oakensheld

stateafl

StateAFL: A Greybox Fuzzer for Stateful Network Servers

aflnet

AFLNet: A Greybox Fuzzer for Network Protocols (https://thuanpv.github.io/publications/AFLNet_ICST20.pdf)

aflnwe

profuzzbench

ProFuzzBench - A Benchmark for Stateful Protocol Fuzzing

TLS-Attacker

TLS-Attacker is a Java-based framework for analyzing TLS libraries. It can be used to manually test TLS clients and servers or as as a software library for more advanced tools.

tlsfuzzer

SSL and TLS protocol test suite and fuzzer

afl-training

Exercises to learn how to fuzz with American Fuzzy Lop

libfuzzer-workshop

Repository for materials of "Modern fuzzing of C/C++ Projects" workshop.

AFL

american fuzzy lop - a security-oriented fuzzer

ml-visuals

🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.

AFLplusplus

The fuzzer afl++ is afl with community patches, qemu 5.1 upgrade, collision-free coverage, enhanced laf-intel & redqueen, AFLfast++ power schedules, MOpt mutators, unicorn_mode, and a lot more!

Fuzzing101

An step by step fuzzing tutorial. A GitHub Security Lab initiative

Encrypted-Traffic-Classification-Models

FlowPic

T. Shapira and Y. Shavitt, "FlowPic: A Generic Representation for Encrypted Traffic Classification and Applications Identification," in IEEE Transactions on Network and Service Management, doi: 10.1109/TNSM.2021.3071441.

Deep-Packet

Pytorch implementation of deep packet: a novel approach for encrypted traffic classification using deep learning

TFE-GNN

WWW'23 Research Paper: TFE-GNN: A Temporal Fusion Encoder Using Graph Neural Networks for Fine-grained Encrypted Traffic Classification

transformer

Transformer: PyTorch Implementation of "Attention Is All You Need"

network_traffic_classification_paper

收集了部分将机器学习应用于网络流量分类的论文