Agentic AI Threats

Agentic AI changes cyber operations because it can combine reasoning, memory, browser interaction, API access, tool orchestration, and multi-agent coordination into sustained operational loops. Traditional automation accelerated individual tasks. Agentic systems can interpret feedback, choose what to do next, and continue pursuing an objective with limited human supervision. That changes the economics of attack. A smaller adversary team can maintain continuous reconnaissance, personalize social engineering, test identity workflows, rotate infrastructure, correlate exposure across cloud and SaaS environments, and adapt when defenders intervene. The result is not necessarily a fully autonomous attacker. It is a persistent, semi-autonomous operating model that can act at a tempo many security programs were not designed to match. MITRE ATT&CK remains useful because the underlying adversary behaviors still matter. What changes is the operational context around those behaviors. Reconnaissance may continue throughout an intrusion. Credential access can focus on sessions, OAuth grants, API keys, and delegated permissions. Lateral movement can occur through SaaS relationships and cloud roles rather than host-to-host traversal. Malicious activity can increasingly look like legitimate work performed through trusted interfaces.