Abstract: Advanced cybersecurity systems and methods may provide enhanced security of critical infrastructure without the risks associated with traditional penetration testing. The systems and methods may model network vulnerabilities and simulate attack scenarios to identify potential security breaches. This supports the integration of generic rules and common properties, allowing for dynamic and scalable vulnerability analysis across complex network systems. Additionally, the systems and methods incorporate a multi-purpose fuzzer and an AI-driven Cyber Reasoning System (CRS) that autonomously detects and remedies software vulnerabilities based on predefined logic and pattern recognition. This comprehensive approach identifies existing vulnerabilities and predicts potential future threats by analyzing changes in network behavior and data flow.

Abstract: A system for autonomous cybersecurity probing includes a scanning module adapted to convert a target computing device or network scan to machine readable form. The scanning module includes an ingest module which processes the scan to create nodes representing the target ports, port status, and vulnerabilities. A command module includes a plurality of nodes representing facts, rules, actions, and verifiers associated with one or more vulnerabilities identified by the scanning module. The command module is configured to determine whether to launch an attack. An attack module is configured to, on receipt of instructions from the command module, assign an attack based on a one of the one or more vulnerabilities. A verifier module is configured to determine success or failure of the assigned attack and to return an indicator of the determined success or failure to the command module. Methods for cybersecurity probing using the described system are provided.