TutorialsJune 21, 20269 min read

A Realistic First Internal AD Assessment For a Two-Person Security Team

A two-person security team does not need to recreate a full enterprise red-team program to find useful Active Directory risk. It needs a scoped first pass, clean evidence, and a report leadership can act on.

Start with the questions that matter

The first internal AD assessment should answer practical questions, not prove that every possible attack path exists. Are privileged groups too broad? Are old accounts still active? Can one compromised workstation reach too much? Are cloud identities connected in ways the team forgot?

Those questions create a focused assessment that a lean team can finish and repeat.

  • Which accounts have meaningful administrative reach?
  • Which machines expose risky services or weak configurations?
  • Which identity paths connect normal users to privileged systems?
  • Which findings can be remediated this quarter?

Collect enough evidence to be trusted

The point is not to produce the biggest graph. It is to produce evidence that survives review. For every meaningful path, keep the source object, destination object, relationship, timestamp, and plain-English impact.

That evidence should be captured while the operator works. Waiting until the end almost guarantees missing context.

Include cloud identity early

Many smaller companies treat Active Directory and cloud identity as separate projects, but attackers do not. Entra ID roles, synced accounts, and cloud permissions can turn an on-prem issue into a cloud issue quickly.

Even a first pass should ask whether on-prem identities have cloud consequences.

For small teams, scope is not the enemy. Unclear scope is.

Ship a report that creates action

The report should not be a graph dump. Split it into executive risk, technical evidence, and a remediation plan. Keep the first pass narrow enough that the team can show progress in the next quarter.

Zypheron gives lean teams one workspace for AD and cloud attack paths, local evidence collection, human-in-the-loop AI summaries, and report output from the same assessment record.

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