SECOPS

Scan GitHub pushes for leaked secrets, then quarantine and rotate

On every push to GitHub, scans the new commits for exposed API keys and tokens. If a real secret is found it opens a tracking issue, revokes the leaked credential.

CategorySecOps
Enginesim
Difficultyintermediate
Triggerwebhook
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerGitHub push webhook receivedGitHubGitHub
  • ActionFetch commit diff and scan for secret patternsGitHubGitHub
  • LogicBranch: verified live secret vs false positive
  • ActionRevoke leaked credential at providerShell
  • ActionOpen GitHub issue with commit, file, and lineGitHubGitHub
  • OutputPost severity and remediation status to SlackSlack

What it does

Watches your GitHub repositories for newly pushed commits and inspects the diff for high-entropy strings and known credential patterns (AWS keys, Stripe keys, OpenAI tokens, private keys). When a verified secret is detected, it immediately revokes the leaked key, files a GitHub issue for the audit trail, and alerts the security channel in Slack.

When to use it

Use it as a last line of defense behind pre-commit hooks. Developers forget to install local scanners, and CI-only scanning is too late once code is on the remote. This catches leaks at push time and shuts the credential down before it can be abused.

How it works

  1. 1A GitHub push webhook fires with the commit range.
  2. 2The flow fetches the diff for each new commit and runs pattern plus entropy detection.
  3. 3A logic branch checks whether any match is a live, verifiable secret versus a false positive.
  4. 4For confirmed leaks, it calls the provider to revoke the key (via a shell rotation step) and opens a GitHub issue capturing the commit SHA, file, and line.
  5. 5It posts a structured alert to Slack with the severity and remediation status.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GitHubRepos, issues, pull requests, actions.
  2. 2
    Connect SlackChannels, DMs, threads, mentions.
  3. 3
    Connect ShellRun sandboxed commands inside the workspace.
  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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