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Cybersecurity threats are growing faster than human analysts can respond. AI fills the gap by analyzing patterns, detecting anomalies, and responding to suspicious behavior in real time. Modern security systems use machine learning to recognize irregular login activity, malicious files, or unusual traffic spikes.
Threat actors also use AI to scale phishing, automate exploits, and generate convincing social engineering attempts. The result is a digital battlefield where both attackers and defenders rely on advanced models.
Defensive AI tools offer automated incident response, malware detection, and predictive analysis. They reduce human workload and increase accuracy by scanning millions of signals per second.
As security becomes an AI vs. AI landscape, strong systems, model monitoring, and ethical guardrails become more important than ever.