System software is a cornerstone of any software system, so building secure system software in accordance with requirements of certification authorities and state-of-the-art practices is an important scientific and technical problem. One of possible approaches to cope with the problem is to build a methodology for secure system software development including advanced scientific technologies and industry best practices. The paper presents current results achieved in building such methodology in the following directions. The first one is regulatory framework improvement including development of GOST R specifications defining requirements to formal models of access control policies and their formal verification. The second direction is design and verification of formal models of corresponding security functional requirements. The third direction is application of new and well established technologies of static and run-time analysis of systems software. The considered technologies include static analysis, fuzzing, functional and unit testing as well as testing the system software against formal models of its functional security requirements. The forth direction is development of methods for acquisition of results of all kinds of the analysis and for its analytical processing. All the directions are illustrated by practical examples of application of the methodology to development of Astra Linux operating system distribution that is certified according to the highest evaluation assurance levels.

Fuzzing as a part of the continuous integration is a necessary tool, aimed primarily at the providing confidence in the software being developed. At the same time, in the presence of significant amounts of the source code, fuzzing becomes a resource-intensive task. That’s why increasing the efficiency of fuzzing to reach needed code sections more quickly without reducing quality becomes an important line of research. The article deals with approaches to improve the efficiency of fuzzing both for kernel and for user-space software. On the other hand, on these amounts of program code, static code analysis produces a huge number of warnings about possible errors, and the main resources within this type of analysis are required not to obtain to result, but for analytical processing. In this regard, in the article considerable attention is paid to the approach of correlating the results of static and dynamic code analysis using the developed tool, which also allows to implement directed fuzzing in order to confirm the warnings of static analyzer, which significantly increases the efficiency of testing components of the protected OS Astra Linux.