What is artificial intelligence security monitoring?
Definition
Artificial intelligence security monitoring combines agent traces, tool calls, messages, authentication events, network activity, model outputs, and infrastructure logs. It seeks patterns such as unexpected external access, permission escalation, coordinated probing, hidden persistence, or attempts to alter evaluation evidence.
Monitoring must be protected from the systems it observes and scaled for high-volume multi-agent activity. Automated analysis can prioritize events, but consequential alerts need retained evidence and human investigation. Coverage should be tested with simulations that exercise likely bypasses rather than relying only on normal operation.
What should artificial intelligence security monitoring record?
It should record identities, permissions, model and tool calls, messages, state changes, network activity, policy decisions, errors, and protected timestamps.
Why must monitoring be separated from the agent it observes?
Separation reduces the chance that an agent can disable, rewrite, or selectively hide the evidence used to detect and investigate its actions.
