Cybersecurity vendors are fast-tracking risk-based vulnerability management, AI, and machine learning to keep patch management current.
Here are the key takeaways:
- Patch management approaches that aren't data-driven are vulnerable to breaches.
- Attackers are increasingly weaponizing old vulnerabilities, making manual patch management insufficient.
- Legacy patch management systems are being replaced by risk-based vulnerability management (RBVM) and AI-based patch management.
- AI-driven patch management is shaking up cybersecurity by enabling real-time anomaly detection and prediction, risk-scoring algorithms, machine learning for real-time patch intelligence, automating remediation decisions, and contextual understanding of endpoint assets and identities.
- Organizations must use AI to manage entire lifecycles and gain greater contextual intelligence.
