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, 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?”.

Contents

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 artefacts such as packets and payloads, and finally atomic indicators such as IP addresses at the lowest semantic level. Current SIEM 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. Each one of those approaches has its pros and cons. [12]

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.

Threat modeling tools

There are currently a number of software tools available to help threat modeling:

Further fields of application

Threat modeling is being applied not only to IT but also to other areas such as vehicle, [22] [23] building and home automation. [24] 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). [24]

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.

Cross-site scripting (XSS) is a type of web application security vulnerability typically found in web applications. XSS attacks enable attackers to inject client-side scripts into web pages viewed by other users. A cross-site scripting vulnerability may be used by attackers to bypass access controls such as the same-origin policy. Cross-site scripting carried out on websites accounted for roughly 84% of all security vulnerabilities documented by Symantec up until 2007. In 2017, XSS attacks were still considered a major threat vector. XSS effects vary in range from petty nuisance to significant security risk, depending on the sensitivity of the data handled by the vulnerable site and the nature of any security mitigation implemented by the site's owner network.

In computer security, a vulnerability is a weakness which can be exploited by a threat actor, such as an attacker, to perform unauthorized actions 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.

A penetration test, colloquially known as a pen test, pentest or ethical hacking, is an authorized simulated cyberattack on a computer system, performed to evaluate the security of the system. Not to be confused with a vulnerability assessment. The test is performed to identify both 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 Web Application Security Project (OWASP) is an online community that produces freely-available articles, methodologies, documentation, tools, and technologies in the field of web application security.

Application security encompasses measures taken to improve the security of an application often by finding, fixing and preventing security vulnerabilities. Different techniques are used to surface such security vulnerabilities at different stages of an applications lifecycle such as design, development, deployment, upgrade, maintenance.

Security testing is a process intended to reveal flaws in the security mechanisms of an information system that protect data and maintain functionality as intended. Due to the logical limitations of security testing, passing security testing 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 or data and the systems and processes used for those purposes. Information assurance includes protection of the integrity, availability, authenticity, non-repudiation and confidentiality of user data. It uses physical, technical, and administrative controls to accomplish these tasks. While focused predominantly on information in digital form, the full range of IA encompasses not only digital, but also analog or physical form. These protections apply to data in transit, both physical and electronic forms, as well as data at rest in various types of physical and electronic storage facilities. IA is best thought of as a superset of information security, and as the business outcome of information risk management.

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

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.

DREAD is part of a system for risk-assessing computer security threats previously used at Microsoft and although currently used by OpenStack and other corporations it was abandoned by its creators. It provides a mnemonic for risk rating security threats using five categories.

Web application security is a branch of information security that deals specifically with security of websites, web applications and web services. At a high level, web application security draws on the principles of application security but applies them specifically to internet and web systems.

In computer security, a threat is a possible danger that might exploit a vulnerability to breach security and therefore cause possible harm.

IT risk management application of risk management methods to information technology in order to manage IT risk

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 filters, monitors, and blocks HTTP traffic to and from a web application. A WAF is differentiated from a regular firewall in that a WAF is able to filter the content of specific web applications while regular firewalls serve as a safety gate between servers. By inspecting HTTP traffic, it can prevent attacks stemming from web application security flaws, such as SQL injection, cross-site scripting (XSS), file inclusion, and security misconfigurations.

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.

Risk Control Strategies are the defensive measures utilized by IT and InfoSec communities to limit vulnerabilities and manage risks to an acceptable level. There are a number of strategies that can be employed as one measure of defense or in a combination of multiple strategies together. A risk assessment is an important tool that should be incorporated in the process of identifying and determining the threats and vulnerabilities that could potentially impact resources and assets to help manage risk. Risk management is also a component of a risk control strategy because Nelson et al. (2015) state that "risk management involves determining how much risk is acceptable for any process or operation, such as replacing equipment".

ISO 22300:2018, 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 277 terms and definitions. This edition was published in the beginning of 2018 and replaces the first edition from 2012.

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. "Useful threat modelling". Hagai Bar-El on Security. Retrieved 2020-03-08.
  13. "Irius Risk Threat Modeling Tool". IriusRisk. 2016.
  14. "What's New with Microsoft Threat Modeling Tool 2016". Microsoft Secure Blog. Microsoft. 2015.
  15. Tarandach. "A Pythonic framework for threat modeling" . Retrieved 12 March 2019.
  16. "Cyber Threat Modeling and Risk Management - securiCAD by foreseeti". foreseeti.
  17. "SD Elements by Security Compass". www.securitycompass.com. Retrieved 2017-03-24.
  18. "Tutamen Features". Tutamantic. Retrieved 12 March 2019.
  19. "OWASP Threat Dragon Project". www.owasp.org. Retrieved 2019-03-11.
  20. "Mozilla SeaSponge Threat Modeling tool". www.mozilla.org. Retrieved 2019-03-11.
  21. Schaad, Andreas; Reski, Tobias (2019). ""Open Weakness and Vulnerability Modeler" (OVVL): An Updated Approach to Threat Modeling". Proceedings of the 16th International Joint Conference on E-Business and Telecommunications. Prague, Czech Republic: SCITEPRESS - Science and Technology Publications: 417–424. doi: 10.5220/0007919004170424 . ISBN   978-989-758-378-0.
  22. http://publications.lib.chalmers.se/records/fulltext/252083/local_252083.pdf
  23. 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)
  24. 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.