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Is AI red teaming enough for agent security?

Red teaming finds exploit paths. Runtime enforcement closes them. Continuous validation proves they stay closed after model, prompt, tool, or policy changes. Testing alone produces a report of yesterday's risk; agent security needs the finding turned into an enforced control and kept as a regression test.

By the Ultra13 teamPublished Updated
TL;DR
  • Red teaming finds where untrusted context can drive an action.
  • Runtime enforcement closes those paths in production.
  • Continuous validation proves they stay closed after changes.
  • A report without enforcement is a screenshot of yesterday's risk.

Find, close, prove

A teardown exposes the exploit path; a source-to-sink policy closes it; a replay keeps it closed. See agentic AI red teaming and a sample proof report.

FAQ

Frequently asked questions

Is red teaming enough on its own?
No. It finds failures but does not stop them in production. You need runtime enforcement to close each path and continuous validation to prove it stays closed.

See where the firewall stops the path.

Give us one agent workflow. We’ll map the context boundary, replay the abuse paths, and show where the Context Firewall blocks them.

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