Dev SecOps

IT Courses

This comprehensive 120-hour curriculum provides a complete journey from DevSecOps fundamentals to advanced AI-powered security operations. The…

AdminElevate
25
120h
0
(0)

This comprehensive 120-hour curriculum provides a complete journey from DevSecOps fundamentals to advanced AI-powered security operations. The project-based approach ensures practical skills with industry-standard tools, while the extensive AI integration modules—including Security Scan Agents, Compliance Audit Agents, and agentic AI automation —prepare students for the future of intelligent DevSecOps where AI transforms security from reactive to autonomous. Students will graduate with a robust portfolio of 7+ projects demonstrating their expertise across the entire DevSecOps spectrum and will be prepared for roles such as DevSecOps Engineer, Security Automation Engineer, and AI Security Specialist.

What Will You Learn?

Master DevSecOps fundamentals including shift-left security principles, secure SDLC integration, and the cultural transformation required for DevSecOps adoption
Implement comprehensive security testing across the CI/CD pipeline including SAST, DAST, SCA, container scanning, and infrastructure scanning
Build and secure CI/CD pipelines with Jenkins, GitHub Actions, and GitLab CI incorporating automated security gates and quality checks
Harden containerized environments with Docker security best practices, image scanning, and runtime protection
Secure Kubernetes deployments with RBAC, network policies, pod security standards, and admission controllers
Implement Infrastructure as Code security with Terraform scanning, policy-as-code using OPA, and compliance automation
Leverage AI-powered DevSecOps tools including agentic AI for vulnerability remediation, intelligent audit compliance, and automated security fixes
Apply advanced AI techniques like AI-generated remediation suggestions, predictive failure analysis, and autonomous security agents to reduce MTTR by up to 70%

Course Curriculum

Introduction to DevSecOps

Evolution from DevOps to DevSecOps: why security must shift left
DevSecOps principles: culture, automation, measurement, sharing (CALMS framework extended)
The business case for DevSecOps: reducing vulnerabilities, faster remediation, compliance benefits
DevSecOps Maturity Model (DSOMM) overview from OWASP
Key metrics: mean time to detect (MTTD), mean time to respond (MTTR), vulnerability escape rate

Security Champions & Culture Transformation

Security champion model: developers as in-team security advocates
Role of champions: translating between security and engineering teams
Building sustainable champion programs with blueprints and frameworks
Training developers to think like attackers without becoming security specialists
Case study: Fortune 500 company reduced vulnerability escape rate by 73% over six months with champions

Threat Modeling & Risk Assessment

Threat modeling methodologies: STRIDE, DREAD, PASTA
Identifying assets, threats, and vulnerabilities in applications
Risk assessment and prioritization frameworks
Integrating threat modeling into agile development
Introduction to automated threat modeling tools

Project 1: Security Champions Program Design

Design comprehensive security champions program for a hypothetical organization
Include champion selection criteria, training curriculum, responsibilities, and incentives
Develop metrics to measure program effectiveness (e.g., vulnerability escape rate reduction)
Create communication templates for champions to use with their teams
Document implementation roadmap with phases and milestones

CI/CD Security Fundamentals

CI/CD pipeline architecture and attack surfaces
Securing build environments: isolated runners, ephemeral agents
Secret management in CI/CD: HashiCorp Vault, GitHub Secrets, Jenkins Credentials
Pipeline integrity: signed commits, artifact signing, SBOM generation
Dependency confusion and supply chain attacks

Jenkins Security Hardening

Jenkins architecture: master-agent security
Authentication and authorization strategies
Securing Jenkinsfiles: credentials binding, script approvals
Plugin security and updates
Pipeline as code security best practices

GitHub Actions & GitLab CI Security

GitHub Actions security model: workflows, runners, permissions
Securing workflows with OIDC for cloud access
Preventing injection attacks in workflows
GitLab CI security features: protected variables, security scanners
Integrating security tools in CI/CD

Project 2: End-to-End Secure CI/CD Pipeline

Design and implement comprehensive secure CI/CD pipeline using Jenkins or GitHub Actions
Document pipeline architecture and security controls
Demonstrate prevention of insecure deployments

Static Application Security Testing (SAST)

SAST fundamentals: analyzing source code for vulnerabilities
SAST tools: SonarQube, Semgrep, Snyk Code, Checkmarx
Integrating SAST into CI/CD pipelines
False positive management and tuning rules
AI-assisted code reviews for vulnerability detection

