Framing and Understanding Worst-Case scenarios
Understanding the worst-case cyber scenarios within an organization is a fundamental step in communicating and managing cyber risk. Rather than focusing on vulnerabilities or threats in technical language, new top-down cyber risk methodologies prioritize financial impact, making risks visible in euros or dollars. Having identified scenarios and knowing their financial impact, strategic planning can be enabled, such as prioritizing risk mitigation efforts, weighing risk transfer options or due diligence purposes.
This blog post explores the top-down cyber risk methodology to define worst-case scenarios within three categories of consequences:
- Business Interruption (BI)
- Data Privacy Breach (DB)
- Financial Theft & Fraud (FTF).
We build on the article "Tailored Cyber Modeling: Why Defining Your Worst-Case Cyber Scenario Matters", which demonstrated the importance of defining worst-case scenarios individually for each organization. Now, we advance to the next step: defining and prioritizing those potential scenarios in practical, organization-specific terms. More specifically, steps 2 and 3 of the process for identifying worst-case scenarios is the focus, as demonstrated in the following graph.
Recap: The Four Steps to Identify Your Worst-Case Cyber Scenario
The ulitmate aim is to identify a worst case scenario for each consequence scenario category. These scenarios should both be realistic and comprehensible while still being the worst cyber incidents, if almost all Information Security measures fail. This ensures a company is prepared for the most severe cyber incident, that can potentially happen and helps avoid a too narrow and limited view on the potential risk. The motto: start big and stop where reality hits!
- Consider the Doomsday Scenario
Envision the absolute worst-case cyber event - such as prolonged operational shutdown or total data compromis - not to predict it, but to challenge assumptions about what’s truly impossible. - Define Potential Scenarios with Clear Boundaries
Break the doomsday scenario into specific, technically isolated events (e.g., by system or division) using only technical architectural separations - not existing controls - as justification. In this article, we will be focusing on this step. - Rank Scenarios by Financial Impact
Assess and prioritize each scenario by estimating its potential financial damage, focusing on those with the highest loss potential in the different risk categories. In this article, we will touch upon this step. - Quantify the Worst Case Using CRQ Tools
Use a CRQ tool to model top-ranked scenarios, translating complex risk into financial terms that business leaders can act on.
Why Use a Top-Down Cyber Risk Methodology?
A top-down cyber risk quantification methodology starts by understanding the business, not the threat landscape. It defines cyber risks based on their potential financial impact. Every company is unique - different business models, digital architectures, and operational dependencies. Since every company has a its own operational structure, the financial scope of cyber risk needs individual identification for each company.
Using a top-down assessment approach to identify and tailor scenarios to an organization’s set-up, leaders can understand and argue cyber risk clearly to stakeholders. This shift in perspective enables you to evaluate the cost of cyber in a comprehensive and plausible way tailored to your company, paving the way for clear communication with board members and the C-suite.
A Three-Step Framework for Defining Cyber Risk Scenarios
While every company is different, the methodology to define cyber risk scenarios remains the same:
- Assess how your business generates value.
- Map out critical processes and digital dependencies.
- Define and prioritze risk scenarios based on how a cyber incident would impact financial outcomes.
Business Interruption: Where Process Meets Profit
Business Interruption (BI) occurs when a cyber incident halts production or service delivery. Identifying the worst-case BI scenario requires understanding what part of your business, if disrupted, would lead to the most significant financial damage.
Framing a Business Interruption cyber scenario
Multiple factors must be considered when identifying and scoping a BI worst-case scenario - depending on the product or service, some factors will be more useful for identifying scenarios within a company, while others will better support asessing and ranking scenarios according to financial severity. For instance, if one IT system connects all production sites, a cyber incident could bring all of them down at once - a Doomsday scenario. If only a few production sites are down, such as through a regional network seggregated from the main IT system, a cyber incident can in the worst case bring all these down.
Assess how your business generates value
Several considerations help locate the most critical financial business processes:
- Which business units, products, or services are the most profitable?
- What are the key operational processes, and which of these are both the most cost-intensive and vital to maintaining overall business continuity?
- How are IT and OT environments segmented, particularly in relation to critical business functions?
Mapping of critical processes and digital interdependencies
Primary factors - these largely define the scope of the scenario.
