cyber threat modelling

Eamon Carroll

min read

What is cyber threat modelling?

Cyber threat modelling is a structured way to anticipate how a system can be attacked and to decide which defenses matter most. It examines assets, entry points, trust boundaries, and likely attacker behaviors to produce actionable mitigations. In practice, cyber threat modelling blends threat analysis with risk assessment: you identify plausible threats, estimate impact/likelihood, and prioritize fixes. Teams often use a data flow diagram (DFD) or architecture sketch to make threats easier to see.

Why is cyber threat modelling important for security programs?

Cyber threat modelling helps you spend security effort where it reduces real risk, not just where a checklist points. It improves security architecture review by surfacing weak trust boundaries, unsafe data handling, and exposed services early—when changes are cheaper. It also supports attack surface analysis by documenting what’s reachable and what assumptions are being made. Over time, repeating cyber threat modelling builds a shared security mindset across engineering and IT.

When should you perform cyber threat modelling?

Run cyber threat modelling whenever risk changes, especially:

New system design or major architectural changes
Adding authentication/authorization, APIs, or third-party integrations
Moving to cloud, containers, or a new network zone
Significant feature releases or changes to sensitive data flows
After incidents or near-misses to prevent recurrence Lightweight threat modeling during design, plus deeper reviews pre-release, is usually effective.

What are the main steps in cyber threat modelling?

Most cyber threat modelling efforts follow a repeatable flow:

Define scope and assets (what you must protect).
Model the system (DFDs, components, trust boundaries).
Identify threats (abuse cases, misuse cases, known attacker tactics).
Assess risk (impact, likelihood, existing controls).
Choose mitigations (design changes, hardening, monitoring).
Validate (tests, review, and security requirements).
Document and track (owners, deadlines, residual risk).

Which frameworks and methods are commonly used?

Common methods help standardize cyber threat modelling across teams:

STRIDE: categorizes threats (spoofing, tampering, etc.).
MITRE ATT&CK: maps real adversary techniques for adversary modeling.
PASTA (risk-driven) and LINDDUN (privacy-focused) are also used. You can combine them: use STRIDE to brainstorm threats, then align detections and controls to MITRE ATT&CK to ensure coverage of realistic attack paths.

Who should be involved in the threat modelling process?

Cyber threat modelling works best as a cross-functional activity. Typical participants include:

Software engineers and architects (system knowledge)
Security engineers (controls, patterns, threat analysis)
IT/network/cloud teams (deployment realities)
Product owners (business impact and priorities)
Compliance or privacy stakeholders when regulated data is involved Including the people who will implement mitigations increases follow-through and makes the outputs more than just a document.

What outputs and artifacts should threat modelling produce?

Useful cyber threat modelling outputs are concrete and trackable:

A scoped system model (DFD or architecture diagram)
A list of threats tied to components and trust boundaries
Prioritized risks (often a simple risk rating)
Recommended mitigations and security requirements
Decisions and assumptions (what you accept vs. fix)
Tickets/backlog items with owners and due dates These artifacts support ongoing security architecture review and can be reused for future releases.

What are common mistakes and how do you avoid them?

Common pitfalls in cyber threat modelling include treating it as a one-time workshop, focusing only on unlikely “movie-plot” attackers, or producing findings that aren’t actionable. Avoid these by:

Keeping scope tight (one service or feature at a time)
Updating the model as systems change
Connecting threats to the attack surface analysis and real attacker techniques (MITRE ATT&CK)
Turning mitigations into engineering work items
Revisiting residual risk explicitly so decisions are intentional Done this way, cyber threat modelling stays practical and improves security outcomes release after release.