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Abstract: Security debt is formed through decisions made with good intent: to move faster, deliver value, or stretch limited resources a little further. But over time, deferred fixes, aging systems, and missing governance can slowly compound until they throw an organization off balance. Unlike technical debt, security debt does not just affect performance, it also affects trust. It seeps into operations, compliance, and culture, shaping how teams think risk and how leaders make decisions. As pressures related to cloud, artificial intelligence (AI), and regulations accelerate, the weight of this unseen debt has become one of the largest threats to resilience.

This paper explores where security debt comes from, how it grows, and its consequences when left unmanaged. It also outlines ways to identify, measure, and reduce it. Through practical examples and a measurable framework called the Security Debt Index (SDI), this paper shows how visibility, accountability, and shared ownership can turn debt from a liability into a tool for building trust, agility, and long-term resilience.

Every day, organizations make decisions where to spend limited time, resources, and attention. In cybersecurity, these trade-offs often leave behind something hidden but increasingly costly: security debt. Security debt represents the accumulated risk created by outdated systems, deferred remediation, unpatched vulnerabilities, and underresourced programs. Much like technical debt (the cost of quick fixes over long-term stability), security debt reflects the exposure that grows when speed, innovation, or convenience outpace security.

Security debt is tied directly to business risk. It threatens confidentiality, integrity, and availability while eroding trust among customers, partners, and regulators. Today’s digital ecosystem—with the accelerated pace of cloud adoption, artificial intelligence (AI), and compliance obligations—only amplifies this risk. Across industries, for example, AI models are deployed before governance catches up, introducing bias or leaking data and proprietary information. Shadow IT also thrives in the gaps, as teams add tools and integrations faster than security can track them. As organizations modernize and interconnect systems, attack surfaces and accountability surfaces will only continue to expand.

Security debt is a reflection of how decisions, priorities, and culture shape an organization’s ability to manage risk. When left unmanaged, it is a blind spot that drives breaches, erodes trust, and limits an organization’s ability to adapt and innovate securely. Security debt is just one of many security risk factors, but it is an important consideration for enterprises that value speed and innovation. This paper explores the causes, impacts, and strategies to identify, measure, and reduce security debt across technology, culture, and governance. Its goal is to equip leaders with a structured framework that treats debt as a tangible business liability that demands executive attention and shared accountability.

Security comprises many factors, one of which is security debt. Because of a desire to move quickly and adopt the newest tools and technology, many enterprises inadvertently accrue security debt. When left unresolved, this debt can have serious consequences for enterprises.

American computer programmer Ward Cunningham first introduced the concept of technical debt in 1992, comparing rushed software work to taking on a financial loan: it speeds delivery now but creates long-term costs related to maintenance and performance. 1 The analogy was later expanded beyond code into architecture, process, and design. 2

Security debt has emerged as a natural extension. Unlike technical debt, which affects efficiency, security debt directly increases exposure to threat activity, compliance gaps, and loss of trust. These gradually weaken confidence in the systems designed to protect the business. When organizations postpone essential security work, such as patching, control updates, access reviews, or redesigns, a major disruption can bring these vulnerabilities to light.

Security debt forms across technology, people, and culture. Broadly, it falls into four categories: technical and process debt; business, leadership, and cultural debt; modernization and innovation debt; and governance debt.

Technical and Process Debt

Technical and process debt refers to aging systems, manual processes, and inconsistent patch cycles. In some cases, it may also come from workarounds that enable enterprises to move quickly instead of implementing future-ready and stable solutions. If patching cycles lag or vulnerability management falls behind, gaps may emerge that can become entry points for attackers. These gaps create the “interest” that organizations pay on deferred maintenance. Over time, these issues can erode an organization’s defenses, leading to breaches. For example, according to IBM’s 2025 Cost of a Data Breach Report, organizations with slower containment cycles face significantly higher breach costs. 3

Business, Leadership, and Cultural Debt

Security debt can also originate with leadership, such as executive management and the board of directors, who set the tone of an enterprise’s culture. For instance, when cybersecurity is treated as a project instead of a shared responsibility, this can create a lack of accountability across the organization. Often, in these cases, budgets are deferred, governance is inefficient, and awareness training is neglected. Budget and resource allocation may also lead to this type of debt. Culture is important as well; when teams assume “someone else will handle it,” resilience may be impacted.

