Carlo Maria Negri
Machine Learning based credential code scanner.
Rel. Cataldo Basile, Antonio Lioy. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2020
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Abstract
Data mining in public code platforms such as GitHub, has been widely used to compromise developer’s privacy. Due to inexperience or laziness, a lot of personal secret are left hardcoded in their source code which is then made public. There is no need for hacking skills to exploit this kind of vulnerability, sometimes is easy to find some credentials just using the GitHub search bar. In 2016 Uber had to sustain a massive data leak affecting 57 million customers that revealed sensitive information such as names, email address and phone numbers. The source of the attack was leaked credentials found in a private GitHub repository.
All the existing tools are mostly regular expression based and don't achieve good results in terms of accuracy an low false positive rate
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