Unrestricted file upload (UFU) is a class of web security vulnerabilities that can have a severe impact on web applications if uploaded files are not sufficiently validated or securely handled. A review of related work shows an increased interest in finding new methods to discover such vulnerabilities. However, each publication evaluates its new vulnerability scanner against a different set of artificial or real-world applications available at the time of writing. Thus, we identify the need for a comprehensive testing framework to allow a reproducible comparison between existing and future UFU vulnerability scanners. Our contributions include the File Upload Exploitation Lab (FUEL), which models 15 distinct UFU vulnerabilities in isolated scenarios to enable a reproducible evaluation of UFU scanners' capabilities. The results of evaluating four black-box UFU scanners against FUEL show that no scanner manages to identify all UFU vulnerabilities, leaving real-world websites at risk of compromise due to false negatives. Our work aims to solve this problem by extending an existing UFU scanner with multiple new detection and exploitation techniques, which we call Fuxploider-NG, to increase its accuracy from ~50% to over 90%, thereby surpassing the capabilities of existing UFU scanners and showcasing the importance of FUEL as a UFU vulnerability evaluation framework. To foster open science and future work in this area, we open-source FUEL and Fuxploider-NG.
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