{"id":19537887,"url":"https://github.com/grananqvist/machine-learning-web-application-firewall-and-dataset","last_synced_at":"2025-04-26T15:31:18.935Z","repository":{"id":45209767,"uuid":"87360407","full_name":"grananqvist/Machine-Learning-Web-Application-Firewall-and-Dataset","owner":"grananqvist","description":null,"archived":false,"fork":false,"pushed_at":"2018-02-26T12:13:13.000Z","size":41037,"stargazers_count":60,"open_issues_count":3,"forks_count":22,"subscribers_count":6,"default_branch":"master","last_synced_at":"2023-11-11T16:28:23.066Z","etag":null,"topics":["ai","dataset","firewall","machine-learning","malicious","waf"],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/grananqvist.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2017-04-05T22:00:22.000Z","updated_at":"2023-10-19T04:47:22.000Z","dependencies_parsed_at":"2022-09-05T14:11:55.242Z","dependency_job_id":null,"html_url":"https://github.com/grananqvist/Machine-Learning-Web-Application-Firewall-and-Dataset","commit_stats":null,"previous_names":[],"tags_count":0,"template":null,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/grananqvist%2FMachine-Learning-Web-Application-Firewall-and-Dataset","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/grananqvist%2FMachine-Learning-Web-Application-Firewall-and-Dataset/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/grananqvist%2FMachine-Learning-Web-Application-Firewall-and-Dataset/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/grananqvist%2FMachine-Learning-Web-Application-Firewall-and-Dataset/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/grananqvist","download_url":"https://codeload.github.com/grananqvist/Machine-Learning-Web-Application-Firewall-and-Dataset/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":224038733,"owners_count":17245497,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ai","dataset","firewall","machine-learning","malicious","waf"],"created_at":"2024-11-11T02:29:51.998Z","updated_at":"2024-11-11T02:29:53.338Z","avatar_url":"https://github.com/grananqvist.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Machine learning based web application firewall\n\nMachine learning based Web Application firewall for detection attacks such as SQL injections, XSS and shell script injections. \n\nCourse project for TDA602\nContributors: Filip Granqvist \u0026 Oskar Holmberg\n\nRequirements:\n - Python 3.x\n - Jupyter notebook\n - Python libraries\n   * Pandas\n   * Numpy\n   * Sklearn\n   * matplotlib\n   * seaborn\n   * scipy\n - Node.js (to run demo server)\n\nFollow along our development process in these notebooks:\n - 0_Data_wrangling.ipynb\t(Formating other sources of payload datasets into a common format (don't step through this))\n - 1_Data_cleaning.ipynb\t(Cleaning the data and output into a common .csv file)\n - 2_Data_analysis.ipynb (All analysis, training, evaluation and saving models to pickles (not recommended to step through the training section, takes a long time))\n \n To run notebooks (they can also be read from github):\n 1. Install jupyter notebook\n 2. type in cmd: jupyter notebook \u003cnotebookfile.ipynb\u003e\n 3. step through each part of the notebook using Ctrl+Enter or from the toolbar\n \n \n Plots_technical_background.ipynb contains junk used to create images for the report  \n   \n Demo-server contains a Node.js server with our best classifier (in the form of a .pickle) implemented available for live testing  \n See README.md in demo-server for instructions on how to set up the server  \n   \n images contains images used for the report\n \n data folder contains our malicious and non-malicious data. Also contains trained classifiers in form of .pickle files  \n tfidf_2grams_randomforest.p contains our single best classifier  \n trained_classifiers.p contains all our classifiers along with performance metrics. But this is not the final version, it was too big for github. Download the final version from here: https://1drv.ms/f/s!Aj1zBHCOJiQFgbQwDswBYtpzB1Pulg and replace the old one\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgrananqvist%2Fmachine-learning-web-application-firewall-and-dataset","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgrananqvist%2Fmachine-learning-web-application-firewall-and-dataset","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgrananqvist%2Fmachine-learning-web-application-firewall-and-dataset/lists"}