Modernization and Innovation Debt

Modernization debt occurs when enterprises keep legacy systems running without updating them to state-of-the-art, modern systems and applications. Innovation debt is similar, but it relates more to a failure to adopt emerging technologies that improve and create efficiency.

Governance only works when the right people understand, support, and act on enterprise policies, which stresses the importance of engagement from security, compliance, legal, procurement, and leadership. However, in many enterprises, innovation outpaces governance, resulting in governance-related debt. When new systems launch without the right guardrails and oversight, for example, they introduce invisible layers of exposure. Industry research consistently links mature governance and board-level cyberoversight with reduced breach impact, including lower breach costs and faster detection and containment as compared to less mature organizations. 4

Every organization’s version of security debt looks different, but the reasons it forms are remarkably consistent. These include:

Security debt develops slowly, decision by decision, with each skipped patch, delayed audit, or unchecked configuration adding another layer of risk. These layers compound until the organization hits a tipping point, such as a breach, audit finding, or compliance violation. Breaches that are identified and contained quickly tend to be less costly. 7 The normal life cycle of security debt is shown in figure 1 .

Figure 1: The Security Debt Life Cycle

When a tipping point is reached, the focus shifts from prevention to containment. Teams might scramble to isolate systems, restore services, and explain incidents. This reactive cycle drains time, budget, and credibility. In this context, breaking the cycle requires deliberate governance actions, such as clarifying ownership and strengthening accountability before the decision, implementation cycle, or security incident occurs.

The following examples show how seemingly minor decisions can have serious consequences for enterprises.

Few examples illustrate security debt better than unpatched systems. Every missed update represents a known risk that has gone unaddressed, usually to avoid downtime or cost.

The 2017 Equifax data breach remains a defining case. A critical Apache Struts vulnerability had been identified, a patch was released, and alerts were issued to the company. However, the update was never applied to Equifax’s systems. Months later, attackers used that flaw to steal the personal data of more than 140 million people. 8 What began as a simple maintenance delay became one of the most expensive breaches in history, costing at least US$575 million and years of trust to rebuild. 9

Weak Identity and Access Management

Weak identity and access management (IAM), such as shared credentials, excessive privileges, lack of credential rotation and monitoring, and poor multifactor authentication (MFA) enforcement, can lead to security debt. In the 2024 Change Healthcare ransomware attack, 10 for example, investigators found that inconsistent use of MFA provided an easy entry point, mirroring the same weaknesses outlined in the federal #StopRansomware advisory. 11 Within days, ransomware spread across critical systems, halting billing and prescriptions nationwide. The ripple effect was staggering: providers could not pay staff or operate, and some even took out personal loans to stay open. 12 The lesson is that security debt can not only impact operations but also human beings.

Siloed Monitoring and Alerting

The average timeline to identify and contain a breach is 241 days ( figure 2 ), 13 proof that security debt related to insufficient monitoring is persistent. Even the most advanced tools can fail when data and alerts are trapped in silos and visibility is weak. Fragmented monitoring between business units, cloud providers, or third-party security operations centers (SOCs) can miss early indicators of malicious activity or compromise. Take the 2020 SolarWinds supply chain breach as an example. Attackers inserted malicious code into a trusted software update, compromising thousands of organizations, from government agencies to Fortune 500 companies. 14 The breach went undetected for months and was ultimately discovered by another vendor investigating unrelated anomalies. 15 This incident shows that visibility requires integration.

