International Journal of Scientific Research and Engineering Development

In the modern digital era, corporate networks are increasingly exposed to sophisticated cyber threats that exploit system vulnerabilities. Traditional vulnerability management and incident response approaches rely heavily on manual operations, leading to slow detection, inefficient mitigation, and prolonged exposure to attacks. To address these challenges, this study introduces an integrated framework that combines automated vulnerability management with intelligent incident response mechanisms. The proposed system continuously monitors network assets, prioritizes vulnerabilities based on risk assessment models, and initiates automated response actions such as isolation, patching, or containment through orchestration platforms. By leveraging automation and artificial intelligence, the framework minimizes human error, shortens response time, and enhances overall security posture. Experiments conducted in a simulated corporate network demonstrate significant improvements in detection and containment efficiency. The system reduced mean time to detect (MTTD) by 42% and mean time to respond (MTTR) by 58%, while lowering operational overhead and false positives. Results confirm that integrating automation within vulnerability management and incident response processes increases resilience against evolving threats. The research highlights the importance of adaptive automation in strengthening enterprise cyber security strategies, enabling organizations to proactively defend against cyber attacks while maintaining business continuity.