- IT Segmentation: Which units are interconnected? Interconnected units form a single scenario - e.g., if three plants rely on the same IT infrastructure, a disruption affects all three collectively.
- Bottlenecks: Which processes, if disrupted, would cause a ripple effect? Processes that are not directly connected via IT systems but are operationally dependent on each other should be considered within the same scope. E.g., if one site produces components essential to others, its failure creates a ripple effect across multiple sites.
Define risk scenarios: how a cyber incident would impact financial outcomes
Secondary factors - will help better estimate the financial severity of scenarios.
- Make-up Capabilities: Can lost production or service be recovered later? The ability to catch up on missed output determines whether sales are deferred or permanently lost. E.g., a food producer may lose sales to substitute products, while a premium car maker may recover due to loyal customers.
- Buffers & Reserves: Are there inventories or time buffers to reduce downtime impact? Having stockpiles or time reserves helps bridge temporary interruptions and maintain service levels. E.g., a retailer with warehouse reserves may continue sales during a production outage.
- Complexity: Which production processes involve many steps or systems? More complex operations are harder to restart and usually take longer to recover after disruption. E.g., a high-tech electronics plant with intricate assembly lines faces a longer and more costly restart time than a simple packaging facility.
- Seasonality: When does the business make peak profits? Interruptions during peak seasons have greater financial impact than during off-peak periods. E.g., a ski resort hit during winter peak season suffers greater losses than a year-round beach resort.
After identifying different BI scenarios, use information from the secondary factors to rank them by severity and prepare for quantification. Information from stakeholders within the organisation will help answer the specific questions.
Data Privacy Breach: Turning Sensitive Data into Financial Exposure
Data Privacy Breach (DB) scenarios refer to cyber incidents that compromise the availability, confidentiality, or integrity of personal data during storage, transmission, processing, or archiving, resulting in a violation of an individual’s right to personal privacy. Identifying the worst-case DB breach scenario involves understanding which set of personal data, if compromised, would result in the most severe impact on individuals’ privacy and cause the most significant damage to the organization.
Framing a Data Privacy Breach cyber scenario
Similarly to BI, there are several factors that support in assessing and ranking scenarios according to financial severity. But differently to BI, there is only one central factor that isolates potential DB scenarios from each other.
For instance, if one system stores or processes personal data across all locations, a data privacy breach could expose all records simultaneously, resulting in the doomsday scenario. However, if several data repositories are linked, a breach within this interconnected segment of the system could compromise all therein stored personal data.
Assess how your business generates value
The following considerations help provide a clear overview of the personal data held within an organization. Thereby, personal data is often an integral part of the value generation for businesses.
- What types of data your organization stores (PII, PCI, PHI)?
- Whose data it is and which regulations apply to it (e.g., EU citizens, U.S. customers)?
- Where and how that data is stored and segmented?
Mapping of critical processes and digital interdependencies
Primary factors - this defines the scope of the scenario.
- Data Segmentation: How isolated are different pools of personal data? Without segmentation, one breach can compromise multiple datasets. Segmentation helps contain the impact of a privacy breach by limiting which data is affected. E.g., a company with several products in different regions, each tracking personal data, will have several databases storing sensitive information.
Define risk scenarios: how a cyber incident would impact financial outcomes
Secondary factors - will help better estimate the financial severity of scenarios.
- Data Volume: How many personal records are stored, and how widely are they distributed?
A large volume of data increases the potential scale and complexity of a breach. The more data stored across systems, the harder it is to protect and contain. E.g., a company storing millions of personal records is at greater risk than smaller volumes of datasets. - Data Type: What categories of personal data are involved, such as PCI or PHI?
Certain data types carry higher regulatory and legal risk. PCI and PHI data are especially sensitive, with specific standards and penalties for mishandling. E.g., exposure of credit card data may entail PCI DSS fine, while leaking PHI health records could result in expensive class action lawsuits. - Data Sensitivity: How harmful would misuse of this data be to individuals?
The more sensitive the personal data, the greater the potential harm to affected individuals. Misuse of highly sensitive data can lead to discrimination, or other economic and social consequences for individuals. E.g., leaking someone’s name connected with their health insurance carrier may have minor consequences, while disclosing their medical history could cause serious, lasting harm. - Subject Nationalities: Which jurisdictions govern the data, and how do privacy laws differ?
