Validating Government Agent Actions Before Execution

A casework agent allowed to check benefit status can chain that access into record changes or disbursements in milliseconds. Static role-based access cannot anticipate every combination of tool calls, and logs only show what already happened. PointGuard AI validates each agent action before execution, holds high-impact actions for human approval, and contains agents whose behavior drifts.

Agents can turn read access into consequential actions faster than anyone can review them.

• Agents chain tools in ways their designers did not anticipate.
• Write, delete, and payment actions are hard to reverse.
• Injected content can redirect an agent mid-task.
• Agencies must show human oversight of consequential decisions.

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

1. Define each agent's mission. Register owners, permitted actions, data scopes, and limits for every agency agent.

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

3. Require approval for high-impact actions. Route record changes, deletions, and disbursements to an authorized staff member.

4. Contain and investigate. Use circuit breakers and kill switches when behavior is unsafe, and keep full telemetry for review.

• OWASP Top 10 for LLMs: LLM01 Prompt Injection and LLM06 Excessive Agency, covering manipulated inputs and agents acting beyond their authority.
• OWASP Top 10 for Agentic Applications: ASI01 Agent Goal Hijack, ASI02 Tool Misuse and Exploitation, and ASI10 Rogue Agents, addressing redirected agents, chained tool misuse, and rogue behavior.
• NIST AI RMF: MAP defines operational limits; MEASURE monitors behavior; MANAGE enables intervention; GOVERN assigns oversight.