The purpose of the study is to develop a platform that allows for various types of checks to identify weaknesses in the subsystems of unmanned automated systems.
Research methods: when developing the platform, a methodology based on the construction of ontological models was used, which made it possible to link the structural and functional characteristics of unmanned automated systems with threats and vulnerabilities, as well as with attacks on such systems. The process parallelization method was used to scan radio frequency ranges. The decision-making system is based on risk assessment methods.
Research results: the platform allows for optimizing the security testing process of unmanned automated systems. For automated testing, a database is used that includes a catalog of structural and functional characteristics, threats, vulnerabilities, and attacks. The platform can determine which types of structural and functional characteristics correspond to the vulnerabilities of unmanned automated systems. A system consisting of individual components (a sensor for scanning unmanned automated systems, an intelligent system for active analysis of unmanned automated systems). The sensor for scanning unmanned automated systems is implemented as a small-sized device. The system of intelligent active analysis of unmanned automated systems is implemented as software.
The scientific novelty lies in the development of a concept for a system for analyzing the safety of unmanned automated systems based on ontological models and radio frequency range analysis to identify system vulnerabilities during pre-operational checks.

Keywords: data analysis, statistics, attacks, risks, unmanned automated systems