Figure 2: Average Time to Identify and Contain a Data Breach 16

Gaps in Governance and Oversight

Governance gaps, including unclear ownership, weak accountability, and insufficient frameworks, create risk, as demonstrated by the 2023 MOVEit breach. In this instance, the Progress Software file transfer tool (known as MOVEit Transfer) was compromised by the CL0P Ransomware Gang, 17 and thousands of organizations across healthcare, government, and finance were affected. 18 The vendor (Progress Software) released a patch quickly, but many affected enterprises were service providers to other enterprises, making remediation complex. 19

Security debt creates operational, financial, reputational, and strategic impacts.

At its core, security debt makes organizations slower and more fragile. Every unpatched system or missing control adds drag to daily operations, which multiplies during a crisis. According to IBM’s 2025 Cost of a Data Breach Report, 86% of breached organizations experienced operational disruption, with activities such as processing orders impacted in the aftermath.

Security debt can also affect agility. Teams working with outdated technology or manual processes have less bandwidth to innovate or strengthen defenses. The constant catch-up cycle can cause human fatigue, and fatigue can lead to mistakes.

The financial cost of security debt impacts projects, audits, and operations. It can manifest as delayed timelines, higher insurance premiums, or rework from teams forced to fix same issues repeatedly. In 2025, the global average cost of a breach was US$4.44 million; regulatory fines and detection and escalation costs were driving factors. 20 Other examples of financial impacts include deferred maintenance that leads to compliance penalties, outdated systems that raise recovery costs, and shaken customer confidence that negatively impacts revenue.

When trust is impacted due to a breach, it affects overall public perception. Customers, investors, and regulators might expect lessons to be learned and applied. In addition, breaches tied to known vulnerabilities or long-ignored risk may do more damage to credibility than novel attacks. This reputational cost can last long after technical remediation, driving customer attrition and leadership turnover.

Strategically, security debt limits decision making and forces leaders to plan around limitations instead of possibilities. When systems are unreliable, for instance, innovation may stall and leaders may hesitate to launch new initiatives, with strategic goals shrinking to fit operational realities. Security debt also changes how success is measured. Instead of tracking growth or transformation, leadership ends up tracking incidents, constraints, and exceptions. However, organizations can confront security debt early by aligning debt reduction to business objectives and embedding it into planning cycles.

Security debt rarely damages only one facet of an organization. Each impact can compound with the —for example, an operational disruption becomes financial loss, reputational damage, and a strategic slowdown ( figure 3 ).

Figure 3: The Compounding Impacts of Security Debt

Recognizing the various impacts is the first step; the challenge is visibility, which involves knowing where security debt exists and how to track progress toward reducing it.

Security debt does not grow in a straight line. Early on, risk accumulates slowly, and teams might delay upgrades, accept exceptions, or postpone fixes with little visible fallout. But as systems become more interconnected and complexity increases, the slope becomes steeper. Teams then spend more time reacting to issues, resulting in fixes costing more, taking longer, and delivering less value to the enterprise. By the time the curve reaches its steepest point, debt has evolved beyond technology and is now organizational. This pattern is what defines the Security Debt Curve (shown in figure 4 ).

Figure 4: The Security Debt Curve

Understanding the curve gives leaders a new lens for viewing risk. Addressing debt early keeps the curve shallow, where action is still affordable and disruption is contained. Deferred action lets that slope grow steeper, with every delay multiplying cost, complexity, and exposure.

The Security Debt Curve illustrates how the longer debt remains unresolved, the more it strains an organization’s agility, resources, and trust.

Identifying security debt is one of the hardest challenges for security and business leaders. Even with strong risk registers or vulnerability data, many organizations struggle to connect isolated findings to a full picture of cumulative exposure. Without that visibility, it is nearly impossible to see where debt is growing the fastest or which risk matters most.

Figure 5 frames identifying security debt as a continuous cycle rather than a one-time exercise. Debt builds, shifts, and compounds over time, which means organizations are constantly monitoring signals, identifying where exposure is growing, assessing impact, measuring progress, and managing trade-offs.

Figure 5: Security Debt Assessment and Indicators Cycle

Most organizations already have the data they need to identify security debt: scans, audits, inventories, and reports. The challenge lies in connecting those signals into a single, coherent story. Structured assessments bring that story into focus, revealing not only what is at risk, but also why the debt exists and where it continues to grow.

