Agent Action Rollback Drill (QA)

Agent Action Rollback Drill (QA)

1. 01

   Pick one production agent workflow and freeze its write permissions before the drill starts

   Choose a workflow that touches client systems, such as a support bot that edits tickets or a reporting agent that writes to a shared drive. Revoke write scope so the drill cannot alter live client data.

2. 02

   Define the five risk dimensions you will score each agent action against

   Vaultak scores actions across five risk dimensions and can block, pause, or roll back anything that violates policy. Mirror that structure: data sensitivity, blast radius, reversibility, client visibility, and cost of a wrong action.

3. 03

   Inject three failure scenarios in ascending severity and log the agent's response to each

   Start with a malformed input the agent should reject, move to a prompt injection embedded in a client document, then a request that would delete or overwrite records. Record whether the agent halted, asked for approval, or proceeded.

4. 04

   Time how long a full rollback takes from detection to restored state

   The number that matters to a client is minutes from bad action to clean state, not the existence of a rollback feature. Anything over 15 minutes needs a documented manual fallback before the workflow goes back into a retainer.

5. 05

   Verify that the audit trail names the actor, the action, and the policy that fired

   A log that says 'action blocked' is useless in a client incident review. Confirm the record identifies which agent, which tool call, which rule, and which human approved or overrode it.

6. 06

   Re-enable write permissions only after the rollback path is proven end to end

   Restore scope one workflow at a time and re-run the mildest scenario to confirm the guardrails still fire with production credentials attached.

7. 07

   File the drill results as an appendix to the client's security scope agreement

   Attach timings, scenarios, and the rollback log to the signed scope document. When a client asks what happens if the agent goes wrong, the answer is a dated test result rather than a promise.