ReACP: A Semi-Automated Framework for Reverse-engineering and Testing of Access Control Policies of Web Applications

This technical report details our a semi-automated framework for the reverseengineering and testing of access control (AC) policies for web-based applications. In practice, AC specifications are often missing or poorly documented, leading to AC vulnerabilities. Our goal is to learn and recover AC policies from implementation, and assess them to find AC issues. Built on top of a suite of security tools, our framework automatically explores a system under test, mines domain input specifications from access request logs, and then, generates and executes more access requests using combinatorial test generation. We apply machine learning on the obtained data to characterise relevant attributes that influence access control to learn policies. Finally, the inferred policies are used for detecting AC issues, being vulnerabilities or implementation errors. We have evaluated our framework on three open-source applications with respect to correctness and completeness. The results are very promising in terms of the quality of inferred policies, more than 94% of them are correct with respect to implemented AC mechanisms. The remaining incorrect policies are mainly due to our unrefined permission classification. Moreover, a careful analysis of these policies has revealed 92 vulnerabilities, many of them are new.