Threat model

Last updated

Threat modeling is a process by which potential threats, such as structural vulnerabilities or the absence of appropriate safeguards, can be identified and enumerated, and countermeasures prioritized. [1] The purpose of threat modeling is to provide defenders with a systematic analysis of what controls or defenses need to be included, given the nature of the system, the probable attacker's profile, the most likely attack vectors, and the assets most desired by an attacker. Threat modeling answers questions like "Where am I most vulnerable to attack?", "What are the most relevant threats?", and "What do I need to do to safeguard against these threats?".


Conceptually, most people incorporate some form of threat modeling in their daily life and don't even realize it.[ citation needed ] Commuters use threat modeling to consider what might go wrong during the morning journey to work and to take preemptive action to avoid possible accidents. Children engage in threat modeling when determining the best path toward an intended goal while avoiding the playground bully. In a more formal sense, threat modeling has been used to prioritize military defensive preparations since antiquity.

Evolution of technology-centric threat modeling

Shortly after shared computing made its debut in the early 1960s, individuals began seeking ways to exploit security vulnerabilities for personal gain. [2] As a result, engineers and computer scientists soon began developing threat modeling concepts for information technology systems.

Early technology-centered threat modeling methodologies were based on the concept of architectural patterns [3] first presented by Christopher Alexander in 1977. In 1988 Robert Barnard developed and successfully applied the first profile for an IT-system attacker.

In 1994, Edward Amoroso put forth the concept of a "threat tree" in his book, "Fundamentals of Computer Security Technology. [4] " The concept of a threat tree was based on decision tree diagrams. Threat trees graphically represent how a potential threat to an IT system can be exploited.

Independently, similar work was conducted by the NSA and DARPA on a structured graphical representation of how specific attacks against IT-systems could be executed. The resulting representation was called "attack trees." In 1998 Bruce Schneier published his analysis of cyber risks utilizing attack trees in his paper entitled "Toward a Secure System Engineering Methodology". [5] The paper proved to be a seminal contribution in the evolution of threat modeling for IT-systems. In Schneier's analysis, the attacker's goal is represented as a "root node," with the potential means of reaching the goal represented as "leaf nodes." Utilizing the attack tree in this way allowed cybersecurity professionals to systematically consider multiple attack vectors against any defined target.

In 1999, Microsoft cybersecurity professionals Loren Kohnfelder and Praerit Garg developed a model for considering attacks relevant to the Microsoft Windows development environment. (STRIDE [1] is an acrostic for: Spoofing identity, Tampering with data, Repudiation, Information disclosure, Denial of service, Elevation of privilege) The resultant mnemonic helps security professionals systematically determine how a potential attacker could utilize any threat included in STRIDE.

In 2003, OCTAVE [6] (Operationally Critical Threat, Asset, and Vulnerability Evaluation) method, an operations-centric threat modeling methodology, was introduced with a focus on organizational risk management.

In 2004, Frank Swiderski and Window Snyder wrote "Threat Modeling," published by Microsoft press. In it they developed the concept of using threat models to create secure applications.

In 2014, Ryan Stillions expressed the idea that cyber threats should be expressed with different semantic levels, and proposed the DML (Detection Maturity Level) model. [7] An attack is an instantiation of a threat scenario which is caused by a specific attacker with a specific goal in mind and a strategy for reaching that goal. The goal and strategy represent the highest semantic levels of the DML model. This is followed by the TTP (Tactics, Techniques and Procedures) which represent intermediate semantic levels. The lowest semantic levels of the DML model are the tools used by the attacker, host and observed network artifacts such as packets and payloads, and finally atomic indicators such as IP addresses at the lowest semantic level. Current SIEM (Security Information and Event Management) tools typically only provide indicators at the lowest semantic levels. There is therefore a need to develop SIEM tools that can provide threat indicators at higher semantic levels. [8]

Threat Modeling Manifesto

The threat modeling manifesto is a document published in 2022 by threat modeling authorities in order to clearly state the core values and principles that every threat modeler should know and follow. [9]

In 2024 the same group of authors followed up the Manifesto with a Threat Modeling Capabilities document, which "...provides a catalog of capabilities to help you cultivate value from your Threat Modeling practice". [10]

Threat modeling frameworks

Conceptually, a threat modeling practice flows from a methodology. Numerous threat modeling methodologies are available for implementation. Typically, threat modeling has been implemented using one of five approaches independently: asset-centric, attacker-centric, software-centric, value and stakeholder-centric, and hybrid. Based on the volume of published online content, the methodologies discussed below are the most well known.


