Enhancing Cybersecurity Resilience with CYBRANA: A Cyber YARA/YAML-Based Resilience Firewall Solution Applied with Next-Gen AI

The ever-increasing volume of server requests puts digital infrastructure at more risk of cyberattacks. This paper introduces CYBRANA, a cyberattack detection and mitigation system powered by AI. CYBRANA uses a Random Forest model to look into firewall and server logs for potential malicious threats. After analysis of flagged logs to extract request paths, CYBRANA then maps YAML rules to look for known attack pattern detection. Upon successful detection, CYBRANA classifies the attack type and severity (using CVSS scoring) by mapping it to the MITRE CAPEC framework®. This approach bridges the gap between existing cybersecurity frameworks and server log analysis, enabling a novel security pipeline. By automating threat detection and mitigation, CYBRANA enhances the security posture of digital infrastructure.