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Threat Hunting & Blue Team Training

Learn detection engineering, SOC workflows, and advanced analytics.

Continuous Learning  Skill Level: Intermediate  Goal: Enhance defensive investigation skills

Focused on understanding attacker behavior, telemetry, and analytic development.


Why Threat Hunting Matters

Threat hunting is a proactive approach where analysts search for hidden adversary activity that automated systems might miss.

By actively hunting, teams can detect and remediate threats earlier, close gaps in telemetry and tooling, and learn attacker techniques to improve detection logic.

Key benefits:

  • Detect advanced threats (APTs) before they escalate.
  • Improve telemetry coverage and detection fidelity.
  • Translate attacker TTPs into reproducible detections.
  • Strengthen incident response and reduce dwell time.

Hands-On Labs

Practice real-world scenarios and detection workflows in these platforms:


Frameworks & Methodologies

Resources that help map detections to adversary behavior and design repeatable hunts:


Courses & Training

Guided learning to build detection engineering and SOC skills:


Practical Tools & Playbooks

Common toolsets and useful collections for threat hunters:

  • ELK / Splunk / Sentinel: Build searches, dashboards, and alerts.
  • YARA: File-based detection rules for malware hunting.
  • Osquery / Velociraptor / GRR: Live endpoint telemetry and collection.
  • Sigma → SIEM rule conversion: Write a Sigma rule and convert it for your SIEM.

Helpful Resources & Recipes


Getting Started — a Simple Hunt

  1. Pick a data source (process creation, DNS logs, or EDR process tree).
  2. Baseline normal behavior for the environment (user behavior, service names, scheduled tasks).
  3. Create hypotheses (e.g., anomalous PowerShell child processes spawning from Word).
  4. Search & validate with queries, enrich findings (WHOIS, VT, internal asset DB).
  5. Document and tune: convert findings into repeatable detections and reduce false positives.

Pro Tip

Start small: pick one data source and one hypothesis per week.
Track hunts and lessons learned in a shared notebook — over time you'll build a library of reusable detections and playbooks.


Join the Discussion

Got a question, idea, or a better way to do it? Drop it below — I read every comment and update guides based on real-world feedback.

Add something useful. Ask good questions. Help someone else learn.