Data Security in Application Development

Description

What does the Data Security in Application Development course cover?

Data Security in Application Development is covered here in 9 modules: Threat Modeling and Risk Assessment in Application Design, Secure Authentication and Identity Management, Data Protection and Encryption Strategies and 6 more. The outline lists 63 specific topics, opening with conduct STRIDE-based threat modeling during the architecture phase to identify spoofing, tampering, and elevation of privilege risks in microservices.

How do you approach Data Security in Application Development step by step?

The work is sequenced in 9 stages. It starts with Threat Modeling and Risk Assessment in Application Design, moves through Secure Authentication and Identity Management and Data Protection and Encryption Strategies, and ends at Zero Trust Architecture Implementation. Each stage carries its own topic list, so the sequence is followed rather than summarised.

What is in Module 1 of the Data Security in Application Development course?

Module 1 is Threat Modeling and Risk Assessment in Application Design. It works through conduct STRIDE-based threat modeling during the architecture phase to identify spoofing, tampering, and elevation of privilege risks in microservices., select appropriate threat modeling tools (e.g., Microsoft Threat Modeling Tool, OWASP Threat Dragon) based on team expertise and integration with CI/CD pipelines., map data flow diagrams to attack surfaces.

How is the Data Security in Application Development course delivered?

The Data Security in Application Development course is fully self-paced with immediate online access after enrolment. Access does not expire and future updates are included at no cost. It can be taken on any device, and a certificate of completion is issued by The Art of Service when you finish.

How much does the Data Security in Application Development course cost?

The Data Security in Application Development course is $296 as a one time payment. There is no subscription, no per seat licence and no hidden fee. Enrolment carries a 30 day satisfied or refunded guarantee, so it can be assessed in full before you commit.

More answers: what you get with every course, refund policy, all help answers.

This curriculum spans the breadth of a multi-workshop security integration program, addressing the same technical depth and cross-system coordination required in enterprise advisory engagements focused on secure application delivery.

Module 1: Threat Modeling and Risk Assessment in Application Design

Conduct STRIDE-based threat modeling during the architecture phase to identify spoofing, tampering, and elevation of privilege risks in microservices.
Select appropriate threat modeling tools (e.g., Microsoft Threat Modeling Tool, OWASP Threat Dragon) based on team expertise and integration with CI/CD pipelines.
Map data flow diagrams to attack surfaces and prioritize mitigations based on exploit likelihood and business impact.
Integrate threat modeling outputs into Jira or Azure DevOps for traceability and mitigation tracking across sprints.
Define risk acceptance criteria for third-party libraries with known vulnerabilities when remediation timelines exceed business deadlines.
Coordinate cross-functional threat modeling workshops with security, development, and product teams to align on risk ownership.
Update threat models incrementally with each major feature release or infrastructure change.

Module 2: Secure Authentication and Identity Management

Implement OAuth 2.1 with PKCE for public clients to prevent authorization code interception in mobile and SPAs.
Configure conditional access policies in identity providers (e.g., Azure AD, Okta) based on device compliance, location, and sign-in risk.
Enforce multi-factor authentication (MFA) selectively for high-privilege roles and sensitive operations using step-up authentication.
Design token lifetime policies balancing security and user experience, including short-lived access tokens with secure refresh mechanisms.
Isolate identity management from application logic using dedicated identity services or identity gateways.
Implement secure logout across all application contexts, including clearing tokens from storage and invalidating refresh tokens server-side.
Monitor and alert on anomalous authentication patterns, such as repeated failed logins from new geolocations.

Module 3: Data Protection and Encryption Strategies

Classify data by sensitivity (public, internal, confidential, regulated) and apply encryption controls accordingly.
Implement field-level encryption for sensitive data (e.g., PII, financial data) in databases using application-layer encryption libraries.
Manage encryption keys using a dedicated key management service (e.g., AWS KMS, Hashicorp Vault) with strict IAM policies and audit logging.
Choose between envelope encryption and direct key wrapping based on performance requirements and key rotation frequency.
Enforce TLS 1.3 for all data in transit and disable legacy cipher suites across load balancers and reverse proxies.
Define data residency requirements and configure encryption key locations to comply with jurisdictional regulations.
Implement secure key rotation procedures with dual control and automated re-encryption workflows.

