STRIDE Threat Modeling: DFD, Risk Analysis & Mitigation

Define threat modeling as a secure by design process in the software development lifecycle, using Stride to identify threats early and support HIPAA, GDPR, and ISO 27,001 compliance.

Explore the stride framework, a six-threat model: spoofing, tampering, repudiation, information disclosure, denial of service, and elevation of privilege, applied to the Health Track app's data flows and trust boundaries.

Learn to visualize system data flows with data flow diagrams (DFDs), identifying processes, data stores, external entities, data flows, and trust boundaries for stride-based threat modeling.

Apply the stride threat modeling framework by building a data flow diagram for the health track app, mapping external entities, login, health data processing, scheduling, and data stores.

Apply stride to each component of the health track app's data flow diagram to identify spoofing, tampering, repudiation, information disclosure, denial of service, and elevation of privilege.

Identify threats with the Stride framework, then evaluate and prioritize them using Dread scoring and a risk matrix to guide focused mitigations in the Health Track app.

Apply risk analysis with a two-dimensional risk matrix to prioritize threats by likelihood and impact. Address top risks like T1 spoofing on the login handler with immediate remediation.

Map STRIDE threats to specific security controls to identify effective countermeasures, then design defense in depth across application, system, and network layers with strong authentication, RBAC, logging, and encryption.

Stride threats to robust controls by enforcing encryption in transit and at rest, strong TLS, AES 256, access controls, data minimization, and tamper-resistant logging with analysis for anomaly detection.

Monitor system changes that affect threats as a living Stride process, embedding threat-model reviews in the development lifecycle and tracking risks with CI/CD alerts, QA, and vulnerability testing.

Guard against tampering in health track data by enforcing data integrity with hashing, digital signatures, and strict RBAC, while logging changes and securing data in transit with TLS.

Apply stride threat modeling to health track app using data flow diagrams to identify spoofing, tampering, information disclosure, denial of service, and elevation of privilege, then prioritize mitigations.