Threat model

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Threat modeling is a process by which potential threats, such as structural vulnerabilities or the absence of appropriate safeguards, can be identified, enumerated, and mitigations can be prioritized. 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?”.

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Conceptually, most people incorporate some form of threat modeling in their daily life and don't even realize it. Commuters use threat modeling to consider what might go wrong during the morning drive 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 IT-based threat modeling

Shortly after shared computing made its debut in the early 1960s individuals began seeking ways to exploit security vulnerabilities for personal gain. [1] As a result, engineers and computer scientists soon began developing threat modeling concepts for information technology systems.

Early IT-based threat modeling methodologies were based on the concept of architectural patterns [2] 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. [3] ” 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. [4] ” 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 [5] 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,” 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 methodologies for IT purposes

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 four approaches independently, asset-centric, attacker-centric, and software-centric. Based on volume of published online content, the methodologies discussed below are the most well known.

STRIDE methodology

The STRIDE approach to threat modeling was introduced in 1999 at Microsoft, providing a mnemonic for developers to find 'threats to our products'. [9] 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.

P.A.S.T.A.

The Process for Attack Simulation and Threat Analysis (PASTA) is a seven-step, risk-centric methodology. [10] 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.

Trike

The focus of the Trike methodology [11] 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.

Generally accepted IT 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. The identification and enumeration of threats (or of mitigation objectives), can either be carried out in an attack-centric way or in an asset-centric way. The former focuses on the types of possible attacks that shall be mitigated, whereas the latter focuses on the assets that shall be protected.

Visual representations based on data flow diagrams

Data Flow Diagram - Online Banking Application.jpg

The Microsoft methodology, PASTA, and Trike each develop a visual representation of the application-infrastructure utilizing 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 allow DFDs to be utilized 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.

Further fields of application

Threat modeling is being applied not only to IT but also to other areas such as vehicle, [12] [13] building and home automation. [14] 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). [14]

Related Research Articles

Risk management Set of measures for the systematic identification, analysis, assessment, monitoring and control of risks

Risk management is the identification, evaluation, and prioritization of risks followed by coordinated and economical application of resources to minimize, monitor, and control the probability or impact of unfortunate events or to maximize the realization of opportunities.

Security engineering is the process of incorporating security controls into an information system so that the controls become an integral part of the system’s operational capabilities. It is similar to other systems engineering activities in that its primary motivation is to support the delivery of engineering solutions that satisfy pre-defined functional and user requirements, but it has the added dimension of preventing misuse and malicious behavior. Those constraints and restrictions are often asserted as a security policy.

Security management is the identification of an organization's assets, followed by the development, documentation, and implementation of policies and procedures for protecting assets.

Broadly speaking, a risk assessment is the combined effort of:

  1. identifying and analyzing potential (future) events that may negatively impact individuals, assets, and/or the environment ; and
  2. making judgments "on the tolerability of the risk on the basis of a risk analysis" while considering influencing factors.

A vulnerability assessment is the process of identifying, quantifying, and prioritizing the vulnerabilities in a system. Examples of systems for which vulnerability assessments are performed include, but are not limited to, information technology systems, energy supply systems, water supply systems, transportation systems, and communication systems. Such assessments may be conducted on behalf of a range of different organizations, from small businesses up to large regional infrastructures. Vulnerability from the perspective of disaster management means assessing the threats from potential hazards to the population and to infrastructure. It may be conducted in the political, social, economic or environmental fields.

Vulnerability (computing) Exploitable weakness in a computer system

In computer security, a vulnerability is a weakness which 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.

Critical infrastructure protection

Critical infrastructure protection (CIP) is a concept that relates to the preparedness and response to serious incidents that involve the critical infrastructure of a region or nation.

Attack trees are conceptual diagrams showing how an asset, or target, might be attacked. Attack trees have been used in a variety of applications. In the field of information technology, they have been used to describe threats on computer systems and possible attacks to realize those threats. However, their use is not restricted to the analysis of conventional information systems. They are widely used in the fields of defense and aerospace for the analysis of threats against tamper resistant electronics systems. Attack trees are increasingly being applied to computer control systems. Attack trees have also been used to understand threats to physical systems.

