{"id":21205930,"url":"https://github.com/prmditya/phish-guard","last_synced_at":"2026-05-04T16:38:08.779Z","repository":{"id":261897538,"uuid":"885642775","full_name":"prmditya/phish-guard","owner":"prmditya","description":"URL based phising detector website using machine learning","archived":false,"fork":false,"pushed_at":"2024-12-08T04:19:57.000Z","size":69411,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-09T22:28:21.678Z","etag":null,"topics":["ai","classification","flask","python"],"latest_commit_sha":null,"homepage":"","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/prmditya.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-11-09T02:33:00.000Z","updated_at":"2024-12-20T06:25:00.000Z","dependencies_parsed_at":"2025-01-21T15:39:49.171Z","dependency_job_id":null,"html_url":"https://github.com/prmditya/phish-guard","commit_stats":null,"previous_names":["prmditya/phish-guard"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/prmditya%2Fphish-guard","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/prmditya%2Fphish-guard/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/prmditya%2Fphish-guard/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/prmditya%2Fphish-guard/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/prmditya","download_url":"https://codeload.github.com/prmditya/phish-guard/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243658270,"owners_count":20326467,"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","classification","flask","python"],"created_at":"2024-11-20T20:53:45.973Z","updated_at":"2026-05-04T16:38:08.720Z","avatar_url":"https://github.com/prmditya.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cp align=\"center\"\u003e\n  \u003cimg src=\"./static/asset/title.png\" width=\"600px\"/\u003e\n\u003c/p\u003e\n\n\u003cdiv align=\"center\"\u003e\n\n![License](https://img.shields.io/badge/license-MIT-blue)\n![Contributors](https://img.shields.io/github/contributors/prmditya/phish-guard)\n\n\u003c/div\u003e\n\n\u003cimg src=\"./static/asset/screenshot.png\"\u003e\n\n\u003cbr\u003e\n\nAI Powered Website for identifying phishing website from URL.\n\n## **Table of Contents**\n- [**Table of Contents**](#table-of-contents)\n- [**About the Project**](#about-the-project)\n- [**Features**](#features)\n- [**Technologies Used**](#technologies-used)\n- [**Installation**](#installation)\n  - [Steps](#steps)\n- [**Usage**](#usage)\n- [**License**](#license)\n- [**Contributing**](#contributing)\n- [**Acknowledgments**](#acknowledgments)\n\n---\n\n## **About the Project**\nPhish Guard is a website developed using machine learning to detect phishing websites based on the provided URL. This project was created as part of the final project assignment for the Intelligent Systems course.\n\n---\n\n## **Features**\nHighlight the key features of this project.  \n- **URL Phishing Detection**: Detects whether a given URL is linked to a phishing website using machine learning models.\n- **Real-time Analysis**: Analyzes URLs in real-time and provides instant results on the legitimacy of the website.\n- **User-Friendly Interface**: Offers an easy-to-use interface for users to input URLs and view detection results.\n\n---\n\n## **Technologies Used**\nList the technologies, tools, or frameworks that being used in the project.  \n- [Flask](https://flask.palletsprojects.com/en/stable/) - A lightweight web framework for building web applications in Python. \n- [Scikit-Learn](https://scikit-learn.org/stable/) - A machine learning library for Python, used for building and evaluating the model.\n- [Pandas](https://pandas.pydata.org/docs/getting_started/index.html) - A data manipulation and analysis library used to handle datasets.\n- [Numpy](https://numpy.org/) - A library for numerical computing, used for working with arrays and matrices in the project.\n- [Requests](https://requests.readthedocs.io/en/latest/) - A library for making HTTP requests, if you're fetching website data for analysis.\n- [Google Colab](https://colab.research.google.com/) - A cloud-based platform for running Jupyter notebooks, used for developing and training the machine learning model.\n\n---\n\n## **Installation**\nThis section explain about how to Install or clone and run the project.\n\n### Steps\n1. Clone the repository:\n   ```bash\n   git clone https://github.com/prmditya/phish-guard.git\n   ```\n2. Navigate to the project directory:\n   ```bash\n   cd phish-guard\n   ```\n3. Install dependencies:\n   ```bash\n   pip install -r requirements.txt\n   ```\n4. Run the application:\n   ```bash\n   python run.py\n   ```\n\n---\n\n## **Usage**\n1. Enter a URL into the input form.\n2. Click the \"Analyze\" button.\n3. The result of the identification will appear at the bottom of the page.\n\n---\n\n## **License**\nThis project is licensed under the [MIT License](LICENSE).  \n\n---\n\n## **Contributing**\nContributions are welcome! Follow these steps:  \n1. Fork the repository.  \n2. Create a new branch (`git checkout -b feature-name`).  \n3. Commit your changes (`git commit -m \"Add feature\"`).  \n4. Push to the branch (`git push origin feature-name`).  \n5. Open a pull request.\n\n---\n\n## **Acknowledgments**\nI would like to express my gratitude to the following resources and individuals who contributed to this project:\n\n- The inspiration for the project came from this [Kaggle notebook on URL classification](https://www.kaggle.com/code/busrabetulcavusoglu/urls-classification).\n- I would also like to thank my friends, [Bizzati Hanif R.F](https://github.com/Bizzati), [M. Yusuf Ramadhan](), and [Fatyatulhaqq Diando N](), for their support and assistance throughout the development of this project.\n\n---\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprmditya%2Fphish-guard","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fprmditya%2Fphish-guard","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprmditya%2Fphish-guard/lists"}