The STRIDE was created in 1999 at Microsoft as a mnemonic for developers to find 'threats to our products'. [11] STRIDE can be used as a simple prompt or checklist, or in more structured approaches such as STRIDE per element. STRIDE, Patterns and Practices, and Asset/entry point were amongst the threat modeling approaches developed and published by Microsoft. References to "the" Microsoft methodology commonly mean STRIDE and Data Flow Diagrams.


The Process for Attack Simulation and Threat Analysis (PASTA) is a seven-step, risk-centric methodology. [12] It provides a seven-step process for aligning business objectives and technical requirements, taking into account compliance issues and business analysis. The intent of the method is to provide a dynamic threat identification, enumeration, and scoring process. Once the threat model is completed, security subject matter experts develop a detailed analysis of the identified threats. Finally, appropriate security controls can be enumerated. This methodology is intended to provide an attacker-centric view of the application and infrastructure from which defenders can develop an asset-centric mitigation strategy.


The focus of the Trike methodology [13] is using threat models as a risk-management tool. Within this framework, threat models are used to satisfy the security auditing process. Threat models are based on a "requirements model." The requirements model establishes the stakeholder-defined "acceptable" level of risk assigned to each asset class. Analysis of the requirements model yields a threat model from which threats are enumerated and assigned risk values. The completed threat model is used to construct a risk model based on asset, roles, actions, and calculated risk exposure.


The Visual, Agile and Simple Threat (VAST) methodology, [14] is based on ThreatModeler, a commercial automated threat-modeling platform. VAST requires creating two types of models: application threat models and operational threat models. Application threat models use process-flow diagrams, representing the architectural point of view. Operational threat models are created from an attacker point of view based on DFDs. This approach allows for the integration of VAST into the organization's development and DevOps lifecycles. [15]

'The Hybrid' Threat Modeling Method

Researchers created this method to combine the positive elements of different methodologies. [16] [17] [18] This methodology combines different methodologies, including SQUARE [19] and the Security Cards [20] and Personae Non Gratae. [21]

Generally accepted technology threat modeling processes

All IT-related threat modeling processes start with creating a visual representation of the application and / or infrastructure being analyzed. The application / infrastructure is decomposed into various elements to aid in the analysis. Once completed, the visual representation is used to identify and enumerate potential threats. Further analysis of the model regarding risks associated with identified threats, prioritization of threats, and enumeration of the appropriate mitigating controls depends on the methodological basis for the threat model process being utilized. Threat modeling approaches can focus on the system in use, attackers, or assets.

Visual representations based on data flow diagrams

Data Flow Diagram - Online Banking Application.jpg

Most threat modeling approaches use data flow diagrams (DFD). DFDs were developed in the 1970s as tool for system engineers to communicate, on a high level, how an application caused data to flow, be stored, and manipulated by the infrastructure upon which the application runs. Traditionally, DFDs utilize only four unique symbols: data flows, data stores, processes, and interactors. In the early 2000s, an additional symbol, trust boundaries, were added to improve the usefulness of DFDs for threat modeling.

Once the application-infrastructure system is decomposed into its five elements, security experts consider each identified threat entry point against all known threat categories. Once the potential threats are identified, mitigating security controls can be enumerated or additional analysis can be performed.

Threat modeling tools

Further fields of application

Threat modeling is being applied not only to IT but also to other areas such as vehicle, [29] [30] building and home automation. [31] In this context, threats to security and privacy like information about the inhabitant's movement profiles, working times, and health situations are modeled as well as physical or network-based attacks. The latter could make use of more and more available smart building features, i.e., sensors (e.g., to spy on the inhabitant) and actuators (e.g., to unlock doors). [31]

Related Research Articles

<span class="mw-page-title-main">Data model</span> Model that organizes elements of data and how they relate to one another and to real-world entities.

A data model is an abstract model that organizes elements of data and standardizes how they relate to one another and to the properties of real-world entities. For instance, a data model may specify that the data element representing a car be composed of a number of other elements which, in turn, represent the color and size of the car and define its owner.

Software development is the process used to conceive, specify, design, program, document, test, and bug fix in order to create and maintain applications, frameworks, or other software components. Software development involves writing and maintaining the source code, but in a broader sense, it includes all processes from the conception of the desired software through the final manifestation, typically in a planned and structured process often overlapping with software engineering. Software development also includes research, new development, prototyping, modification, reuse, re-engineering, maintenance, or any other activities that result in software products.

<span class="mw-page-title-main">Computer-aided software engineering</span> Software Quality Engineering Practices

Computer-aided software engineering (CASE) was a domain of software tools used to design and implement applications. CASE tools were similar to and were partly inspired by Computer-Aided Design (CAD) tools used for designing hardware products. CASE tools were intended to help develop high-quality, defect-free, and maintainable software. CASE software was often associated with methods for the development of information systems together with automated tools that could be used in the software development process.

