sid321axn/Detection_of_Malicious_URLs
In this project, we have detected the malicious URLs using lexical features and boosted machine learning algorithms
This project helps cybersecurity analysts and IT security professionals automatically identify potentially harmful website links. By analyzing the structure and characters within a raw URL, it determines if the link is safe, a phishing attempt, points to malware, or leads to a defaced site. It takes raw URLs as input and classifies them into these categories, providing quick threat assessment.
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Use this if you need to quickly and automatically classify large lists of URLs to detect potential threats like phishing, malware, or defacements.
Not ideal if you require deep content inspection of a webpage or behavioral analysis beyond the URL itself to determine its safety.
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Last pushed
Aug 19, 2020
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