Capstone: Your AI-Powered Security Stack
Organize all AI security tools, workflows, and automation into an integrated DevSecOps stack you can implement immediately.
Premium Course Content
This lesson is part of a premium course. Upgrade to Pro to unlock all premium courses and content.
- Access all premium courses
- 1000+ AI skill templates included
- New content added weekly
You’ve learned AI tools for every layer of the security stack. Now build an integrated DevSecOps practice where these tools work together — not as isolated checkboxes, but as a connected system.
🔄 Quick Recall: Across this course you’ve covered: the AI security landscape (Lesson 1), vulnerability scanning (Lesson 2), infrastructure security (Lesson 3), CI/CD pipeline security (Lesson 4), monitoring and incident response (Lesson 5), compliance automation (Lesson 6), and advanced threat defense (Lesson 7). This capstone connects them into a unified stack.
Your Integrated Security Stack
Prevention Layer (Before Code Ships)
| Stage | Tool/Technique | AI Enhancement |
|---|---|---|
| IDE | Semgrep, Snyk IDE plugin | Real-time vulnerability warnings while coding |
| Pre-commit | GitLeaks, pre-commit hooks | Secret detection before code enters git |
| PR/CI | SAST + SCA + container scan | AI triage: 85% noise reduction |
| IaC Review | Checkov, tfsec | AI-assisted Terraform/K8s hardening |
| Deploy Gate | OPA/Kyverno admission controllers | Policy-as-code enforcement |
Detection Layer (After Code Ships)
| Stage | Tool/Technique | AI Enhancement |
|---|---|---|
| Runtime | CrowdStrike, Falco | Behavioral anomaly detection |
| Logs | Datadog, ELK + AI analysis | Automated correlation and threat identification |
| Network | VPC Flow Logs + AI analysis | Traffic pattern anomaly detection |
| Cloud | AWS GuardDuty, Security Hub | AI-prioritized findings |
| Endpoints | EDR solutions | Real-time threat hunting |
Response Layer (When Incidents Happen)
| Stage | Tool/Technique | AI Enhancement |
|---|---|---|
| Alert | PagerDuty, Opsgenie | AI-filtered alerts (reduce noise) |
| Triage | SOAR playbooks | Automated initial response |
| Investigate | Log analysis + AI correlation | AI-assisted root cause identification |
| Contain | Automated isolation scripts | Pre-built containment actions |
| Recover | Runbooks + rollback procedures | AI-verified recovery steps |
| Learn | Postmortem generation | AI-generated Five Whys analysis |
✅ Quick Check: You implement all three layers. A new vulnerability is discovered in a dependency. Trace how your stack handles it end-to-end: (Answer: (1) SCA scan detects CVE in next CI run → AI triages as HIGH risk (reachable function, internet-facing service) → PR blocked. (2) AI generates fix suggestion → developer reviews and applies → PR merged. (3) Monitoring adds detection rule for exploitation of that CVE. (4) Compliance dashboard updates to show remediation timeline. (5) If the CVE was already in production, the monitoring rule watches for exploitation attempts while the fix deploys. All layers connected, all automated except human review of the fix.)
Implementation Roadmap
Quarter 1: Foundation
Week 1-2: SCA scanning in CI/CD
- Integrate Snyk or pip-audit/npm-audit
- Configure AI triage rules
- Set merge-blocking thresholds
Week 3-4: Secret scanning
- Pre-commit hooks (GitLeaks)
- Server-side scanning in CI
- Establish rotation procedures
Week 5-8: Compliance automation
- Map controls to evidence sources
- Automate evidence collection scripts
- Build compliance dashboard
Week 9-12: Review and optimize
- Analyze false positive rates
- Tune AI triage thresholds
- Document runbooks
Quarter 2: Expansion
- Add SAST scanning (Semgrep)
- Implement IaC scanning (Checkov)
- Build incident response playbooks
- Deploy monitoring enhancements
Quarter 3: Maturity
- Threat modeling for critical services
- Zero-trust migration (Phase 1)
- Penetration test preparation and execution
- Advanced monitoring and anomaly detection
Quarter 4: Optimization
- Full pipeline integration testing
- Red team exercises
- Compliance audit execution
- Stack performance optimization
Course Recap
| Lesson | What You Learned | When to Use |
|---|---|---|
| 1. Welcome | AI DevSecOps landscape | Strategic planning |
| 2. Vulnerability Scanning | SAST, SCA, container scanning + AI triage | Every PR and build |
| 3. Infrastructure | Terraform, K8s, cloud security review | IaC changes and audits |
| 4. CI/CD Security | Pipeline security gates, secrets, policy-as-code | Pipeline configuration |
| 5. Monitoring | Log analysis, incident response, playbooks | Production operations |
| 6. Compliance | Evidence automation, policy generation, audit prep | Continuous + audit cycles |
| 7. Threat Defense | Threat modeling, zero trust, pen test prep | Quarterly planning |
| 8. Capstone | Integrated stack and implementation roadmap | Your DevSecOps practice |
Key Takeaways
- Start with 3 high-ROI implementations: SCA with AI triage, secret scanning, and compliance automation
- Connect your tools — siloed security tools create blind spots that integrated stacks don’t
- AI in security requires its own risk management: no production data in external AI, human-review all recommendations
- Implementation is a multi-quarter journey — foundation first, then expand layer by layer
- The goal is security as a feature of your pipeline, not a gate that slows it down
- AI makes enterprise-grade security practices accessible to teams of any size
Knowledge Check
Complete the quiz above first
Lesson completed!