SECOPS

File and track verified push secret leaks as Linear issues with audit log

Detects live secrets in pushes, files one Linear issue per leak with severity and owner, and appends every confirmed exposure to a Postgres audit table for compliance reporting.

CategorySecOps
Enginesim
Difficultyintermediate
Triggerevent
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerGitHub push event receivedGitHubGitHub
  • ActionRetrieve commit diffsGitHubGitHub
  • LogicScan, verify, assign severity and owner
  • ActionOpen Linear triage issue per leakLinearLinear
  • ActionInsert audit row in PostgresPostgreSQLPostgres
  • OutputLink Linear issue as GitHub commit statusGitHubGitHub

What it does

This workflow turns verified secret exposures into trackable remediation work. On each push it scans the diff, confirms which secrets are live, creates a Linear issue per leak with severity, the owning team, and rotation checklist, and records the event in a Postgres audit table so you have a defensible history of every exposure and its resolution.

When to use it

Use it when leaked-secret response needs an owner, a deadline, and an audit trail, not just a transient alert. Ideal for teams under SOC 2 or similar regimes that must prove each exposure was tracked to closure.

How it works

  1. 1A GitHub push event triggers the workflow.
  2. 2An action retrieves the commit diffs.
  3. 3A logic step scans and verifies liveness, attaching severity and the likely owning team based on file path.
  4. 4A Linear action opens a triage issue per verified leak with the rotation checklist.
  5. 5A Postgres action inserts an audit row with repo, SHA, severity, and issue link.
  6. 6The output sets a GitHub commit status linking the Linear issue.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GitHubRepos, issues, pull requests, actions.
  2. 2
    Connect LinearIssues, projects, cycles, triage.
  3. 3
    Connect PostgresAny Postgres URL — query, write, migrate.
  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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