<span class="mw-page-title-main">Data modeling</span> Creating a model of the data in a system

Data modeling in software engineering is the process of creating a data model for an information system by applying certain formal techniques. It may be applied as part of broader Model-driven engineering (MDD) concept.

Vulnerabilities are flaws in a computer system that weaken the overall security of the device/system. Vulnerabilities can be weaknesses in either the hardware itself, or the software that runs on the hardware. Vulnerabilities can be exploited by a threat actor, such as an attacker, to cross privilege boundaries within a computer system. To exploit a vulnerability, an attacker must have at least one applicable tool or technique that can connect to a system weakness. In this frame, vulnerabilities are also known as the attack surface. Constructs in programming languages that are difficult to use properly can also manifest large numbers of vulnerabilities.

A penetration test, colloquially known as a pentest or ethical hacking, is an authorized simulated cyberattack on a computer system, performed to evaluate the security of the system; this is not to be confused with a vulnerability assessment. The test is performed to identify weaknesses, including the potential for unauthorized parties to gain access to the system's features and data, as well as strengths, enabling a full risk assessment to be completed.

The Open Worldwide Application Security Project (OWASP) is an online community that produces freely available articles, methodologies, documentation, tools, and technologies in the fields of IoT, system software and web application security. The OWASP provides free and open resources. It is led by a non-profit called The OWASP Foundation. The OWASP Top 10 - 2021 is the published result of recent research based on comprehensive data compiled from over 40 partner organizations.

Application security includes all tasks that introduce a secure software development life cycle to development teams. Its final goal is to improve security practices and, through that, to find, fix and preferably prevent security issues within applications. It encompasses the whole application life cycle from requirements analysis, design, implementation, verification as well as maintenance.

Software assurance (SwA) is a critical process in software development that ensures the reliability, safety, and security of software products. It involves a variety of activities, including requirements analysis, design reviews, code inspections, testing, and formal verification. One crucial component of software assurance is secure coding practices, which follow industry-accepted standards and best practices, such as those outlined by the Software Engineering Institute (SEI) in their CERT Secure Coding Standards (SCS).

Security testing is a process intended to detect flaws in the security mechanisms of an information system and as such help enable it to protect data and maintain functionality as intended. Due to the logical limitations of security testing, passing the security testing process is not an indication that no flaws exist or that the system adequately satisfies the security requirements.

Information assurance (IA) is the practice of assuring information and managing risks related to the use, processing, storage, and transmission of information. Information assurance includes protection of the integrity, availability, authenticity, non-repudiation and confidentiality of user data. IA encompasses both digital protections and physical techniques. These methods apply to data in transit, both physical and electronic forms, as well as data at rest. IA is best thought of as a superset of information security, and as the business outcome of information risk management.

STRIDE is a model for identifying computer security threats developed by Praerit Garg and Loren Kohnfelder at Microsoft. It provides a mnemonic for security threats in six categories.

Information technology risk, IT risk, IT-related risk, or cyber risk is any risk relating to information technology. While information has long been appreciated as a valuable and important asset, the rise of the knowledge economy and the Digital Revolution has led to organizations becoming increasingly dependent on information, information processing and especially IT. Various events or incidents that compromise IT in some way can therefore cause adverse impacts on the organization's business processes or mission, ranging from inconsequential to catastrophic in scale.

Maritime Security Risk Analysis Model (MSRAM) is a process and model that supports the U.S. Coast Guard's mission to understand and mitigate the risk of terrorist attacks on targets in U.S. ports and waterways. MSRAM began as a Captain of the Port-level risk analysis tool developed shortly after 9/11/2001. In 2005, the USCG began development and implementation of MSRAM in order to take advantage of lessons learned with the initial effort and to apply a risk approach that can be applied at both the field and headquarter levels. To develop this program, USCG HQ invited representatives from headquarters, and all levels of command to define requirements and identify milestones. This led to an action plan that fielded the first MSRAM system in 2006. Since the first MSRAM rollout, USCG is in the third iteration of MSRAM as of 2008.

<span class="mw-page-title-main">Misuse case</span>

Misuse case is a business process modeling tool used in the software development industry. The term Misuse Case or mis-use case is derived from and is the inverse of use case. The term was first used in the 1990s by Guttorm Sindre of the Norwegian University of Science and Technology, and Andreas L. Opdahl of the University of Bergen, Norway. It describes the process of executing a malicious act against a system, while use case can be used to describe any action taken by the system.