The goal of assessment is to build a repeatable way to see where risk collects. A strong approach blends technical insight, governance awareness, and business context. Assessment methods include:

These assessments help construct a living map of where attention needs to shift.

Once debt is identified, the step is to interpret it. Indicators serve as directional signals, pointing to areas of concern. Good indicators do three things: show movement, connect to priorities, and help leaders focus on what requires accountability or investment. The following are practical indicators for tracking debt across different parts of an organization.

Metrics that reveal where risk collects in systems and infrastructure include:

Governance and Process Indicators

Signals that show where accountability or structure may be weakening include:

Emerging Technology Indicators

Metrics that capture how new innovations introduce unseen risk include:

Business and Impact Indicators

Measurements that tie security debt to real business consequences include:

Making Indicators Actionable

To make indicators actionable, organizations can select 10 to 15 that align with their most crucial goals. It is important to give each indicator a clear owner, a review cadence, and a direct connection to a business outcome. Gradually, trends will emerge, showing where debt is compounding, shrinking, or responding to investment. When indicators are defined, measured, reviewed consistently, and visible to the right stakeholders, they can track performance and help leaders make proactive decisions.

Indicators show where security debt exists, while measurement explains how it “behaves” over time. Measuring security debt is understanding the scale, speed, and impact of the debt. Done well, measurement turns debt into something that can be trended, prioritized, and managed like any other form of risk.

The Security Debt Index (SDI) model considers these three dimensions:

Each dimension is scored using a normalized scale (e.g., 1-5) based on the criteria defined by the organization. These scores are then combined to form the SDI ( figure 6 ). This is a composite score that tracks whether the organization’s overall debt posture is improving or worsening. Rather than replacing existing risk ratings, SDI provides a way to track debt—a rising SDI signals that issues are compounding faster than they are being resolved, while a declining SDI indicates that remediation efforts are reducing both exposure and backlog.

Figure 6: Security Debt Index (SDI) Model

For example, a vulnerability affecting a customer-facing system may score high for severity due to business impact. If it has remained open for several months, its duration score increases. If similar vulnerabilities continue to appear across the same platform, velocity rises as well. Even if each issue appears manageable on its own, the combined SDI highlights when unresolved risk is compounding and therefore requires consideration.

The most meaningful insights come from patterns, such as the number of issues closed versus discovered, the average age of open findings, or how quickly critical vulnerabilities are resolved. These patterns show where effort is paying off, where momentum is stalling, and where leadership attention can make the biggest difference.

When used consistently, SDI allows organizations to compare debt trends across systems, teams, or time periods and to prioritize remediation where risk is both material and accelerating. SDI scores are not intended to be precise measurements, but directional indicators that support comparison and decision making.

Reducing security debt should focus on managing what matters most, specifically the risk factors that carry the greatest business impact, regulatory exposure, or operational consequence. The goal is deliberate progress and aligning security, technology, and business priorities so that risk is reduced with intent instead of urgency.

Including security debt in the risk register can help organizations track debt, maintaining visibility throughout the process. Each entry should include the issue, its owner, and the impact if left unaddressed, along with the estimated time, effort, and cost to fix it. Updated consistently, this helps encourage accountability. It can also be a practical tool for communicating progress with leadership, regulators, and partners.

Methods to Reduce Security Debt

Two valuable practices for reducing security debt are incorporating security into DevOps and adopting a zero trust mindset.

In DevOps, automation and speed sometimes surpass controls. Security should be embedded into DevOps, and developers should write code with security in mind. Embedding validation directly into delivery through automated testing, configuration checks, and access reviews prevents vulnerabilities from entering production.

Zero trust addresses both new and inherited risk by shifting the underlying security mindset. Rather than assuming trust based on network location, role, or past access decisions, a zero trust approach treats access as something that must be continuously evaluated and revalidated. 23 Methods such as verifying identity and enforcing least privilege help expose and reduce vulnerabilities, shrinking the number of attack paths.

