Incorporation of Verifier Functionality in the Software for Operations and Network Attack Results Review and the Autonomous Penetration Testing System
This addresses the issue of maintaining accuracy in cybersecurity assessment tools for network operators and penetration testers, but it is incremental as it builds on existing SONARR and APTS frameworks.
The paper tackles the problem of inconsistent representation of real-world entities in digital twin networks for operations and network attack review software (SONARR) and autonomous penetration testing systems (APTS) due to changing fact values, by proposing and evaluating the addition of verifiers that update network facts from the environment, resulting in more reliable output.
The software for operations and network attack results review (SONARR) and the autonomous penetration testing system (APTS) use facts and common properties in digital twin networks to represent real-world entities. However, in some cases fact values will change regularly, making it difficult for objects in SONARR and APTS to consistently and accurately represent their real-world counterparts. This paper proposes and evaluates the addition of verifiers, which check real-world conditions and update network facts, to SONARR. This inclusion allows SONARR to retrieve fact values from its executing environment and update its network, providing a consistent method of ensuring that the operations and, therefore, the results align with the real-world systems being assessed. Verifiers allow arbitrary scripts and dynamic arguments to be added to normal SONARR operations. This provides a layer of flexibility and consistency that results in more reliable output from the software.