01 / 06
Detection Engineering CI/CD Pipeline
Detection rules treated like code: written, tested, and deployed automatically
TRACKDetection Engineering & Security AutomationSTATUSPLANNED
STACKSigma · YARA · MITRE ATT&CK · GitHub Actions · Splunk / Elastic
## OBJECTIVE
Build a lab pipeline where detection rules live in version control and only reach the SIEM after passing automated checks, the same way application code moves through CI/CD.
## SCOPE
- Author a suite of custom Sigma and YARA rules, each mapped to a specific MITRE ATT&CK technique, starting with T1059 (Command and Scripting Interpreter).
- Validate rule syntax and metadata automatically on every commit with GitHub Actions.
- Deploy passing rules straight to a lab SIEM instance (Splunk or Elastic), with no manual copy and paste.
## WHAT IT WILL DEMONSTRATE
- Turning an ATT&CK technique into a testable, reviewable detection.
- Detection-as-code practices: version control, peer review, and repeatable deployment.
Planned build. This page will be updated with the repository, write-up, and results as the work is completed.
02 / 06
SOAR Playbook: Automated Alert Triage
Tier-1 and Tier-2 triage handled by an API-driven workflow
TRACKDetection Engineering & Security AutomationSTATUSPLANNED
STACKShuffle or Tines · VirusTotal · Shodan · AbuseIPDB · Active Directory / Entra ID
## OBJECTIVE
Automate the repetitive first steps of indicator triage so analyst time goes to the alerts that need judgment.
## SCOPE
- Intercept phishing and endpoint alerts with an API-driven workflow in an open-source SOAR platform (Shuffle or Tines).
- Enrich each indicator against VirusTotal, Shodan, and AbuseIPDB.
- Query Active Directory / Entra ID for context on the affected user.
- Resolve the alert: close benign tickets safely, or automatically isolate the endpoint when the evidence supports it.
## WHAT IT WILL DEMONSTRATE
- SOAR playbook design and security API integration.
- Triage logic with clear, auditable decision points.
Planned build. This page will be updated with the repository, write-up, and results as the work is completed.
03 / 06
Multi-Cloud Infrastructure Security & Guardrails
A secure cloud architecture defined as code, with policies that block misconfigurations before they ship
TRACKDetection Engineering & Security AutomationSTATUSPLANNED
STACKTerraform · AWS / Azure · Open Policy Agent · AWS Organizations / Azure Policy
## OBJECTIVE
Deploy an enterprise-style cloud environment entirely through Infrastructure as Code, with security requirements enforced automatically rather than by manual review.
## SCOPE
- Define the full architecture (AWS or Azure) in Terraform.
- Embed automated policy checks with Open Policy Agent or native guardrails (AWS Organizations / Azure Policy).
- Enforce strict network isolation, encryption at rest, and least-privilege IAM roles.
## WHAT IT WILL DEMONSTRATE
- Cloud security architecture and policy as code.
- Catching insecure configurations before deployment instead of after an incident.
Planned build. This page will be updated with the repository, write-up, and results as the work is completed.
04 / 06
Digital Forensics & Root-Cause Reconstruction
A simulated breach investigated end to end, down to a minute-by-minute attacker timeline
TRACKDigital Forensics & Threat IntelligenceSTATUSPLANNED
STACKVolatility · Autopsy / FTK · Isolated sandbox
## OBJECTIVE
Work a realistic compromise the way an incident responder would: from evidence collection to a defensible reconstruction of what happened.
## SCOPE
- Simulate a complex breach, such as a ransomware deployment or a web server compromise, in an isolated sandbox.
- Analyze memory dumps with Volatility to hunt for code injection and hidden processes.
- Examine disk images with Autopsy / FTK to identify persistence mechanisms.
- Reconstruct a precise, minute-by-minute timeline of the attacker's lateral movement.
## WHAT IT WILL DEMONSTRATE
- Memory and disk forensics.
- Root-cause analysis and evidence-based timeline reconstruction.
Planned build. This page will be updated with the repository, write-up, and results as the work is completed.
05 / 06
APT Attribution Dossier & Infrastructure Mapping
A structured investigation into an active threat actor, delivered as a professional intelligence briefing
TRACKDigital Forensics & Threat IntelligenceSTATUSPLANNED
STACKOSINT · Malware sandboxes · Passive DNS · MITRE ATT&CK
## OBJECTIVE
Produce a finished intelligence product of the kind analysts brief to decision-makers.
## SCOPE
- Select an established state-sponsored APT or global ransomware group.
- Map its historical TTPs, active infrastructure, and primary geographic targets using OSINT repositories, malware sandboxes, and passive DNS.
- Package the findings into a comprehensive, professionally formatted intelligence briefing.
## WHAT IT WILL DEMONSTRATE
- Structured intelligence research and source evaluation.
- Infrastructure pivoting and clear written analysis.
Planned build. This page will be updated with the repository, write-up, and results as the work is completed.
06 / 06
Malware Behavioral Analysis & Threat Data Pipeline
From a detonated sample to shareable, structured threat intelligence
TRACKDigital Forensics & Threat IntelligenceSTATUSPLANNED
STACKCuckoo / CAPE · Python · STIX / TAXII
## OBJECTIVE
Show the full path from raw malware behavior to intelligence that other teams and tools can consume automatically.
## SCOPE
- Build a secure dynamic malware analysis sandbox (Cuckoo / CAPE) and execute real-world samples in isolation.
- Extract network artifacts, command-and-control (C2) callback patterns, and system modifications.
- Write a Python parser that converts the extracted IOCs into formal STIX objects for sharing over TAXII.
## WHAT IT WILL DEMONSTRATE
- Dynamic malware analysis and C2 identification.
- Threat intelligence automation and data standards (STIX / TAXII).
Planned build. This page will be updated with the repository, write-up, and results as the work is completed.