JavaScript&Me, A Tool to Support Research into Code Transformation and Browser Security
Susana Lima, Ricardo Morla, João Routar · Proceedings of the 31st ACM International Conference on Information & Knowledge Management · 2022
Doing research into code variations and their applications to browser security is challenging. One of the most important aspects of this research is to choose a relevant dataset on which machine learning algorithms can be applied to yield useful results. Although JavaScript code is widely available on various sources, such as package managers, code hosting platforms, and websites, collecting a large corpus of JavaScript and curating it is not a simple task. We present a novel open-source tool that helps with this task by allowing the automatic and systematic collection, processing, and transformation of JavaScript code. These three steps are performed by independent modules, and each one can be extended to incorporate new features, such as additional code sources, or transformation tools, adding to the flexibility of our tool and expanding its usability. Additionally, we use our tool to create a corpus of around 270k JavaScript files, including regular, minified, and obfuscated code, on which we perform a brief analysis. The conclusions from this analysis show the importance of properly curating a dataset before using it in research tasks, such as machine learning classifiers, reinforcing the relevance of our tool.