Automatic Detection of Access Control Vulnerabilities via Api Specification Processing

Abstract

Objective. Insecure Direct Object Reference (IDOR) or Broken Object Level Authorization (BOLA) are one of the critical type of access control vulnerabilities for modern applications. As a result, an attacker can bypass authorization checks leading to information leakage, account takeover. Our main research goal was to help an application security architect to optimize security design and testing process by giving an algorithm and tool that allows to automatically analyze system API specifications and generate list of possible vulnerabilities and attack vector ready to be used as security non-functional requirements. Method. We conducted a multivocal review of research and conference papers, bug bounty program reports and other grey sources of literature to outline patterns of attacks against IDOR vulnerability. These attacks are collected in groups proceeding with further analysis common attributes between these groups and what features compose the group. Endpoint properties and attack techniques comprise a group of attacks. Mapping between group features and existing OpenAPI specifications is performed to implement a tool for automatic discovery of potentially vulnerable endpoints. Results and practical relevance. In this work, we provide systematization of IDOR/BOLA attack techniques based on literature review, real cases analysis and derive IDOR/BOLA attack groups. We proposed an approach to describe IDOR/BOLA attacks based on OpenAPI specifications properties. We develop an algorithm of potential IDOR/BOLA vulnerabilities detection based on OpenAPI specification processing. We implemented our novel algorithm using Python and evaluated it. The results show that algorithm is resilient and can be used in practice to detect potential IDOR/BOLA vulnerabilities.