Software Composition Analysis

SCA fundamentals: identifying vulnerable dependencies
SCA tools: Snyk, OWASP Dependency Check, WhiteSource
License compliance and open-source governance
Automated dependency updates and remediation
SBOM management and vulnerability intelligence

Dynamic Application Security Testing (DAST)

DAST fundamentals: testing running applications
DAST tools: OWASP ZAP, Burp Suite, Acunetix
Integrating DAST into CI/CD pipelines
Automated test case generation with AI assistance
API security testing

Project 3: Integrated Security Testing Pipeline

Build comprehensive security testing pipeline with SAST, SCA, and DAST
Configure all tools to run automatically on code changes
Implement quality gates that block deployments based on severity thresholds
Create unified dashboard showing security findings across tools
Set up automated remediation workflows for high-severity issues
Document security testing strategy and metrics

Docker Security Hardening

Docker security best practices: least privilege, non-root users
Dockerfile security: multi-stage builds, minimal base images
Image scanning with Trivy, Clair, Docker Bench Security
Distroless images and scratch images
Secure registry configuration with Harbor

Container Runtime Security

Runtime security monitoring with Falco
Seccomp and AppArmor profiles
Read-only root filesystems
Resource limits and DoS prevention
Container escape prevention

Kubernetes Security Fundamentals

Kubernetes architecture security: control plane, etcd, kubelet
Authentication and authorization: X.509, OIDC, RBAC
Network policies for micro-segmentation
Pod Security Standards (PSS) and Pod Security Admission (PSA)
Secret management in Kubernetes

Advanced Kubernetes Security

Admission controllers: validating and mutating webhooks
Open Policy Agent (OPA) and Gatekeeper for policy enforcement
Service mesh security (Istio/Linkerd) with mTLS
Runtime security in Kubernetes with Falco
Kubernetes CIS benchmarks

Project 4: Containerized App Hardening

Containerize a sample application with security best practices
Implement comprehensive image scanning in CI/CD pipeline
Deploy hardened containers to Kubernetes cluster
Configure RBAC, network policies, and pod security standards
Set up runtime security monitoring with Falco
Implement OPA policies for admission control
Document all security controls with validation evidence

Terraform Security Fundamentals

Infrastructure as Code (IaC) security principles
Terraform state security: remote state, encryption, locking
Sensitive data handling in Terraform
Module security and versioning
Terraform security scanning tools overview

IaC Scanning with Checkov & tfsec

Checkov for Terraform security scanning
tfsec for infrastructure analysis
Custom policies and skip rules
Integrating IaC scanning in CI/CD pipelines
Remediating common misconfigurations (open security groups, unencrypted storage)

Policy as Code with Open Policy Agent

OPA fundamentals and Rego language
Policy-as-code for infrastructure compliance
Enforcing policies across cloud environments
Integrating OPA with Terraform and Kubernetes
Compliance as code for CIS benchmarks, GDPR, HIPAA

Project 5: Secure Infrastructure Automation

Design complete infrastructure for web application using Terraform
Implement security scanning with Checkov and tfsec in CI/CD
Create custom policies for organization-specific requirements
Set up OPA for policy enforcement across environments
Document all security controls mapped to compliance frameworks (CIS, NIST)
Demonstrate prevention of insecure infrastructure deployments

Introduction to AI in DevSecOps

The evolution from static automation to autonomous orchestration
How AI is transforming security operations: from detection to remediation
Key AI applications across the DevSecOps lifecycle
Agentic DevSecOps: AI agents that reason through complex environments
Benefits: reduced MTTR, automated compliance, contextual fixes

Security Scan Agent for Automated Remediation

AI-powered security scanning that goes beyond CVE lists
Transforming vulnerability management from manual hurdle to automated accelerator
Correlating vulnerabilities with application context for prioritization
AI-generated code fixes for detected vulnerabilities
Reducing Mean Time to Repair (MTTR) dramatically

Compliance Audit Agent for Continuous Compliance

AI-powered compliance monitoring across SOC2, HIPAA, NIST frameworks
Automated evidence collection and continuous compliance
Proactive monitoring of changes against regulatory frameworks
Intelligent explanations of compliance violations
Turning audit readiness from quarterly fire drill into automated standard

Architecture Analyzer & SQL Security Agents

AI-powered architecture analysis against organizational “Golden Path”
Identifying regressions, circular dependencies, design pattern deviations
SQL Security Scan Agent for data-layer protection
Deep inspection of SQL scripts for injection vulnerabilities
Shifting data security into CI/CD pipeline without manual DBA review