DREAD is part of a system for risk-assessing computer security threats that was formerly used at Microsoft. It provides a mnemonic for risk rating security threats using five categories.

In computer security, a threat is a potential negative action or event facilitated by a vulnerability that results in an unwanted impact to a computer system or application.

<span class="mw-page-title-main">IT risk management</span>

IT risk management is the application of risk management methods to information technology in order to manage IT risk, i.e.:

A web application firewall (WAF) is a specific form of application firewall that filters, monitors, and blocks HTTP traffic to and from a web service. By inspecting HTTP traffic, it can prevent attacks exploiting a web application's known vulnerabilities, such as SQL injection, cross-site scripting (XSS), file inclusion, and improper system configuration. They also introduce a performance degradation and are easily bypassed by attackers so their deployment is not recommended.

Cyber threat hunting is a proactive cyber defence activity. It is "the process of proactively and iteratively searching through networks to detect and isolate advanced threats that evade existing security solutions." This is in contrast to traditional threat management measures, such as firewalls, intrusion detection systems (IDS), malware sandbox and SIEM systems, which typically involve an investigation of evidence-based data after there has been a warning of a potential threat.


  1. 1 2 "The STRIDE Threat Model". Microsoft. 2016.
  2. McMillan, Robert (2012). "The World's First Computer Password? It Was Useless Too". Wired Business.
  3. Shostack, Adam (2014). "Threat Modeling: Designing for Security". John Wiley & Sons Inc: Indianapolis.
  4. Amoroso, Edward G (1994). Fundamentals of Computer Security Technology. AT&T Bell Labs. Prentice-Hall: Upper Saddle River. ISBN   9780131089297.
  5. Schneier, Bruce; et al. (1998). "Toward A Secure System Engineering Methodology" (PDF). National Security Agency: Washington.
  6. Alberts, Christopher (2003). "Introduction to the OCTAVE® Approach" (PDF). Software Engineering Institute, Carnegie Mellon: Pittsburgh.
  7. Stillions, Ryan (2014). "The DML Model". Ryan Stillions security blog. Ryan Stillions.
  8. Bromander, Siri (2016). "Semantic Cyberthreat Modelling" (PDF). Semantic Technology for Intelligence, Defence and Security (STIDS 2016).
  11. Kohnfelder, Loren; Garg, Praerit. "Threats to Our Products". Microsoft. Retrieved 4 Feb 2024.
  12. Ucedavélez, Tony and Marco M. Morana (2015). "Risk Centric Threat Modeling: Process for Attack Simulation and Threat Analysis". John Wiley & Sons: Hobekin.
  13. Eddington, Michael, Brenda Larcom, and Eleanor Saitta (2005). "Trike v1 Methodology Document".{{cite web}}: CS1 maint: multiple names: authors list (link)
  14. Fruhlinger, Josh (2020-04-15). "Threat modeling explained: A process for anticipating cyber attacks". CSO Online. Retrieved 2022-02-03.
  15. "Threat Modeling: 12 Available Methods". SEI Blog. Retrieved 2022-02-03.
  16. "The Hybrid Threat Modeling Method".
  17. "A Hybrid Threat Modeling Method".
  18. Tarandach, Izar; Coles, Matthew J. (24 November 2020). Threat Modeling: A Practical Guide for Development Teams. ISBN   978-1492056553.
  19. "Security Quality Requirements Engineering Technical Report".
  21. "CSDL | IEEE Computer Society".
  22. "What's New with Microsoft Threat Modeling Tool 2016". Microsoft Secure Blog. Microsoft. 2015.
  23. "Irius Risk Risk Management Tool". Continuum Security. 2016.
  24. "foreseeti - securiCAD". Retrieved November 27, 2018.
  25. "Cyber Threat Modelling and Risk Management - securiCAD by foreseeti". foreseeti.
  26. "SD Elements by Security Compass". Retrieved 2017-03-24.
  27. "OWASP Threat Dragon".
  28. "OWASP pytm".
  29. [ bare URL PDF ]
  30. Hamad, Mohammad; Prevelakis, Vassilis; Nolte, Marcus (November 2016). "Towards Comprehensive Threat Modeling for Vehicles" (PDF). "Institute of Control Engineering". Publications Institute of Computer and Network Engineering. doi:10.24355/dbbs.084-201806251532-0 . Retrieved 11 March 2019.
  31. 1 2 Meyer, D.; Haase, J.; Eckert, M.; Klauer, B. (2016-07-01). "A threat-model for building and home automation". 2016 IEEE 14th International Conference on Industrial Informatics (INDIN). pp. 860–866. doi:10.1109/INDIN.2016.7819280. ISBN   978-1-5090-2870-2. S2CID   12725362.