Traditional cyber security models were not designed for autonomous AI agents. Threat observation — monitoring real-world attacks against agentic systems — is the missing layer.
Agentic systems introduce entirely new attack surfaces. Autonomous AI systems can behave unpredictably and evolve beyond originally tested conditions.
Threat Observation is the practice of monitoring, studying, and analysing real-world attacks against autonomous systems.
Many attack patterns targeting agentic AI are still emerging and are not yet fully understood by traditional cyber security models.
Specification gaming occurs when an AI agent technically achieves its goal while violating the intent behind the instruction.
Organizations should continuously monitor agent behaviour, perform adversarial testing, simulate hostile environments, and maintain strong human oversight.
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