Simulating AD attacks with Purple Team labs

Purple teaming in an Active Directory (AD) context is the discipline of running controlled, authorized attack simulations (red) while observing, tuning, and validating detection + response (blue). Done well, it turns vague goals like “improve AD security” into measurable outcomes: which attacks did we detect, how fast, with what signal quality, and what changed because of it.

This guide shows how to build a purple team lab for AD, instrument it correctly, run realistic attack simulations safely, and translate results into hardening actions and better alerts—without turning the article into a “how-to hack” recipe.

What You Get from an AD Purple Team Lab

• Detection validation: prove which techniques are visible in your telemetry (and which are blind spots).
• Signal quality tuning: reduce false positives, improve precision, and add context for faster triage.
• Response rehearsal: test investigation playbooks end-to-end (collection → correlation → containment).
• Hardening feedback loop: confirm a control change actually blocks or degrades the simulated technique.
• Executive-friendly reporting: “Technique X: detected in 3 minutes, high confidence, containment steps validated.”

Lab Safety Principles (Non-Negotiable)

• Isolate the lab: separate VLAN / virtual switch, no trust to production, and no route to sensitive networks.
• Use synthetic data: fake users, fake passwords, fake app/service accounts—no reused credentials.
• Time-box and document: start/stop times, the exact technique simulated, and expected artifacts.
• Prefer “emulation” over “exploitation”: you often only need the log/behavioral footprint to validate detections.
• Only authorized tooling: use organization-approved test frameworks, and keep them in the lab only.

Core Lab Architecture (A Practical Reference Blueprint)

A “good enough” AD purple lab doesn’t need to be huge. It needs to be representative and observable. A baseline architecture that works for most teams:

• 1× Domain Controller VM (DNS, AD DS)
• 1× Member Server VM (file server / IIS / “app server” role)
• 2× Workstations (one “user endpoint”, one “admin workstation”)
• Optional: AD CS (if you want to test certificate abuse detections), ADFS (if relevant), and a jump box
• Central logging: Windows Event Forwarding (WEF) or an agent-based collector to your SIEM

If you’re newer to Kerberos and why AD attacks often revolve around tickets, read: NTLM authentication and Kerberos Authentication Protocols Explained. That foundation will make your detections dramatically more intuitive.

Telemetry First: What You Must Collect to Make Purple Teaming Worth It

Most “we didn’t detect it” outcomes are really “we didn’t collect it.” Before you run any simulations, build a logging posture that matches your goals.

Minimum viable logging (Windows)

• Domain Controller Security logs (Account logon, Kerberos, directory service access, group changes)
• Workstation + server Security logs (logons, privilege use, process creation if enabled)
• PowerShell logging (module logging, script block logging—where appropriate)
• Optional but high-value: Sysmon + a curated config (process, network, image loads)

Identity signals (cloud/hybrid)

If your AD environment is hybrid, you’ll often correlate on-prem activity with Entra signals (sign-ins, risky users, suspicious locations, etc.). For operational guidance on building visibility in Entra, see: How to monitor and report security events in Microsoft Entra ID.

Make lockouts and auth failures “investigatable”

Password spraying and noisy authentication attempts are common lab scenarios because they validate both detection and operational response. To tighten your lockout investigations and understand the key event IDs, use: Account Lockout Event ID: How to Find Account Lockouts.

PowerShell tooling in the lab

You’ll do a lot of lab automation in PowerShell (user creation, group assignment, policy checks, log exports). If your test admin box is missing the AD module, reference: How to install the PowerShell Active Directory module.

How to Run AD Purple Team Exercises (The Repeatable Workflow)

A mature purple team exercise is a loop, not a one-off:

1. Pick a technique (mapped to a real attacker behavior you care about).
2. Define “expected artifacts” (which logs, which event IDs, which hosts).
3. Emulate safely (in a controlled way that produces the footprint without needing destructive steps).
4. Detect + investigate (can your SOC find it quickly and confidently?).
5. Tune + harden (detections, audit policy, baselines, tiering, segmentation).
6. Re-run the same scenario to confirm the improvement actually worked.

Recommended “Starter Pack” AD Scenarios

Below are common AD attack themes that are valuable to simulate because they teach defenders how attackers move through identity infrastructure. The focus here is on what to simulate and what to detect, not step-by-step exploitation instructions.

Scenario 1: Password spraying / authentication spikes

Objective: Validate detection of unusual authentication patterns and ensure lockout investigations are fast and consistent.

• Emulation idea: generate repeated failed logons from a workstation to a small subset of test accounts over a short window.
• Primary signals: failed logon events, lockouts, source host identification, account targeting patterns.
• Questions to answer:
  • Can you identify the source host quickly?
  • Can you distinguish a user typo storm from a spray?
  • Do you have thresholds tuned per environment (servers vs workstations)?

Scenario 2: Kerberos service ticket abuse emulation (Kerberoast-like footprint)

Objective: Validate that suspicious service ticket request patterns are visible and alertable.

• Emulation idea: from a standard user context, request service tickets for multiple SPN-backed accounts in quick succession.
• Primary signals: Kerberos service ticket request events on DCs; unusual volume, unusual encryption types, odd client hosts.
• Questions to answer:
  • Can you detect “high volume service ticket requests” from a single client?
  • Do you baseline normal service ticket behavior (apps, scanners, monitoring)?
  • Do you have a playbook: identify SPN owner, password age, privilege level, and mitigation path?

Tip: This is where understanding Kerberos mechanics matters—again, the refresher here helps: NTLM vs Kerberos explained.

