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Medium
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Agentic AI in Cybersecurity: From Reactive Defense to Proactive Resilience
- Agentic AI in cybersecurity involves autonomous software agents that can perceive, reason, and act independently in complex environments, shifting from reactive to proactive defense.
- Agentic AI is characterized by autonomy, proactivity, adaptability, and context-awareness, enabling it to make decisions and execute actions in real-time.
- This technology actively hunts for vulnerabilities, conducts contextual analysis to prioritize threats, issues early warnings, and delivers rapid responses, reducing mean time to containment.
- Agentic AI applications include automating SIEM triage, adaptive access control, autonomous incident response, and proactive vulnerability management.
- However, attackers are also leveraging agentic AI for autonomous malware and AI-generated social engineering, intensifying the cybersecurity landscape.
- Challenges with agentic AI include explainability, defining autonomy boundaries, addressing bias, and balancing automation bias with human skills.
- The future of cybersecurity involves human-AI collaboration, where agentic AI accelerates detection and response, empowers analysts, and enhances organizational resilience.
- Steps for adopting agentic AI include assessing needs, evaluating solutions, defining autonomy boundaries, investing in training, and continuously monitoring performance.
- Agentic AI represents a new era of proactive security, automating threat detection and response to help organizations stay ahead of evolving threats in cybersecurity.
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