How to automate the last mile of compliance evidence

Built-in collectors handle common evidence workflows. The remaining manual work is usually more specific: confirming who administers a GitHub organization, or showing which AWS IAM users have MFA enabled. That is the last mile—small in scope, but repeated every audit period.

Custom Evidence Automation turns a reviewed, read-only collection into governed evidence. It does not certify a control, guarantee auditor acceptance, or replace a reviewer. It gives the reviewer a fresh artifact with clear provenance to assess.

Start with a real evidence need

Use a missing, stale, or repeatedly uploaded requirement as the trigger. Ask three questions before automating it:

• Is the requirement supported by a reviewed template?
• Can the source be accessed with an existing read-only integration?
• Will the collected result give a reviewer useful evidence rather than a broad data dump?

Today, the reviewed starting templates cover GitHub organization administrators and AWS IAM users with MFA. They are intentionally narrower than a general-purpose integration builder.

Scope the collection to your environment

Choose the reviewed template, then set the supported scope for the resource you need to evidence. For a GitHub organization-administrator collection, that means the organization the integration should read. AWS IAM/MFA collection uses the connected AWS account. Do not put credentials, tokens, or secrets in the scope fields—AuditFetch uses the configured integration credential instead.

Test before you enable

Run the read-only test against the selected source before enabling an automation. The test verifies the current connection and permissions, reports whether matching resources were found, and returns a bounded preview. AuditFetch shows the returned field names and any redacted fields so the reviewer can understand what the collection saw without treating the preview as a compliance conclusion.

If the test fails, fix the connection, required read-only access, or scope and test again. A changed draft must pass a fresh test before it can be enabled.

Keep the evidence governed after collection

When enabled, the automation creates evidence through the same lifecycle as built-in collectors: source metadata, capture time, mapping and review state, retention rules, and export history stay with the artifact. One collected evidence type can support compatible controls and frameworks, but that reuse is visible for review—it is not an automatic assertion that every control is satisfied.

A practical first automation

If GitHub is already connected, start with organization administrators. Review the required read-only access, scope the organization, run the test, inspect the preview, then enable the tested draft. After the first collection, open the resulting evidence and confirm its mapping and freshness before relying on it in an audit packet.

This sequence keeps the value simple: less repeated manual evidence work, with the same review and provenance expectations as the rest of AuditFetch.

Boundaries to keep explicit

A successful test proves that the configured integration could read the declared scope and return the expected bounded shape at that time. It does not prove that the population is complete, that a review decision is correct, or that the evidence will remain fresh. Reconcile scope against an authoritative inventory, keep the reviewer accountable for sufficiency, and revisit the automation when the provider or requirement changes.