SECOPS

Leaked Secret Scanner: Detect, Rotate, and Page the Owner

Continuously scans public GitHub commits for leaked credentials, and on a verified hit it auto-rotates the exposed key, archives evidence, and pages the owning engineer.

CategorySecOps
Enginesim
Difficultyadvanced
Triggerevent
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerPublic repo push receivedGitHubGitHub
  • ActionScan commit diff for secret patterns
  • LogicVerify match is a live credential
  • ActionRevoke and reissue exposed key
  • ActionArchive leak evidence to S3AWS S3
  • OutputPage the commit author's on-callPagerDutyPagerDuty

What it does

This workflow watches your public GitHub footprint for accidentally committed secrets (API keys, tokens, cloud credentials), confirms the leak is real, immediately rotates the exposed credential, and pages whoever introduced it so they can react within minutes instead of hours.

When to use it

Run this when your org has public repos and you need a closed-loop response to credential leaks rather than just an alert. It is built for secops teams who want rotation and human escalation to happen automatically, not just a Slack ping that sits unread overnight.

How it works

  1. 1A GitHub push event arrives for any watched public repo.
  2. 2The diff is scanned with secret-detection patterns to find candidate credentials in the new commits.
  3. 3A logic branch verifies the match (entropy and provider-prefix checks) and drops false positives.
  4. 4For a confirmed live key, an action calls the provider to revoke and reissue the credential.
  5. 5The leaking commit, file path, and rotation receipt are written to an S3 evidence bucket.
  6. 6PagerDuty pages the commit author's on-call so a human owns the cleanup.

Set it up

What you configure once, before turning it on.

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

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