LegitPhish Dataset

Published: 7 April 2025| Version 1 | DOI: 10.17632/hx4m73v2sf.1
Contributor:
Rachana Potpelwar

Description

The dataset contains 101,219 URLs and 18 features (including the label). Here's a description of each attribute: Phishing (0): 63,678 URLs Legitimate (1): 37,540 URLs These URLs have been sourced from the URLHaus database, scraped from many sites and other well-known repositories malicious websites actively used in phishing attacks. Each entry in this subset has been manually verified and is labeled as a phishing URL, making this dataset highly reliable for identifying harmful web content. The legitimate URLs have been collected from reputable sources such as Wikipedia and Stack Overflow. These websites are known for hosting user-generated content and community discussions, ensuring that the URLs represent safe, legitimate web addresses. The URLs were randomly scraped to ensure diversity in the types of legitimate sites included. Dataset Features: URL: The full web address of each entry, providing the primary feature for analysis. Label: A binary label indicating whether the URL is legitimate (1) or phishing (0). Applications: This dataset is suitable for training and evaluating machine learning models aimed at distinguishing between phishing and legitimate websites. It can be used in a variety of cybersecurity research projects, including URL-based phishing detection, web content analysis, and the development of real-time protection systems. Usage: Researchers can leverage this balanced dataset to develop and test algorithms for identifying phishing websites with high accuracy, using features such as URL structure, and class label attributes. The inclusion of both phishing and legitimate URLs provides a comprehensive basis for creating robust models capable of detecting phishing attempts in diverse online environments. Feature Name Description URL The full URL string. url_length - Total number of characters in the URL. has_ip_address - Binary flag (1/0): whether the URL contains an IP address. dot_count - Number of . characters in the URL. https_flag - Binary flag (1/0): whether the URL uses HTTPS. url_entropy - Shannon entropy of the URL string – higher values indicate more randomness. token_count - Number of tokens/words in the URL. subdomain_count - Number of subdomains in the URL. query_param_count - Number of query parameters (after ?). tld_length - Length of the Top-Level Domain (e.g., "com" = 3). path_length - Length of the path part after the domain. has_hyphen_in_domain Binary flag (1/0): whether the domain contains a hyphen (-). number_of_digits - Total number of numeric characters in the URL. tld_popularity Binary flag (1/0): whether the TLD is popular. suspicious_file_extension Binary flag (1/0): indicates if the URL ends with suspicious extensions (e.g., .exe, .zip). domain_name_length - Length of the domain name. percentage_numeric_chars - Percentage of numeric characters in the URL. ClassLabel Target label: 1 = Legitimate, 0 = Phishing.

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Institutions

Shri Guru Gobind Singhji Institute of Engineering and Technology

Categories

Cybersecurity, Data Analytics

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