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Graphical User Interface (GUI)-based APplications (GAPs) are ubiquitous, both in business and personal use and they are deployed on diverse software and hardware platforms. Unfortunately, close to 50Mil people have disabilities in the USA alone and over 600Mil worldwide, and it is difficult for Users With Disabilities (UWDs) to work with GAPs on their smartphones. Since there are hundreds of disabilities that impair people in vision, movement, thinking, remembering, learning, communicating, and hearing, UWDs need specialized enhancements to GUIs. Mobile Assistive APplications (MA2Ps) provide these enhancement services using specialized accessibility technologies that are fundamentally insecure, thus exposing all smartphone users to a variety of attacks. The goal of this framework is therefore to investigate security problems with accessibility technologies and to explore a novel theoretical foundation to allow stakeholders to create, analyze, and predict the security and privacy behavior of complex MA2Ps for UWDs. A connecting thread in the research thrusts is a combination of GAP and MA2P modeling and compositional intercomponent analysis using these models to create a prototype that can predict and mitigate security threats posed by accessiblity technologies for smartphone users. Also, the results of the proposed framework should inform the GUI security and assistive technologies communities about the possibilities and limits of program analyses and machine learning in dealing with security problems posed by accessibility technologies that make users unsafe.