> ## Documentation Index
> Fetch the complete documentation index at: https://docs.befailproof.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Rollback

> Restore a known policy deployment when a rollout disrupts valid agent work.

Rollback changes the deployed version or removes a policy assignment; it does not erase the decision history that explains the incident.

## Roll back a machine

<Tabs>
  <Tab title="Dashboard">
    1. Go to **Admin → enforcement**, expand the affected machine, and identify its last known-good policy set.
    2. Select **edit**, restore those versions and effects, and apply the new deployment.
    3. Wait for machine check-in, then verify the reported deployment.
    4. Open **Observe → policy** and the affected sessions to confirm valid work is no longer blocked.
  </Tab>

  <Tab title="CLI">
    Cloud deployment rollback is a dashboard workflow. Use local status to confirm that the corrected deployment has reached the machine:

    ```bash theme={null}
    failproofai config --status
    ```

    `failproofai config --pause` pauses builtin, custom, and convention policies for one local session. It does not pause Cloud-managed policies, so it is not a workaround for a bad Cloud deployment.
  </Tab>
</Tabs>

## When to roll back

* A policy blocks an expected production action.
* Match volume is materially higher than the observed rollout predicted.
* A policy depends on fields that an integration does not provide.
* A new version changes behavior outside the intended failure mode.

After rollback, open the affected sessions and identify the condition that caused the false positive. Create a new version, test both the unsafe and legitimate cases, then repeat the observe phase.

<Warning>
  Pausing enforcement can be appropriate during an incident, but it widens exposure for every active policy in that scope. Prefer rolling back the specific policy version when possible.
</Warning>