A tailored course, built for your situation
Mastering CIS Controls for Senior Software Engineers
A structured path to deep technical command of security control implementation in AI/ML environments
$199 one-time
24-hour access provisioning
30-day money-back guarantee
Hand-built implementation playbook
12 modules. 12 chapters per module. 144 chapters total.
12 modules, each with 12 chapters (144 chapters total), text-based, plus downloadable templates and a hand-built implementation playbook delivered alongside course access.
Most security training stops at awareness, this course gets down to configuration-level execution within complex AI/ML stacks.
The situation this course is for
Security frameworks are often taught at a distance, but in practice, implementation demands exact syntax, sequencing, and system-specific tuning, especially in AI/ML platforms where drift undermines control consistency.
Who this is for
Senior software engineers in cloud-scale environments who own or influence security integration in AI/ML systems and want mastery-level command of the CIS Controls
Who this is not for
Entry-level compliance staff, auditors without technical implementation roles, or managers seeking high-level overviews
What you walk away with
- Deploy CIS Controls with exact configuration benchmarks mapped to AI/ML platform components
- Automate control validation across containerized and orchestration layers
- Integrate control mapping directly into CI/CD pipelines
- Lead internal reviews with source-level examples and implementation logic
- Produce audit-ready artefacts that reflect actual system state
The 12 modules (with all 144 chapters)
Module 1. Introduction to CIS Controls in AI/ML Systems
Ground the CIS Controls in the context of AI/ML infrastructure, focusing on control relevance, risk surface alignment, and integration touchpoints.
12 chapters in this module
- What CIS Controls are and why they matter
- AI/ML stack components and control mapping
- Control baseline selection (Level 1 vs 2)
- How CIS compares to NIST CSF and ISO 27001
- Security baseline as code principles
- Integration points with MLOps pipelines
- Control ownership in platform teams
- Documentation expectations for auditors
- Tooling ecosystem for control enforcement
- Versioning control configurations
- Handling exceptions with evidence
- From framework to implementation roadmap
Module 2. CIS Control 1: Inventory and Control of Hardware Assets
Establish and maintain a fully accurate inventory of hardware used in AI/ML infrastructure, including on-premise and cloud-hosted systems.
12 chapters in this module
- Automatic discovery via agent and API
- Tagging standards for asset classification
- Hardware inventory in hybrid environments
- Integration with configuration management DB
- Handling ephemeral compute instances
- Validation frequency and thresholds
- Enforcement of unauthorized device policy
- Role-based access to inventory data
- Audit trail for asset changes
- Mapping to compliance requirements
- Automated reporting templates
- Drift detection logic
Module 3. CIS Control 2: Inventory of Software Assets
Build a comprehensive software register for AI/ML systems, including libraries, frameworks, and dependencies.
12 chapters in this module
- Software bill of materials (SBOM) generation
- Python and container image introspection
- Scanning for embedded libraries
- License compliance tracking
- Version lifecycle monitoring
- Integration with package managers
- Container layer analysis
- Real-time software change alerts
- Mapping software to CIS subcontrols
- Automated approval workflows
- Reporting for security reviews
- Handling legacy software exceptions
Module 4. CIS Control 3: Continuous Vulnerability Management
Implement proactive scanning and remediation for vulnerabilities in AI/ML environments.
12 chapters in this module
- Vulnerability scanner selection criteria
- Scheduling automated scans
- Prioritization using CVSS and context
- Integration with ticketing systems
- Patch deployment windows
- Zero-day response protocol
- Container image vulnerability checks
- AI model dependency scanning
- False positive triage process
- Reporting to platform leadership
- Remediation SLAs by severity
- Evidence for audit trail
Module 5. CIS Control 4: Controlled Use of Administrative Privileges
Secure and monitor privileged access within AI/ML platforms.
12 chapters in this module
- Principle of least privilege definition
- Just-in-time access workflows
- Multi-factor approval for elevation
- Credential rotation automation
- Session logging and review
- Break-glass account protocols
- Privilege auditing frequency
- Role-based access control models
- Integration with identity provider
- Emergency override documentation
- Privilege drift detection
- Monitoring for anomalous use
Module 6. CIS Control 5: Secure Configuration for Hardware and Software
Ensure baseline security configurations are enforced across all system components.