Scenario 3: Privileged group membership change (persistence and escalation)

Objective: Ensure your monitoring catches unauthorized additions to high-impact groups.

• Emulation idea: add a test user to a privileged group (e.g., Domain Admins in the lab) using a controlled admin account.
• Primary signals: group membership change auditing, “who changed what,” where, and when.
• Questions to answer:
  • Do you alert on membership changes to Tier-0 groups?
  • Do alerts include actor + target + group + originating host?
  • Can responders quickly validate if the change was authorized?

Scenario 4: Lateral movement behavior emulation

Objective: Validate detections for suspicious remote execution patterns and admin share usage.

• Emulation idea: use legitimate remote admin methods in the lab (remote service creation, remote management tools) to mimic the “shape” of lateral movement.
• Primary signals: new service creation, remote logons, unusual admin connections between workstations, process ancestry.
• Questions to answer:
  • Do you have a baseline for normal admin pathways (PAWs, jump servers)?
  • Can you detect “workstation-to-workstation admin” as anomalous?
  • Do you enforce tiering so these pathways are rarer by design?

Scenario 5: Directory replication abuse emulation (DCSync-like investigation path)

Objective: Ensure replication-related permissions and suspicious replication requests are monitored.

• Emulation idea: focus on the permissioning and auditing angle: validate who has replication rights, alert on changes granting them, and test any relevant directory service access logs.
• Primary signals: permission changes on domain/replication objects, directory service access events (where enabled), DC-side anomalies.
• Questions to answer:
  • Can you enumerate and alert on accounts granted replication rights?
  • Do you have a response plan to remove rights and rotate secrets fast?

Build Better Alerts: Make Them Actionable, Not Just Noisy

A purple lab is where you upgrade alerts from “something happened” to “here’s what to do next.” For each detection, try to attach:

• Scope: host(s), account(s), domain(s), time window
• Enrichment: account type (human vs service), privilege tier, password age, MFA status (hybrid)
• Baselines: “normal rate” vs observed rate
• Suggested next steps: 3–5 investigation actions a responder can execute immediately
• Containment guidance: disable account? isolate host? rotate secrets? revert group membership?

Lab Hardening Moves You Can Validate Quickly

1) Local admin password hygiene (LAPS)

If your lab simulations include lateral movement, local admin password reuse is a classic accelerant. LAPS reduces blast radius by rotating per-device local admin passwords. If you want a step-by-step LAPS implementation reference, see: How to Install and Setup Microsoft LAPS.

2) Tiering and admin pathways

Even without new tools, you can reduce risk by making “weird admin paths” rarer:

• Use dedicated admin workstations / jump hosts for privileged actions.
• Reduce interactive logons to servers and DCs.
• Separate workstation admin from server admin from domain admin.

3) Audit policy tuned for identity abuse

Purple team results frequently show that a “missing” detection is actually an “audit policy gap.” Enable the categories you need (especially on DCs), then validate with your scenarios that logs arrive in your collector/SIEM.

Scoring the Exercise (So You Can Prove Improvement)

A simple scorecard makes your purple lab outcomes easy to track over time:

• Visibility: did the expected artifacts appear? (Yes/Partial/No)
• Detection: did an alert fire? (Yes/No)
• Time-to-detect (TTD): minutes from start to alert
• Time-to-triage (TTT): minutes from alert to “credible understanding”
• False positive risk: High/Medium/Low
• Response readiness: playbook executed successfully? (Yes/Partial/No)
• Control validation: did a hardening change measurably reduce the technique’s success/footprint?

A Practical “1-Week” Purple Lab Plan for AD

• Day 1: Build the lab + seed accounts/groups + ensure logging pipeline works end-to-end.
• Day 2: Run auth failure spikes + lockout investigations; tune thresholds and enrichment.
• Day 3: Run Kerberos service ticket footprint emulation; build baselines and noise filters.
• Day 4: Run privileged group change scenario; validate alerting and response steps.
• Day 5: Run lateral movement emulation; validate workstation-to-workstation admin anomalies.
• Day 6: Implement 1–2 hardening changes (e.g., LAPS, tiering restrictions) and re-run scenarios.
• Day 7: Produce the report: what improved, what remains blind, what’s next.

Reporting Template (Copy/Paste Friendly)

Exercise:
Technique simulated:
Date/time window:
Systems involved:
Accounts involved (test only):

Expected artifacts:
- Host logs:
- DC logs:
- SIEM fields:
- Entra (if hybrid):

Outcome:
- Visibility: (Yes/Partial/No)
- Detection: (Yes/No)
- TTD:
- TTT:
- Analyst notes:

Gaps:
- Missing logs:
- Excess noise:
- Missing enrichment:

Actions taken:
- Detection updates:
- Hardening changes:
- Playbook changes:

Re-test results:
- Visibility:
- Detection:
- TTD/TTT improvement:

Related Reading on WindowsActiveDirectory.com

• NTLM authentication and Kerberos Authentication Protocols Explained
• Account Lockout Event ID: How to Find Account Lockouts
• How to Install and Setup Microsoft LAPS: Step-by-Step Guide
• How to monitor and report security events in Microsoft Entra ID
• How to install the PowerShell Active Directory module

Conclusion

Simulating AD attacks in a purple team lab is one of the fastest ways to level up identity defense—because it forces your logging, detections, and playbooks to meet reality. Keep it isolated, prioritize telemetry, emulate techniques safely, and track improvements with a scorecard. Over time, your lab becomes a regression test suite for identity security: every change is measurable, repeatable, and explainable.