AI Agent Security
Operational security journal June 6, 2026 For security, governance, and risk teams

Operational security

Secure agents by governing actions, not just prompts

A practical guide to prompt injection, tool misuse, permissions, runtime policy, and the control patterns teams need before agents touch production systems.

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AI Agent Security

Attack vectors that matter

Agents are risky because they combine language, autonomy, and side effects. The security posture has to account for that combination.

Prompt injection

External content can steer the model toward unsafe actions or policy bypass attempts.

Tool misuse

A valid tool can still be used with unsafe timing, arguments, or intent.

Privilege sprawl

Agents often inherit broad credentials that were designed for humans or services.

Quiet exfiltration

Small tool calls can leak sensitive data without looking dramatic.

AI Agent Security

The control stack

A serious agent security program combines least privilege, validation, monitoring, and runtime enforcement.

Least privilege

Give agents the smallest durable capability set that can complete the job.

Argument validation

Check model-generated parameters before tools run.

Auditability

Record what the agent requested, what policy decided, and what executed.

Execution governance

Block or modify actions that violate deterministic policy.

AI Agent Security

Pilot checklist

Before introducing autonomous actions, make the control boundary visible and testable.

List every tool, classify its blast radius, and make approval rules explicit before the agent can call it.

Run prompt injection tests against tool-connected workflows, then review the logs for denied and allowed actions.

Next step

Add runtime governance to your agents

VEX Protocol helps teams separate what an agent suggests from what production systems are allowed to execute.

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Sources

References and further reading