OTHER

SOC2 Evidence Staleness Sweep (S3 artifacts → Confluence register)

On a weekly schedule, scans the SOC2 evidence bucket in S3, computes each artifact's age against its control's collection cadence.

CategoryOther
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule fires the evidence sweep
  • ActionList evidence objects and last-modified dates in S3AWS S3
  • LogicGroup by control, compute freshest-artifact age vs cadence
  • ActionUpdate per-control freshness status in Confluence registerConfluenceConfluence
  • OutputPublish updated control register pageConfluenceConfluence

What it does

Every week it walks your SOC2 evidence store in S3, reads the last-modified date of each control's artifact, and compares it to the freshness cadence you defined for that control (for example 30, 90, or 180 days). Controls whose newest artifact has aged past their window get flagged STALE in a Confluence control register so auditors and control owners always see current status.

When to use it

Use it when your evidence lives as files in S3 (screenshots, exported configs, signed PDFs) and your auditable source of truth is a Confluence page. It keeps the register honest between point-in-time audits without anyone manually checking file dates.

How it works

  1. 1A weekly schedule fires the sweep.
  2. 2It lists every object in the SOC2 evidence prefix in S3 and pulls each artifact's last-modified timestamp.
  3. 3Logic groups objects by control ID and computes the age of the freshest artifact per control, comparing it to that control's cadence.
  4. 4It writes the per-control freshness status (FRESH / DUE SOON / STALE) into the Confluence control register table.
  5. 5The updated register page is published as the run output.

Set it up

What you configure once, before turning it on.

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

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