SECOPS

Escalate confirmed secret exposures to PagerDuty with auto-rotation

When a secret-scanning webhook reports a confirmed exposed credential, it rotates the key, opens a PagerDuty incident with full context, and logs the timeline to an audit store.

CategorySecOps
Enginesim
Difficultyadvanced
Triggerwebhook
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerConfirmed-exposure webhook receivedHTTP webhook
  • LogicFilter for high-severity production secrets
  • ActionRotate and reissue affected credentialShell
  • ActionOpen PagerDuty incident with full contextPagerDutyPagerDuty
  • OutputWrite response timeline to S3 audit bucketAWS S3

What it does

Receives confirmed exposure events from your scanner and treats them as security incidents. It rotates the affected credential, pages the on-call security engineer through PagerDuty with the leak location and blast radius, and records the full response timeline to an audit log in S3.

When to use it

Use it when a leaked production secret is a wake-someone-up event, not a ticket for next sprint. This is for the credentials that gate customer data or payment systems, where minutes of exposure matter and you need a paged human plus an automated first-response.

How it works

  1. 1An incoming webhook delivers a confirmed-exposure payload (credential type, source, severity).
  2. 2A logic step filters for high-severity, production-scoped secrets only.
  3. 3The flow runs a shell rotation routine to revoke and reissue the credential.
  4. 4It opens a PagerDuty incident with the leak source, affected service, and rotation status.
  5. 5It writes the complete event timeline to an S3 audit bucket for post-incident review.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect PagerDutyIncidents, on-call, escalations.
  3. 3
    Connect ShellRun sandboxed commands inside the workspace.
  4. 4
    Connect AWS S3Buckets, objects, signed URLs.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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