Together, security-focused DevOps and zero trust practices create a delivery rhythm where speed, safety, and accountability coexist.

Compliance and Regulatory Frameworks

Frameworks and regulations, such as the Payment Card Industry Data Security Standard (PCI DSS) 4.0, Health Insurance Portability and Accountability Act (HIPAA), Health Information Trust Alliance (HITRUST) Common Security Framework (CSF), and National Institute of Standards and Technology (NIST) Cybersecurity Framework 2.0, can provide structure for compliance activities that prevent or reduce security debt. This may include documentation, control testing, and audits. Regular tests and audits, for example, can highlight where risk keeps resurfacing within the organization. The key is moving from “check-the-box” compliance to operational compliance, where policies and controls are embedded into daily processes, consistently applied, and reinforced through ownership. In addition, adopting frameworks can help demonstrate accountability, maturity, and measurable improvement.

Governance Integrations

Governance turns debt management into a continuous practice. Integrating tracking, ownership, and reporting into governance routines (such as risk reviews, architecture and change forums, audit follow-ups, and leadership reporting) helps make accountability a part of daily operations.

As mentioned, modern environments demand adaptive governance. Cloud, AI, and data platforms create risk that traditional controls do not always address, so it is important to expand governance to cover these systems. This is done by defining security and compliance as automated controls within the continuous integration/continuous delivery (CI/CD) pipeline, i.e., policy as code.

When it comes to reducing security debt, the 80/20 principle holds true: most risk stems from a small set of recurring issues, and addressing those few areas delivers the greatest impact. Prioritization helps identify what to focus on, while technical strategies such as automation and modernization make that focus sustainable.

Automation supports prioritization by handling routing work, such as patching, inventory updates, and configuration checks, so that teams can focus on recurring high-impact risk. Modernization reinforces this effort by retiring legacy systems, consolidating tools, and standardizing configurations, which reduces complexity and shrinks attack surfaces.

Risk Trade-Offs: When to Accept, Transfer, or Mitigate

No organization can eliminate all security debt. It is crucial to know which risk to act on, delay, or . Some best practices include:

Framing these choices in business terms turns trade-offs into strategy and balances cost and risk in a way that leadership can support.

Explaining Security Debt to Leadership

Leadership needs clarity and context rather than technical detail. Security debt should be framed in business terms, showing how it affects revenue, operations, and customer confidence. When technical issues are tied to outcomes like reputation, they are more easily recognized as business priorities. For instance, an outdated payment system is not just legacy technology; it is a PCI compliance gap. Weak access controls are not just configuration misses; they are potential service disruptions.

Simple metrics should be communicated to leadership, such as the number of unsupported systems, the average age of findings, or the cost to remediate legacy risk. Visualization methods are useful as well, including dashboards or scorecards (with debt trends per business unit), heatmaps, maturity scores, and trend lines. A heatmap, for example, can show where risk clusters across the enterprise, and a trend line can reveal whether controls are improving or fading. The goal is to communicate findings clearly so that leaders can gain insights and act with confidence.

Leaders set the tone of an enterprise, and culture shifts when executives treat security debt as a shared business risk. This overall mindset change leads to fewer repeat findings, faster remediation, and stronger collaboration.

Security debt will always exist, but its future depends on how organizations manage it. As technology evolves, so does the nature of security debt itself.

AI has the potential to transform how organizations track and reduce security debt. Automated discovery tools can map unpatched systems, expired certificates, or policy gaps in minutes. Predictive analytics can flag areas where controls are most likely to fail, giving teams the foresight to act before incidents occur. But if left unmonitored, AI can create new blind spots or amplify poor decisions made without human oversight. 24 The key is to pair AI’s speed with governance to ensure it strengthens, rather than undermines, resilience.

Governance and disclosure expectations related to cyberrisk are growing stronger. New requirements, such as the US Securities and Exchange Commission’s (SEC’s) cybersecurity disclosure rule, require boards to evaluate and report cyberrisk with the same rigor as financial performance. 25 In some cases, boards must attest that appropriate oversight exists. This forces organizations to quantify what was once intangible: security debt.