Different countries have different legal requirements and penalties for data breaches. The nationality of data subjects determines the regulatory response. E.g., a breach involving EU citizens may trigger heavy GDPR fines, while one involving U.S. citizens could result in class actions and mandatory breach notifications. - Processing Methods: How is personal data handled - internally or by third-party tools?
Use of third-party services or analytics tools can introduce additional risk, especially if individuals are unaware of how their data is being processed. E.g., a website using Google Analytics without proper consent may face regulatory penalties under privacy laws such as GDPR.
Once various DB scenarios have been identified through assessing data segments, the next step is to assess their relative severity using the secondary factors. Gathering input from relevant stakeholders across the organization will support answering the guiding questions and prioritizing scenarios for further analysis.
Financial Theft & Fraud: When Cyber Incidents Drain Capital
Financial Theft & Fraud (FTF) scenarios refer to cyber incidents that result in the unauthorized transfer or theft of funds from an organization, either through external manipulation (e.g., phishing, social engineering) or internal misuse of access rights. These incidents compromise the confidentiality and integrity of payment processes and result in direct financial losses.
Identifying the worst-case FTF scenario requires understanding which type of transaction, if compromised, would lead to the most significant financial damage - whether from a single high-value payment or the slow accumulation of smaller, undetected thefts over time.
Framing a Financial Theft & Fraud cyber scenario
Defining a worst-case scenario for FTF involves understanding the financial processes in a company. Primarily, the type of transaction defines the different potential scenarios, while secondary factors strongly influence the severity. For example, a single redirected capital transaction of €25 million via a compromised executive account constitutes a different risk scenario than the prolonged embezzlement of €15,000 per month by an internal actor over several years.
Assess how your business generates value
The following considerations help provide a clear overview of the organization's financial flows and payment streams, which are central to the value generation of the business:
- For which business processes are financial transactions needed?
- When and where are financial transactions conducted?
- Who conducts financial transaction?
Mapping of critical processes and digital interdependencies
Primary factors - this defines the scope of the scenario.
- Transaction Type: What are the different payment types and processes - one-time large transfers or repeated small payments? The nature of the transaction defines the different scenario motives - either a one-off payment by an external attacker that causes immediate loss, or a continuous internal fraud using small recurring payments by a malicious insider. E.g., a €40 million capital transaction redirected in a single event represents a different risk scenario than an insider diverting €10,000 monthly over several years.
Define risk scenarios: how a cyber incident would impact financial outcomes
Secondary Factors – these influence the financial severity of a scenario.
- Payment Frequency: How often do transactions occur that could be targeted? Frequent transactions increase the number of exploitable moments for an attacker. E.g., a channel processing €150,000 per month creates a smaller target than one handling €50,000 multiple times per month.
- Approval Controls: What payment limits or thresholds are in place to restrict unauthorized transfers? Strict approval limits, such as banking transaction limits, can significantly reduce the impact of a fraudulent transaction, even if it’s initiated. E.g., a payment system that automatically blocks transfers over €100,000 without executive approval can prevent large-scale losses, even if initial access is compromised.
- Transaction Volume: What volume do the payment transactions have? The overall volume of money in a targeted stream determines the financial magnitude of a potential breach. E.g. a one-time transaction for a contractor service is less attractive than one-time M&A transaction.
Once FTF scenarios have been identified, the next step is to estimate their potential financial impact using the secondary factors. Collaborating with finance, and internal audit stakeholders is essential to answering these questions and ranking scenarios for further analysis and response planning.
Conclusion: Empowering Strategic Decisions with Cyber Insights
Identifying worst-case cyber scenarios isn’t about predicting every possible cyber threat. It’s about defining the specific, financially-driven scenarios that would hurt your organization most. This top-down, cyber risk methodology, provides a comprehensible method for uniquely identifying cyber scenarios from a financial view. By identifying the worst-case consequence scenarios, you can:
- Build an understanding of the financially worst case cyber scenarios for the organization.
- Provide a comprehensive storyline and awareness of cyber risk to the boardroom.
- Derive a strategic action plan and focus resources based on the scenarios.
This approach supports a shift from reactive protection to strategic cyber risk management - empowering you to receive a transparent view on cyber risk, and protect shareholder value.
