.org/10.1109/ETFA.2015.7301400)[39m



[38;2;255;187;0m[4mTools[0m
[38;5;12mInformation[39m[38;5;12m [39m[38;5;12mabout[39m[38;5;12m [39m[38;5;12mthe[39m[38;5;12m [39m[38;5;12mvarious[39m[38;5;12m [39m[38;5;12mopen[39m[38;5;12m [39m[38;5;12msource[39m[38;5;12m [39m[38;5;12mtools[39m[38;5;12m [39m[38;5;12myou[39m[38;5;12m [39m[38;5;12mcan[39m[38;5;12m [39m[38;5;12muse[39m[38;5;12m [39m[38;5;12mto[39m[38;5;12m [39m[38;5;12mleverage[39m[38;5;12m [39m[38;5;12mfuzz[39m[38;5;12m [39m[38;5;12mtesting.[39m[38;5;12m [39m[38;5;12mThe[39m[38;5;12m [39m[38;5;12mitems[39m[38;5;12m [39m[38;5;12min[39m[38;5;12m [39m[38;5;12mthis[39m[38;5;12m [39m[38;5;12msection[39m[38;5;12m [39m[38;5;12mhave[39m[38;5;12m [39m[38;5;12mbeen[39m[38;5;12m [39m[38;5;12morganized[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12mclassified[39m[38;5;12m [39m[38;5;12mbased[39m[38;5;12m [39m[38;5;12mon[39m[38;5;12m [39m[38;5;12mthe[39m[38;5;12m [39m[38;5;12mstandards[39m[38;5;12m [39m[38;5;12mset[39m[38;5;12m [39m[38;5;12mby[39m[38;5;12m [39m[38;5;12mthe[39m[38;5;12m [39m[38;5;12mhttps://fuzzing-survey.org/[39m[38;5;12m [39m[38;5;12mwebsite.[39m[38;5;12m [39m[38;5;12mAlthough[39m[38;5;12m [39m[38;5;12mthere[39m[38;5;12m [39m[38;5;12mare[39m
[38;5;12mcurrently[39m[38;5;12m [39m[38;5;12mmore[39m[38;5;12m [39m[38;5;12mthan[39m[38;5;12m [39m[38;5;12m35[39m[38;5;12m [39m[38;5;12mcategories,[39m[38;5;12m [39m[38;5;12mwe[39m[38;5;12m [39m[38;5;12mhave[39m[38;5;12m [39m[38;5;12mselected[39m[38;5;12m [39m[38;5;12mthe[39m[38;5;12m [39m[38;5;12mmost[39m[38;5;12m [39m[38;5;12mrelevant[39m[38;5;12m [39m[38;5;12mones[39m[38;5;12m [39m[38;5;12mto[39m[38;5;12m [39m[38;5;12mprovide[39m[38;5;12m [39m[38;5;12mefficient[39m[38;5;12m [39m[38;5;12minformation.[39m[38;5;12m [39m[38;5;12mAdditionally,[39m[38;5;12m [39m[38;5;12mitems[39m[38;5;12m [39m[38;5;12mthat[39m[38;5;12m [39m[38;5;12mare[39m[38;5;12m [39m[38;5;12moutdated[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12mdeprecated[39m[38;5;12m [39m[38;5;12mhave[39m[38;5;12m [39m[38;5;12mbeen[39m[38;5;12m [39m[38;5;12mexcluded,[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12monly[39m[38;5;12m [39m[38;5;12mthose[39m[38;5;12m [39m[38;5;12mthat[39m[38;5;12m [39m[38;5;12mare[39m[38;5;12m [39m[38;5;12mcurrently[39m[38;5;12m [39m[38;5;12musable[39m[38;5;12m [39m[38;5;12mare[39m[38;5;12m [39m[38;5;12mlisted.[39m
[38;2;255;187;0m[4mFile[0m
[38;5;12m- [39m[38;5;14m[1mAFL++[0m[38;5;12m (https://github.com/AFLplusplus/AFLplusplus) - AFL++ is a superior fork to Google's AFL - more speed, more and better mutations, more and better instrumentation, custom module support, etc.[39m
[38;5;12m- [39m[38;5;14m[1mAngora[0m[38;5;12m (https://github.com/AngoraFuzzer/Angora) - Angora is a mutation-based coverage guided fuzzer. The main goal of Angora is to increase branch coverage by solving path constraints without symbolic execution.[39m
[38;2;255;187;0m[4mKernel[0m
[38;2;255;187;0m[4mNetwork[0m
[38;2;255;187;0m[4mAPI[0m
[38;5;12m- [39m[38;5;14m[1mIvySyn[0m[38;5;12m (https://gitlab.com/brown-ssl/ivysyn) - IvySyn is a fully-automated framework for discovering memory error vulnerabilities in Deep Learning (DL) frameworks.[39m
[38;5;12m-[39m[38;5;12m [39m[38;5;14m[1mMINER[0m[38;5;12m [39m[38;5;12m(https://github.com/puppet-meteor/MINER)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mMINER[39m[38;5;12m [39m[38;5;12mis[39m[38;5;12m [39m[38;5;12ma[39m[38;5;12m [39m[38;5;12mREST[39m[38;5;12m [39m[38;5;12mAPI[39m[38;5;12m [39m[38;5;12mfuzzer[39m[38;5;12m [39m[38;5;12mthat[39m[38;5;12m [39m[38;5;12mutilizes[39m[38;5;12m [39m[38;5;12mthree[39m[38;5;12m [39m[38;5;12mdata-driven[39m[38;5;12m [39m[38;5;12mdesigns[39m[38;5;12m [39m[38;5;12mworking[39m[38;5;12m [39m[38;5;12mtogether[39m[38;5;12m [39m[38;5;12mto[39m[38;5;12m [39m[38;5;12mguide[39m[38;5;12m [39m[38;5;12mthe[39m[38;5;12m [39m[38;5;12msequence[39m[38;5;12m [39m[38;5;12mgeneration,[39m[38;5;12m [39m[38;5;12mimprove[39m[38;5;12m [39m[38;5;12mthe[39m[38;5;12m [39m[38;5;12mrequest[39m[38;5;12m [39m[38;5;12mgeneration[39m[38;5;12m [39m[38;5;12mquality,[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12mcapture[39m[38;5;12m [39m[38;5;12mthe[39m[38;5;12m [39m[38;5;12munique[39m[38;5;12m [39m
