What AI Red Teaming Means for Autonomous Workflows

AI red teaming is often treated as a model evaluation exercise. For autonomous workflows, that is too narrow.

An agent may write to systems, retrieve sensitive context, trigger approvals, summarize regulated material, or coordinate actions across multiple tools. The meaningful test is whether the total workflow behaves safely under pressure.

Test the Action Path

Map the chain from user input to model reasoning, tool invocation, business action, logging, and human review. Each step is a possible control point.

Use Realistic Abuse Cases

Prompt injection matters, but it is only one path. Red-team scenarios should include confused-deputy behavior, malicious documents, overbroad tool permissions, identity misuse, and unsafe escalation.

Turn Findings Into Operating Controls

The output of red teaming should be more than a report. It should inform access design, monitoring, approval rules, remediation priorities, and repeatable validation.