Module 4: Secure Coding and Dependency Management

Integrate SAST tools (e.g., SonarQube, Checkmarx) into pull request pipelines with defined severity thresholds for blocking merges.
Enforce input validation and output encoding at API boundaries to prevent injection attacks, including stored and reflected XSS.
Use parameterized queries or ORM frameworks with strict escaping to eliminate SQL injection risks in dynamic queries.
Establish a software bill of materials (SBOM) using tools like Syft or Dependency-Track for all production artifacts.
Implement automated patching policies for open-source dependencies based on CVSS scores and exploit availability.
Freeze and audit third-party libraries before production deployment, especially for transitive dependencies.
Conduct manual code reviews for security-critical components, such as authentication flows and data access layers.

Module 5: API Security and Access Control

Enforce rate limiting and quota management on public APIs to prevent abuse and DoS attacks.
Validate and sanitize all API inputs using schema definitions (e.g., OpenAPI) with strict type and format constraints.
Implement role-based and attribute-based access control (RBAC/ABAC) at the API gateway and service level.
Use short-lived, scoped access tokens for service-to-service communication instead of shared secrets.
Log and monitor API access patterns, including user-agent, IP, and endpoint usage for anomaly detection.
Expose only necessary endpoints in production; disable debugging and administrative APIs in non-development environments.
Apply mutual TLS (mTLS) for internal microservices to authenticate and encrypt inter-service traffic.

Module 6: Secure Deployment and Infrastructure as Code

Scan IaC templates (e.g., Terraform, CloudFormation) for misconfigurations using tools like Checkov or tfsec before deployment.
Enforce least privilege in cloud IAM roles used by CI/CD pipelines, separating deployment, rollback, and monitoring permissions.
Isolate build environments from production networks and apply host-based firewalls and endpoint protection.
Sign and verify container images using Cosign or Notary to ensure integrity and provenance in registries.
Configure immutable infrastructure patterns to prevent runtime configuration drift and unauthorized changes.
Automate drift detection and alerting for production environments using configuration monitoring tools.
Restrict direct access to production systems; require all changes to flow through version-controlled deployment pipelines.

Module 7: Logging, Monitoring, and Incident Response

Centralize logs from applications, infrastructure, and security tools using a SIEM (e.g., Splunk, Sentinel) with retention policies aligned to compliance.
Mask sensitive data (e.g., tokens, passwords) in logs at the application level before transmission.
Define and deploy correlation rules to detect suspicious behavior, such as privilege escalation or data exfiltration patterns.
Configure real-time alerts for critical security events with escalation paths and on-call rotations.
Conduct tabletop exercises to validate incident response playbooks for data breaches and ransomware scenarios.
Preserve forensic artifacts (logs, memory dumps, container states) during incidents using write-once storage.
Integrate incident response workflows with ticketing and communication platforms while maintaining chain of custody.

Module 8: Compliance and Governance in Development Lifecycle

Map security controls to regulatory frameworks (e.g., GDPR, HIPAA, PCI-DSS) and maintain a compliance matrix for audits.
Conduct privacy impact assessments (PIA) for features involving personal data collection or processing.
Implement data minimization by design, collecting only data required for specified business purposes.
Enforce data retention and deletion policies in code, including automated purging of expired records.
Document security decisions in architecture decision records (ADRs) for traceability and governance review.
Perform regular third-party risk assessments for vendors with access to application data or infrastructure.
Integrate compliance checks into CI/CD pipelines using policy-as-code tools like Open Policy Agent.

Module 9: Zero Trust Architecture Implementation

Implement device posture checks before granting access to internal applications using endpoint detection and response (EDR) integration.
Adopt a “never trust, always verify” model by requiring authentication and authorization for every resource request.
Deploy micro-segmentation in cloud environments to restrict lateral movement between workloads.
Use service meshes (e.g., Istio, Linkerd) to enforce mTLS and fine-grained traffic policies between services.
Replace static network ACLs with identity- and context-aware access policies enforced at the application layer.
Continuously validate user and device trust through real-time signals like location, behavior, and risk score.
Design fallback mechanisms for identity providers to maintain availability during outages without compromising security.