[38;5;12merrors[39m[38;5;12m [39m[38;5;12mcaused[39m[38;5;12m [39m[38;5;12mby[39m[38;5;12m [39m[38;5;12mincorrect[39m[38;5;12m [39m[38;5;12mparameter[39m[38;5;12m [39m[38;5;12musage.[39m
[38;5;12m- [39m[38;5;14m[1mRestTestGen[0m[38;5;12m (https://github.com/SeUniVr/RestTestGen) - RestTestGen is a robust tool and framework designed for automated black-box testing of RESTful web APIs.[39m
[38;5;12m- [39m[38;5;14m[1mGraphFuzz[0m[38;5;12m (https://github.com/ForAllSecure/GraphFuzz) - GraphFuzz is an experimental framework for building structure-aware, library API fuzzers.[39m
[38;5;12m- [39m[38;5;14m[1mMinerva[0m[38;5;12m (https://github.com/ChijinZ/Minerva) - Minerva is a browser fuzzer augmented by API mod-ref relations, aiming to synthesize highly-relevant browser API invocations in each test case.[39m
[38;5;12m- [39m[38;5;14m[1mFANS[0m[38;5;12m (https://github.com/iromise/fans) - FANS is a fuzzing tool for fuzzing Android native system services. It contains four components: interface collector, interface model extractor, dependency inferer, and fuzzer engine.[39m
[38;2;255;187;0m[4mJavaScript[0m
[38;2;255;187;0m[4mFirmware[0m
[38;2;255;187;0m[4mHypervisor[0m
[38;2;255;187;0m[4mCPU[0m
[38;5;12m- [39m[38;5;14m[1mDifuzzRTL[0m[38;5;12m (https://github.com/compsec-snu/difuzz-rtl) - DifuzzRTL is a differential fuzz testing approach for CPU verification. [39m
[38;5;12m- [39m[38;5;14m[1mMorFuzz[0m[38;5;12m (https://github.com/sycuricon/MorFuzz) - MorFuzz is a generic RISC-V processor fuzzing framework that can efficiently detect software triggerable functional bugs.[39m
[38;5;12m- [39m[38;5;14m[1mSpecFuzz[0m[38;5;12m (https://github.com/tudinfse/SpecFuzz) - SpecFuzz is a tool to enable fuzzing for Spectre vulnerabilities[39m
[38;5;12m- [39m[38;5;14m[1mTransynther[0m[38;5;12m (https://github.com/vernamlab/Medusa) - Transynther automatically generates and tests building blocks for Meltdown attacks with various faults and microcode assists.[39m
[38;2;255;187;0m[4mLib[0m
[38;2;255;187;0m[4mWeb[0m
[38;5;12m- [39m[38;5;14m[1mTEFuzz[0m[38;5;12m (https://github.com/seclab-fudan/TEFuzz/) - TEFuzz is a tailored fuzzing-based framework to facilitate the detection and exploitation of template escape bugs.[39m
[38;5;12m- [39m[38;5;14m[1mWitcher[0m[38;5;12m (https://github.com/sefcom/Witcher) - Witcher is a web application fuzzer that utilizes mutational fuzzing to explore web applications and fault escalation to detect command and SQL injection vulnerabilities.[39m
[38;5;12m- [39m[38;5;14m[1mCorbFuzz[0m[38;5;12m (https://github.com/shouc/corbfuzz) - CorbFuzz is a state-aware fuzzer for generating as much reponses from a web application as possible without need of setting up database, etc.[39m
[38;2;255;187;0m[4mDOM[0m
[38;2;255;187;0m[4mArgument[0m
[38;2;255;187;0m[4mBlockchain[0m
[38;5;12m- [39m[38;5;14m[1mFluffy[0m[38;5;12m (https://github.com/snuspl/fluffy) - Fluffy is a multi-transaction differential fuzzer for finding consensus bugs in Ethereum. [39m
[38;5;12m- [39m[38;5;14m[1mLOKI[0m[38;5;12m (https://github.com/ConsensusFuzz/LOKI) - LOKI is a blockchain consensus protocol fuzzing framework that detects the consensus memory related and logic bugs.[39m
[38;2;255;187;0m[4mDBMS[0m
[38;5;12m- [39m[38;5;14m[1mSquirrel[0m[38;5;12m (https://github.com/s3team/Squirrel) - Squirrel is a fuzzer for database managment systems (DBMSs).[39m


[38;2;255;187;0m[4mContribute[0m

[38;5;12mContributions welcome! Read the [39m[38;5;14m[1mcontribution guidelines[0m[38;5;12m (contributing.md) first.[39m


[38;2;255;187;0m[4mLicense[0m

[38;5;14m[1m![0m[38;5;12mCC0[39m[38;5;14m[1m (http://mirrors.creativecommons.org/presskit/buttons/88x31/svg/cc-zero.svg)[0m[38;5;12m (http://creativecommons.org/publicdomain/zero/1.0)[39m

[38;5;12mTo the extent possible under law, cpuu has waived all copyright and[39m
[38;5;12mrelated or neighboring rights to this work.[39m