Evolutions in oversight are changing how organizations talk risk. Data that was once buried in security reports is now reaching senior leadership and investors, driving more discussions readiness and accountability. In the future, these conversations could evolve into formal reporting on security debt.

Security debt is not a new problem. What makes it different now is visibility. Organizational practices create security debt, but drivers such as innovation, cloud, AI, and speed might provide the tools to measure and reduce it.

The path forward begins with recognition. Organizations must first identify where the debt exists, then prioritize it based on business impact and risk exposure, not just technical severity. From there, progress depends on embedding accountability into culture, governance, and reporting. Security debt must be tracked, discussed, and managed like any other business liability.

The goal is awareness and adaptability. Leaders must understand that debt compounds and that reduction is a continuous process. The organizations that make real progress will be those that stay intentional by acknowledging debt, measuring it honestly, and taking consistent steps to reduce it. Every effort to improve visibility, strengthen governance, and align decisions to business goals brings an organization closer to sustainable resilience.

1 Cunningham, W.; “ The WyCash Portfolio Management System ,” 26 March 1992 2 Sculley, D.; Holt, G.; et al.; “ Hidden Technical Debt in Machine Learning Systems ” 3 IBM, “ Cost of a Data Breach Report 2025 ” 4 ISACA, “ State of Cybersecurity 2023 report ”; World Economic Forum, “ Global Cybersecurity Outlook 2024 ” 5 IBM, “Cost of a Data Breach” 6 US National Institute of Standards and Technology (NIST), Artificial Intelligence Risk Management Framework (AI RMF) , USA, 2023 7 Sobers, R.; “ Data Breach Response Times: Trends and Tips ,” Varonis, 22 June 2022 8 US House of Representatives Committee on Oversight and Government Reform, “ The Equifax Data Breach ,” December 2018 9 US Federal Trade Commission, “ Equifax to Pay $575 Million as Part of Settlement with FTC, CFPB, and States Related to 2017 Data Breach ,” 22 July 2019 10 Gregory, J.; “ Change Healthcare discloses USD 22M ransomware payment ,” IBM 11 US Cybersecurity & Infrastructure Security Agency (CISA), “ #StopRansomware: ALPHV Blackcat ,” 27 February 2024 12 US Senate Committee on Finance, “ Hacking America’s Health Care: Assessing the Change Healthcare Cyber Attack and What’s ,” 1 May 2024 13 IBM, “Cost of a Data Breach” 14 MITRE ATT&CK, “ SolarWinds Compromise ,” 24 March 2023 15 Temple-Raston, D.; “ A ‘Worst Nightmare’ Cyberattack: The Untold Story Of The SolarWinds Hack ,” NPR, 16 April 2021 16 IBM, “Cost of a Data Breach” 17 US CISA, “ #StopRansomware: CL0P Ransomware Gang Exploits CVE-2023-34362 MOVEit Vulnerability ,” 7 June 2023 18 Chestler, A.; Cook Rush, L.; et al.; “ MOVEit Transfer Zero-Day Vulnerability: What Companies Need to Know ,” Baker Donelson, 7 June 2023 19 Simas, Z.; “ Unpacking the MOVEit Breach: Statistics and Analysis ,” EmsiSoft, 18 July 2023 20 IBM, “Cost of a Data Breach” 21 Given that these endpoints or systems are unaccounted for, it can be challenging to develop metrics around them, but risk professionals should work with functional leaders to account for these missing assets. 22 Like asset visibility gaps, capturing the volume of shadow IT is complicated, but risk professionals should attempt to account for the risk associated with shadow IT. 23 NIST, Special Publication 800-207, Zero Trust Architecture , USA, 2020 24 NIST, AI RMF 25 US Securities and Exchange Commission, “ SEC Adopts Rules on Cybersecurity Risk Management, Strategy, Governance, and Incident Disclosure by Public Companies ,” 26 July 2023