{"id":15682443,"url":"https://github.com/mohab-sameh/attackbench","last_synced_at":"2026-05-10T19:22:01.813Z","repository":{"id":183800554,"uuid":"630478449","full_name":"mohab-sameh/AttackBench","owner":"mohab-sameh","description":"A workbench to simulate, research, and develop ML-powered Intrusion Detection Systems to prevent next-gen network 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![Language](https://img.shields.io/badge/Language-Python-informational?style=flat\u0026logo=\u003cLOGO_NAME\u003e\u0026logoColor=white\u0026color=2bbc8a) ![IDE](https://img.shields.io/badge/IDE-VSCode-informational?style=flat\u0026logo=\u003cLOGO_NAME\u003e\u0026logoColor=white\u0026color=2bbc8a) ![Platform](https://img.shields.io/badge/Platform-Streamlit-informational?style=flat\u0026logo=\u003cLOGO_NAME\u003e\u0026logoColor=white\u0026color=2bbc8a) ![Models](https://img.shields.io/badge/Models-Sklearn/Tensorflow-informational?style=flat\u0026logo=\u003cLOGO_NAME\u003e\u0026logoColor=white\u0026color=2bbc8a)\n\n\u003ch1 align='center'\u003e AttackBench 🔍\u003c/h1\u003e\n\n![image](https://user-images.githubusercontent.com/37941642/233388228-a15d5d47-c7d0-4cf1-914a-bce094a33ac7.png)\n\n\u003cp align='center'\u003eAttackBench is a workbench for the research and development of Anomaly-Based Intrusion Detection Systems.\u003c/p\u003e\n\u003cbr /\u003e\n\n\n\n\u003ch2\u003eQuick Look 👀\u003c/h2\u003e\n\u003cimg src=\"https://github.com/mohab-sameh/AttackBench/blob/main/assets/demo.gif\" align=\"center\"\u003e\n\n\u003cbr /\u003e\n\n\n\u003ch2\u003eSome Features 📋\u003c/h2\u003e\n\n* Easily develop complete \u0026 usable machine learning and deep learning pipelines 🧠\n* Utilize 3rd Party Datasets (such as NSL-KDD, KDD-99, ISCX-NBXX) 📊\n* Connect and import CSV datasets through your AWS S3 buckets 🗃️\n* Perform Live Packet Capture \u0026 predict network attacks using your developed ML/DL Model! ☢️🔍\n* Export comparative Metrics of executed pipelines 📑\n* Simple and Intuitive GUI 🖥️\n* Cloud-Deployable ☁️\n* Tons of Data exploration, preprocessing, machine learning, and deep learning tools! 💻\n* Cross-Platform usability 💻📱🖥️\n\n\u003cbr /\u003e\n\n\u003ch2\u003eDemo\u003c/h2\u003e\n\nWant to see AttackBench in action?\n\n\u003ca href=\"https://attackbench.streamlit.app/\" target=\"_blank\"\u003e\n\n![AttackBench | Streamlit App](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)\n\n\u003c/a\u003e\n\n\n\u003cbr /\u003e\n\n\u003ch2\u003eTested Platforms 🖥️\u003c/h2\u003e\n\n* Deployed on Windows 10 (20H2), Mac OS 10.14, Ubuntu 18.04/20.04\n* Access through any device with your browser of choice (tested on Firefox, Safari, MS Edge, Chrome, Opera).\n\n\n\n\n\u003cbr /\u003e\n\n\u003ch2\u003eInstallation 📜\u003c/h2\u003e\n\n* Install requirements:\n```\npip install requirements.txt\n```\n\n\n\n\n\u003cbr /\u003e\n\u003ch2\u003eUsage⌨️\u003c/h2\u003e\n\n* Run app:\n```\nstreamlit run app.py\n```\n* Use through your browser of choice. \n\n* Or Try a ready cloud-deployed instance [here]([https://share.streamlit.io/mohab-sameh/anomaly-based-ids-workbench/main/Implementation/app-files/app.py](https://attackbench.streamlit.app/))\n\n\n\n\n\u003cbr /\u003e\n\u003ch2\u003ePacket Capture Dependencies 🔍\u003c/h2\u003e\n\n* Libpcap:\n```\npip install libpcap-dev\n```\n* GCC ([installation instructions](https://linuxize.com/post/how-to-install-gcc-compiler-on-ubuntu-18-04/))\n* KDD Feature extractor ([repo](https://github.com/AI-IDS/kdd99_feature_extractor) or use my [prebuilt repo](https://github.com/mohab-sameh/Kdd99-Feature-Extractor-Prebuilt))\n\n\u003e Note: please make sure the KDD Feature extractor is in the root directory (ex: ~/Kdd99-Feature-Extractor-Prebuilt/kdd99_feature_extractor-master)\n\n\n\n\u003cbr /\u003e\n\n\n\n\u003ch2\u003e \n  Published literature:\n\u003c/h2\u003e\n\n[M. S. Abdel-Wahab, A. M. Neil and A. Atia, \"A Comparative Study of Machine Learning and Deep Learning in Network Anomaly-Based Intrusion Detection Systems,\" 2020 15th International Conference on Computer Engineering and Systems (ICCES), 2020, pp. 1-6, doi: 10.1109/ICCES51560.2020.9334553.](https://ieeexplore.ieee.org/document/9334553)\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmohab-sameh%2Fattackbench","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmohab-sameh%2Fattackbench","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmohab-sameh%2Fattackbench/lists"}