Continuously monitor AI agents for behavioral drift, unauthorized actions, and escalating risk, then stop dangerous activity before it impacts enterprise systems.
AI agents can make decisions, invoke tools, access data, and execute multi-step tasks with limited human oversight. An agent that begins a task operating correctly can later deviate from its intended mission, access unnecessary resources, misuse credentials, enter runaway loops, or perform destructive actions.
Traditional monitoring often evaluates events individually or identifies problems only after execution. Agent governance requires additional context. Organizations need to determine whether each action is consistent with the agent's identity, assigned mission, permissions, previous activity, and cumulative risk.
The challenge is therefore not simply monitoring what an agent does, but continuously determining whether its behavior remains consistent with what it is authorized and expected to do.
In April 2026, a Cursor coding agent powered by Claude Opus 4.6 deleted PocketOS's production database and volume-level backups in approximately nine seconds. The agent was working on a staging task when it encountered a credential problem, searched for another credential, found an API token associated with an unrelated task, and used it against a production environment.
The incident illustrates how a sequence of individually observable actions can escalate into destructive behavior. Moving outside the staging context, searching for unrelated credentials, accessing production resources, and initiating a destructive operation were all potential indicators of drift before the final action occurred.
Effective agent drift detection requires continuous visibility, behavioral context, and real-time enforcement.
Discover and identify agents. Maintain an inventory of agents across endpoints, applications, gateways, APIs, and runtime environments. Each agent should have an owner, identity, mission, provenance, permitted resources, and risk profile. PointGuard AI Discovery provides visibility into agents and other AI resources so they can be governed and monitored. (PointGuard)
Monitor runtime behavior. Observe tool calls, resource requests, credential use, agent-to-agent interactions, and other consequential actions as they occur. Actions can then be evaluated against authorization policies and the agent's intended scope.
Detect cumulative risk and drift. Evaluate sequences of activity rather than isolated events. Unusual tool use, repeated failures, attempts to access unrelated systems, privilege changes, or deviations from mission can increase a cumulative risk score and trigger additional controls.
Contain dangerous activity. When risk exceeds defined thresholds, controls should be able to require human-in-the-loop approval, block a tool call, trigger a circuit breaker, isolate an agent, or activate a kill switch.
PointGuard AI Agent Mission Control provides a runtime control plane that validates agent actions before execution and contains rogue behavior in real time. (PointGuard)
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