12 chapters in this module
- CIS Benchmarks for Linux and Docker
- Hardening AI training environments
- Configuration drift detection
- Automated remediation scripts
- Secure boot and firmware checks
- File integrity monitoring
- Kernel parameter hardening
- SSH configuration standards
- Disabling insecure services
- Enabling logging and telemetry
- Validation via automated checks
- Audit log retention policies
Module 7. CIS Control 6: Maintenance, Monitoring, and Analysis of Audit Logs
Implement centralized logging with detection capabilities for AI/ML systems.
12 chapters in this module
- Log sources in AI/ML stack
- Centralized log aggregation setup
- Log retention compliance
- Anomaly detection rules
- Correlation across services
- Real-time alerting configuration
- Log normalization standards
- Querying for incident response
- Audit readiness reporting
- Retention tiering strategy
- Encryption of log data
- Access control for log systems
Module 8. CIS Control 7: Email and Web Browser Protections
Harden end-user applications commonly used in development workflows.
12 chapters in this module
- Browser security configuration
- Extension whitelisting
- Phishing-resistant authentication
- URL filtering for developers
- Sandboxing web content
- Email attachment scanning
- Safe link rewriting
- User training integration
- Reporting suspicious activity
- Integration with endpoint protection
- Monitoring for credential phishing
- Zero-trust browser principles
Module 9. CIS Control 8: Malware Defenses
Establish and maintain malware prevention across development and production systems.
12 chapters in this module
- Antivirus agent deployment
- Real-time scanning policies
- Signature and behavior detection
- Container image malware checks
- File reputation services
- Quarantine workflows
- Incident triage steps
- Endpoint detection and response
- Integration with SIEM
- Automated threat feeds
- Whitelisting trusted binaries
- Recovery from compromise
Module 10. CIS Control 9: Limitation and Control of Network Ports, Protocols, and Services
12 chapters in this module
- Network inventory methods
- Port and protocol baselining
- Firewall rule standardization
- Micro-segmentation basics
- Service discovery automation
- Unapproved service detection
- Protocol deprecation planning
- Network access control setup
- Encrypted traffic inspection
- Zero trust network access
- DNS filtering integration
- Network change approval process
Module 11. CIS Control 10: Data Recovery
Ensure reliable backup and restoration of critical AI/ML data and configurations.
12 chapters in this module
- Backup scope definition
- Scheduled vs event-driven backups
- Encryption of backup data
- Test restoration process
- RPO and RTO alignment
- Versioning of model artifacts
- Immutable backup storage
- Air-gapped recovery options
- Disaster recovery runbooks
- Monitoring backup success
- Retention policies
- Audit trail for data recovery
Module 12. Integration and Automation of CIS Controls
Unify control implementation into CI/CD pipelines and platform governance workflows.
12 chapters in this module
- IaC security scanning
- Policy as code frameworks
- Automated compliance checks
- Control integration in PR workflows
- Dashboard for control status
- Alert routing to on-call
- Monthly control review process
- Cross-team control alignment
- Documentation automation
- Third-party audit preparation
- Continuous improvement cycle
- Scaling across environments
How this maps to your situation
- Onboarding new AI/ML projects with secure baselines
- Responding to internal security reviews
- Preparing for external compliance audits
- Leading security improvements in platform teams
Before vs. after
Before
Security controls treated as compliance checkboxes, often implemented late or generically
After
Proactive, automated control integration into AI/ML systems with exact configuration knowledge
What's included with your purchase
- 12 modules with 12 chapters each (144 chapters)
- Downloadable templates and worked examples for every module
- Hand-built implementation playbook delivered alongside course access
- 30-day money-back guarantee
Delivery and format
- Course and learning environment access provisioned within 24 hours of purchase
- Hand-built implementation playbook delivered alongside course access
Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access.
Time investment: Approximately 3 hours per module, designed for integration into busy engineering schedules.
If nothing changes
Without deep control mastery, security integration remains reactive, increasing audit findings, rework, and incident risk in AI/ML environments.
How this compares to the alternatives
Generic security courses teach frameworks at a distance. This course delivers exact implementation patterns, configuration examples, and automation scripts tailored to AI/ML platforms.
Frequently asked
Who is this course for?
Senior software engineers working on AI/ML platforms who want to master the technical implementation of CIS Controls.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Is prior security certification required?
No. The course is designed for practitioners building systems, not auditors or compliance staff.
$199 one-time. Approximately 3 hours per module, designed for integration into busy engineering schedules..
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.
30-day money-back guarantee·
144 chapters·
Hand-built playbook included·
Account access within 24 hours