Secure-by-Design Cybersecurity For Medical Devices: Advanced Threat Modeling Frameworks For 2025

The cybersecurity landscape for connected and software-driven medical devices is undergoing rapid transformation. In 2025, regulators expect manufacturers to demonstrate proactive, system-level cybersecurity risk management that is fully aligned with secure-by-design principles. Threat modeling has moved from an optional best practice to an essential requirement embedded across the device lifecycle.

Medical devices now operate within interconnected ecosystems: cloud platforms, hospital networks, mobile apps, wearable sensors, firmware, and third-party components. This interconnected complexity increases attack surfaces, making structured threat modeling indispensable for identifying confidentiality, integrity, and availability risks early in design.

Threat modeling enables manufacturers to:

• Detect design vulnerabilities before they reach implementation
• Map security risks to regulatory expectations
• Create cyber-resilient architecture
• Reduce recall risk and postmarked exposure
• Build defensible technical documentation for regulatory submissions

Maven Regulatory Solutions supports manufacturers in adopting secure-by-design practices aligned with global cybersecurity expectations, enabling stronger compliance and safer product ecosystems.

Regulatory Context: 2025 Cybersecurity Expectations

Global authorities increasingly recognize that cybersecurity and patient safety are inseparable. While terminology varies, all agencies now expect structured, repeatable threat modeling integrated into risk management.

Key 2025 Expectations Across Major Regulators

• FDA: Threat modeling within the Secure Product Development Framework (SPDF), system diagrams, exploitability scoring, and traceability of mitigations.
• Health Canada: Formal documentation of attack surface analysis and verification of cybersecurity risk controls.
• TGA / GCC / EU MDR/IVDR: Evidence of cybersecurity-by-design, secure architectures, and vulnerability management continuity.
• ISO & IEC Standards:
  • ISO 14971: Harmonized safety–security risk linkage
  • AAMI TIR57: Threat modeling methodology guidance
  • IEC 81001-5-1: Secure lifecycle requirements for medical software

Regulators now expect manufacturers to integrate security risk analysis with safety engineering to support system-level clinical risk reduction.

Threat Modeling in Context: Bridging Safety and Cybersecurity

Medical devices traditionally rely on FMEA, FMECA, and Fault Tree Analysis (FTA) to evaluate safety risks. Cybersecurity introduces parallel but distinct concepts:

Mapping Safety and Security Concepts

• Hazard (Safety) ↔ Threat (Cybersecurity)
• Failure Cause ↔ Attack Vector
• Severity ↔ Impact (CIA)
• Probability of Harm ↔ Exploitability
• Control Measures ↔ Technical and Procedural Safeguards

Semi-automated threat modeling approaches that align with safety engineering enable consistent implementation across the product lifecycle.

Threat Modeling as a Core Component of Cyber Risk Management

Threat modeling reinforces cybersecurity risk management by evaluating how data moves, where it’s processed, and how attackers might exploit weak points.

Key Capabilities Enabled by Threat Modeling

• Identification of system-level vulnerabilities
• Analysis of attack chains, not isolated failure points
• Clarification of cybersecurity requirements early in design
• Prioritized mitigation based on exploitability scoring
• Cross-functional collaboration between engineering, quality, and IT security

Alignment with SPDF

Threat modeling supports all SPDF pillars:

• Security Risk Management
• Security Architecture
• Security Testing and Validation
• Post market Monitoring and Patching

How to Begin: Practical, Scalable Threat Modeling Approach

A structured threat modeling workflow maximizes clarity and repeatability:

Core Workflow

1. Diagram the System
   Construct Data Flow Diagrams (DFDs), UML diagrams, cloud architectures, or subsystem models to visualize components, trust boundaries, and attack surfaces.
2. Identify Threats
   Apply STRIDE, attack trees, misuse cases, or custom elicitation frameworks to document realistic attack vectors.
3. Mitigate Risks
   Implement security controls mapped to device architecture and clinical use context (e.g., access control, encryption, authentication, network segmentation, secure boot).
4. Validate & Document
   Verify mitigation coverage, evaluate residual risk, and maintain living documentation throughout the lifecycle.

Artifacts Commonly Used

• Data flow diagrams
• System context models
• API and interface maps
• Wireless communication diagrams
• Software dependency trees
• Cloud data exchange flows

Structured Threat Elicitation Methods

STRIDE Framework

STRIDE remains the most widely used threat categorization model for medical devices due to its simplicity and applicability.

STRIDE Categories

• Spoofing
• Tampering
• Repudiation
• Information Disclosure
• Denial of Service
• Elevation of Privilege

STRIDE enables systematic analysis of every data flow, trust boundary, and system component.

STRIDE Applied to Medical Device Data Flows

Attack Trees

Attack trees visualize layered attack strategies by breaking down each attacker’s goal into nodes and sub-goals.

Example Use Case

Analyzing threats affecting:

• Image transfer between device and PACS systems
• Device-to-cloud telemetry
• Remote diagnostics and servicing channels

Attack trees clarify how multiple vulnerabilities combine into larger attack paths.

Risk Assessment and Prioritization

CVSS Scoring

CVSS provides a quantitative scoring mechanism to evaluate:

• Attack vector
• Attack complexity
• Required privileges
• User interaction
• Impact on confidentiality, integrity, availability

CVSS supports decision-making for:

• Acceptable vs. unacceptable cybersecurity risk
• Required mitigation measures
• Patch prioritization and vulnerability disclosure

CVSS Factors for Medical Devices

Beyond Clinical Use: Non-Clinical Cybersecurity Scenarios

Cyber risks extend beyond patient-facing environments. A complete threat model considers:

Common Non-Clinical Threat Domains

• Manufacturing and provisioning vulnerabilities
• Cryptographic key generation and storage
• Software updates and patch distribution
• Technician access controls
• Remote service interfaces
• Supply chain exposure (components, firmware, code)

Ignoring non-clinical scenarios can leave critical attack vectors unaddressed.

Key Takeaways for 2025

Threat modeling is now an industry-standard method that strengthens secure-by-design development. Manufacturers benefit by:

• Reducing post market cybersecurity exposure
• Enhancing regulatory defensibility
• Increasing patient trust and reliability
• Creating robust documentation aligned with SPDF and global expectations

Threat modeling is most effective when implemented early—but it remains valuable at any stage of the device lifecycle.