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 not only digital protections but also physical techniques. These protections 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 security management (ISM) defines and manages controls that an organization needs to implement to ensure that it is sensibly protecting the confidentiality, availability, and integrity of assets from threats and vulnerabilities. The core of ISM includes information risk management, a process which involves the assessment of the risks an organization must deal with in the management and protection of assets, as well as the dissemination of the risks to all appropriate stakeholders. This requires proper asset identification and valuation steps, including evaluating the value of confidentiality, integrity, availability, and replacement of assets. As part of information security management, an organization may implement an information security management system and other best practices found in the ISO/IEC 27001, ISO/IEC 27002, and ISO/IEC 27035 standards on information security.

MEHARI is a free, open-source information risk analysis assessment and risk management method, for the use of information security professionals.

Information technology risk, IT risk, IT-related risk, or cyber risk is any risk related 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.

Misuse case

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.

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.

IT risk management

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

Cyber threat hunting is an active 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.

Cyber risk quantification involves the application of risk quantification techniques to an organization's cybersecurity risk. Cyber risk quantification is the process of evaluating the cyber risks that have been identified and then validating, measuring and analyzing the available cyber data using mathematical modeling techniques to accurately represent the organization's cybersecurity environment in a manner that can be used to make informed cybersecurity infrastructure investment and risk transfer decisions. Cyber risk quantification is a supporting activity to cybersecurity risk management; cybersecurity risk management is a component of enterprise risk management and is especially important in organizations and enterprises that are highly dependent upon their information technology (IT) networks and systems for their business operations.

ISO 22300:2021, Security and resilience – Vocabulary, is an international standard developed by ISO/TC 292 Security and resilience. This document defines terms used in security and resilience standards and includes 360 terms and definitions. This edition was published in the beginning of 2021 and replaces the second edition from 2018.

References

  1. ↑ McMillan, Robert (2012). "The World's First Computer Password? It Was Useless Too". Wired Business.
  2. ↑ Shostack, Adam (2014). "Threat Modeling: Designing for Security". John Wiley & Sons Inc: Indianapolis.
  3. ↑ Amoroso, Edward G (1994). "Fundamentals of Computer Security Technology". AT&T Bell Labs. Prentice-Hall: Upper Saddle River.
  4. ↑ Schneier, Bruce; et al. (1998). "Toward A Secure System Engineering Methodology" (PDF). National Security Agency: Washington.
  5. ↑ "The STRIDE Threat Mode". Microsoft. 2016.
  6. ↑ Alberts, Christopher (2003). "Introduction to the OCTAVE® Approach" (PDF). Software Engineering Institute, Carnegie Mellon: Pittsburg.
  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).
  9. ↑ Kohnfelder, Loren; Garg, Praerit. "Threats to Our Products". Microsoft. Retrieved 20 September 2016.
  10. ↑ Ucedavélez, Tony and Marco M. Morana (2015). "Risk Centric Threat Modeling: Process for Attack Simulation and Threat Analysis". John Wiley & Sons: Hobekin.
  11. ↑ Eddington, Michael, Brenda Larcom, and Eleanor Saitta (2005). "Trike v1 Methodology Document". Octotrike.org.
  12. ↑ http://publications.lib.chalmers.se/records/fulltext/252083/local_252083.pdf
  13. ↑ Hamad, Mohammad; Prevelakis, Vassilis; Nolte, Marcus (November 2016). "Towards Comprehensive Threat Modeling for Vehicles" (PDF). Publications Institute of Computer and Network Engineering. doi:10.24355/dbbs.084-201806251532-0 . Retrieved 11 March 2019.Cite journal requires |journal= (help)
  14. 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): 860–866. doi:10.1109/INDIN.2016.7819280. ISBN   978-1-5090-2870-2. S2CID   12725362.
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