Project · Beginner · about 12 hours

Triage a day of logs and write detections

Analyse a set of security logs, separate noise from a real intrusion, and write and test Sigma detections for what you find.

Skills:Linux and Bash, Python, SIEM and security operations

Part of: Cybersecurity Engineer

Brief

A security operations centre lives on logs. Build a realistic set (extend the generator from the SIEM shelf, or use a public sample), find the intrusion hidden in the noise, and turn your findings into tested, reusable detections.

What to build

  1. Produce a labelled log set that mixes normal activity, internet scanning and one multi-step intrusion (guessing, a success, privilege use, persistence)

  2. Triage it: identify the incident, build a timeline, and write down what you dismissed as noise and why

  3. Write Sigma rules for the key steps and one correlation (failures then success), each mapped to an ATT&CK technique

  4. Build a test harness that runs the rules against known-bad and known-good logs and reports false positives and negatives

  5. Write the analyst report: what happened, evidence, and recommended actions

Deliverables

  • Repository with logs/, rules/, tests/ and REPORT.md

How it is graded

Reviewers run your test harness and add a new benign pattern to check your rules do not fire on it.

Stretch

Load your rules and logs into a free SIEM (for example Elastic or Wazuh) and reproduce the alerts there.

Deliverables

  • A log generator or captured sample and a written triage of what happened, with a timeline
  • At least four Sigma rules mapped to MITRE ATT&CK techniques
  • A test harness that runs each rule against known-bad and known-good logs and reports hits
  • A short report an analyst could act on

How a reviewer grades it

CriterionWeightWhat good looks like
Triage correctly separates scanner noise from the real intrusion30%
Detections fire on the attack and not on normal activity, proven by tests35%
Rules are mapped to ATT&CK and documented with triage steps20%
Report is clear and actionable15%