Agentic DevSecOps & AI Orchestration

Fleet of specialized AI agents for security functions
Agent coordination for complex investigation and remediation
GitLab Duo Agent Platform for agentic AI automation
Custom agents for automated complex development tasks
External agent integration with Claude Code, OpenAI Codex

Project 6: AI-Enhanced Security Pipeline

Build comprehensive security pipeline with AI capabilities
Integrate with existing security tools (SAST, SCA, container scanning)
Use AI capabilities for intelligent remediation
Document AI applications in DevSecOps workflows
Demonstrate reduction in remediation time

Final Project: Enterprise DevSecOps Transformation with AI Integration

Phase 1: Infrastructure as Code with Security
Phase 2: Secure CI/CD Pipeline
Phase 3: Container & Kubernetes Security
Phase 4: AI-Powered Security Operations
Phase 5: Documentation & Compliance

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Dev SecOps

What Will You Learn?

Course Curriculum

Introduction to DevSecOps

Evolution from DevOps to DevSecOps: why security must shift left

DevSecOps principles: culture, automation, measurement, sharing (CALMS framework extended)

The business case for DevSecOps: reducing vulnerabilities, faster remediation, compliance benefits

DevSecOps Maturity Model (DSOMM) overview from OWASP

Key metrics: mean time to detect (MTTD), mean time to respond (MTTR), vulnerability escape rate

Security Champions & Culture Transformation

Security champion model: developers as in-team security advocates

Role of champions: translating between security and engineering teams

Building sustainable champion programs with blueprints and frameworks

Training developers to think like attackers without becoming security specialists

Case study: Fortune 500 company reduced vulnerability escape rate by 73% over six months with champions

Threat Modeling & Risk Assessment

Threat modeling methodologies: STRIDE, DREAD, PASTA

Identifying assets, threats, and vulnerabilities in applications

Risk assessment and prioritization frameworks

Integrating threat modeling into agile development

Introduction to automated threat modeling tools

Project 1: Security Champions Program Design

Design comprehensive security champions program for a hypothetical organization

Include champion selection criteria, training curriculum, responsibilities, and incentives

Develop metrics to measure program effectiveness (e.g., vulnerability escape rate reduction)

Create communication templates for champions to use with their teams

Document implementation roadmap with phases and milestones

CI/CD Security Fundamentals

CI/CD pipeline architecture and attack surfaces

Securing build environments: isolated runners, ephemeral agents

Secret management in CI/CD: HashiCorp Vault, GitHub Secrets, Jenkins Credentials

Pipeline integrity: signed commits, artifact signing, SBOM generation

Dependency confusion and supply chain attacks

Jenkins Security Hardening

Jenkins architecture: master-agent security

Authentication and authorization strategies

Securing Jenkinsfiles: credentials binding, script approvals

Plugin security and updates

Pipeline as code security best practices

GitHub Actions & GitLab CI Security

GitHub Actions security model: workflows, runners, permissions

Securing workflows with OIDC for cloud access

Preventing injection attacks in workflows

GitLab CI security features: protected variables, security scanners

Integrating security tools in CI/CD

Project 2: End-to-End Secure CI/CD Pipeline

Design and implement comprehensive secure CI/CD pipeline using Jenkins or GitHub Actions

Document pipeline architecture and security controls

Demonstrate prevention of insecure deployments

Static Application Security Testing (SAST)

SAST fundamentals: analyzing source code for vulnerabilities

SAST tools: SonarQube, Semgrep, Snyk Code, Checkmarx

Integrating SAST into CI/CD pipelines

False positive management and tuning rules

AI-assisted code reviews for vulnerability detection

Software Composition Analysis

SCA fundamentals: identifying vulnerable dependencies

SCA tools: Snyk, OWASP Dependency Check, WhiteSource

License compliance and open-source governance

Automated dependency updates and remediation

SBOM management and vulnerability intelligence

Dynamic Application Security Testing (DAST)

DAST fundamentals: testing running applications

DAST tools: OWASP ZAP, Burp Suite, Acunetix

Integrating DAST into CI/CD pipelines

Automated test case generation with AI assistance

API security testing

Project 3: Integrated Security Testing Pipeline

Build comprehensive security testing pipeline with SAST, SCA, and DAST

Configure all tools to run automatically on code changes

Implement quality gates that block deployments based on severity thresholds

Create unified dashboard showing security findings across tools

Set up automated remediation workflows for high-severity issues

Document security testing strategy and metrics

Docker Security Hardening

Docker security best practices: least privilege, non-root users

Dockerfile security: multi-stage builds, minimal base images

Image scanning with Trivy, Clair, Docker Bench Security

Distroless images and scratch images

Secure registry configuration with Harbor