AI Agents Exceeding Their Intended Scope

Customers trigger product agents that loop, drift, or invoke tools beyond their authorization. These failures often surface only after an agent has modified production data or sent messages on a customer's behalf. PointGuard AI validates each agent action before it runs, enforces each agent's mission, and contains agents automatically when behavior moves outside policy.

Customer-facing agents act in production, at scale, on behalf of many tenants.

• Agents can loop or call tools repeatedly and run up costs.
• Ambiguous requests push agents beyond their intended task.
• Injected content can redirect an agent mid-workflow.
• Failures are found only after customer data changes.

Agent Mission Control and Guardian Agent validate actions before execution and contain agents in real time.

1. Define each agent's mission. Register permitted tools, data scopes, rate limits, and expected behavior for every product agent.

2. Validate before execution. Check each proposed action against policy and the agent's trust score at sub-millisecond latency.

3. Contain automatically. Use circuit breakers to stop loops, require approval for destructive actions, and pause agents when trust drops.

4. Investigate with telemetry. Reconstruct agent decisions and tool calls per tenant to fix root causes and answer customer questions.

• OWASP Top 10 for LLMs: LLM06 Excessive Agency and LLM10 Unbounded Consumption, covering agents acting with excessive autonomy and runaway resource use.
• OWASP Top 10 for Agentic Applications: ASI01 Agent Goal Hijack, ASI08 Cascading Failures, and ASI10 Rogue Agents, addressing redirected agents, failures that spread across tenants, and rogue behavior.
• NIST AI RMF: MAP defines operational limits; MEASURE monitors behavior; MANAGE contains agents; GOVERN assigns oversight.