{"id":25968929,"url":"https://github.com/vimal007vimal/malicious-url-detection","last_synced_at":"2026-06-10T07:31:44.845Z","repository":{"id":239312393,"uuid":"799186212","full_name":"Vimal007Vimal/Malicious-URL-Detection","owner":"Vimal007Vimal","description":"Our project employs machine learning to pinpoint phishing URLs with 97.4% accuracy, leveraging HTTPS and website traffic as critical indicators. Insights into features like AnchorURL enhance cybersecurity strategies, showcasing the power of AI in combating online threats.","archived":false,"fork":false,"pushed_at":"2024-10-10T05:51:50.000Z","size":313,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-04T22:37:28.109Z","etag":null,"topics":["cybersecurity","https","malicious-url-detection","phishing","python","python3","xgboost-algorithm","xgboost-classifier"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Vimal007Vimal.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-05-11T12:03:15.000Z","updated_at":"2024-11-25T07:31:00.000Z","dependencies_parsed_at":"2025-03-04T22:45:53.143Z","dependency_job_id":null,"html_url":"https://github.com/Vimal007Vimal/Malicious-URL-Detection","commit_stats":null,"previous_names":["vimal007vimal/malicious-url-detection"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Vimal007Vimal/Malicious-URL-Detection","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Vimal007Vimal%2FMalicious-URL-Detection","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Vimal007Vimal%2FMalicious-URL-Detection/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Vimal007Vimal%2FMalicious-URL-Detection/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Vimal007Vimal%2FMalicious-URL-Detection/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Vimal007Vimal","download_url":"https://codeload.github.com/Vimal007Vimal/Malicious-URL-Detection/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Vimal007Vimal%2FMalicious-URL-Detection/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34142637,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-10T02:00:07.152Z","response_time":89,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":["cybersecurity","https","malicious-url-detection","phishing","python","python3","xgboost-algorithm","xgboost-classifier"],"created_at":"2025-03-04T22:35:47.826Z","updated_at":"2026-06-10T07:31:44.830Z","avatar_url":"https://github.com/Vimal007Vimal.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Malicious URL Detection \r\n![image](https://github.com/Vimal007Vimal/Malicious-URL-Detection/assets/144089192/8f4cbfc2-e19a-4a17-a9e6-a1f38f320164)\r\n![image](https://github.com/Vimal007Vimal/Malicious-URL-Detection/assets/144089192/c1c36981-bd17-46c8-85e4-0b478761b28c)\r\n\r\n\r\n## Installation\r\nThe Code is written in Python 3.9 If you don't have Python installed you can find it [here](https://www.python.org/downloads/). If you are using a lower version of Python you can upgrade using the pip package, ensuring you have the latest version of pip. To install the required packages and libraries, run this command in the project directory after [cloning](https://www.howtogeek.com/451360/how-to-clone-a-github-repository/) the repository:\r\n```bash\r\npip install -r requirements.txt\r\n```\r\n\r\n## Directory Tree \r\n```\r\n├── static\r\n│   ├── styles.css\r\n├── templates\r\n│   ├── index.html\r\n├── README.md\r\n├── app.py\r\n├── feature.py\r\n├── phishing.csv\r\n├── requirements.txt\r\n\r\n\r\n```\r\n\r\n## Technologies Used\r\n\r\n[\u003cimg target=\"_blank\" src=\"https://upload.wikimedia.org/wikipedia/commons/3/31/NumPy_logo_2020.svg\" width=200\u003e](https://numpy.org/doc/) [\u003cimg target=\"_blank\" src=\"https://upload.wikimedia.org/wikipedia/commons/e/ed/Pandas_logo.svg\" width=200\u003e](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html)\r\n[\u003cimg target=\"_blank\" src=\"https://upload.wikimedia.org/wikipedia/commons/8/84/Matplotlib_icon.svg\" width=100\u003e](https://matplotlib.org/)\r\n[\u003cimg target=\"_blank\" src=\"https://scikit-learn.org/stable/_static/scikit-learn-logo-small.png\" width=200\u003e](https://scikit-learn.org/stable/) \r\n[\u003cimg target=\"_blank\" src=\"https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcScq-xocLctL07Jy0tpR_p9w0Q42_rK1aAkNfW6sm3ucjFKWML39aaJPgdhadyCnEiK7vw\u0026usqp=CAU\" width=200\u003e](https://flask.palletsprojects.com/en/2.0.x/) \r\n\r\n## Result\r\n\r\nAccuracy of various model used for URL detection\r\n\u003cbr\u003e\r\n\r\n\u003cbr\u003e\r\n\r\n||ML Model|\tAccuracy|  \tf1_score|\tRecall|\tPrecision|\r\n|---|---|---|---|---|---|\r\n0|\tGradient Boosting Classifier|\t0.974|\t0.977|\t0.994|\t0.986|\r\n1|\tCatBoost Classifier|\t        0.972|\t0.975|\t0.994|\t0.989|\r\n2|\tXGBoost Classifier| \t        0.969|\t0.973|\t0.993|\t0.984|\r\n3|\tMulti-layer Perceptron|\t        0.969|\t0.973|\t0.995|\t0.981|\r\n4|\tRandom Forest|\t                0.967|\t0.971|\t0.993|\t0.990|\r\n5|\tSupport Vector Machine|\t        0.964|\t0.968|\t0.980|\t0.965|\r\n6|\tDecision Tree|      \t        0.960|\t0.964|\t0.991|\t0.993|\r\n7|\tK-Nearest Neighbors|        \t0.956|\t0.961|\t0.991|\t0.989|\r\n8|\tLogistic Regression|        \t0.934|\t0.941|\t0.943|\t0.927|\r\n9|\tNaive Bayes Classifier|     \t0.605|\t0.454|\t0.292|\t0.997|\r\n\r\nFeature importance for Malicious URL Detection \r\n\u003cbr\u003e\u003cbr\u003e\r\n![image](https://user-images.githubusercontent.com/79131292/144603941-19044aae-7d7b-4e9a-88a8-6adfd8626f77.png)\r\n\r\nGradient Boosting Classifier currectly classify URL upto 97.4% respective classes and hence reduces the chance of malicious attachments.\r\n\\The final conclusion on the Malicious dataset is that the some feature like \"HTTTPS\", \"AnchorURL\", \"WebsiteTraffic\" have more importance to classify URL is Malicious URL or not.\r\nThe final take away form this project is to explore various machine learning models, perform Exploratory Data Analysis on Malicious dataset and understanding their features.\r\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvimal007vimal%2Fmalicious-url-detection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvimal007vimal%2Fmalicious-url-detection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvimal007vimal%2Fmalicious-url-detection/lists"}