As systems grow increasingly abstract and interconnected, the very complexity that enables our advanced capabilities has become perhaps our most significant vulnerability. This article explores how complexity itself has emerged as a meta-risk that overshadows conventional cybersecurity threats and suggests that the next major innovation in cybersecurity might rely on achieving simplicity.
Introduction
The cybersecurity community has traditionally focused on identifying, assessing, and mitigating specific risks - from malware and data breaches to system failures and even human error. However, an ominous meta-risk now overshadows these conventional threats: complexity itself. As systems grow increasingly abstract and interconnected, the very complexity that enables our advanced capabilities has become perhaps our most significant vulnerability.
The Paradox of Frictionless Interconnection
Today's IT infrastructure represents a paradox: systems designed to facilitate frictionless interconnection and intuitive use are simultaneously becoming more vulnerable precisely because of these qualities. The interconnected nature of modern technology stacks means that understanding the entire system and its potential failures has become nearly impossible for any single person or even team. A single weak point in the supply chain can cascade into a worldwide system failure.
The Complexity Arms Race
Perhaps nowhere is the complexity risk more evident than in the emerging battlefield between AI security tools and AI-powered attacks. Security vendors deploy increasingly sophisticated machine learning algorithms to detect threats, while attackers leverage the same technologies to evade detection.
This creates a classic arms race scenario, but with a crucial difference: both sides are deploying systems whose behaviors cannot be fully predicted or understood, even by their creators. When AI tools measure risk against AI-fueled attacks, we enter uncharted territory where complexity compounds exponentially.
Why Traditional Risk Models are Failing
Conventional risk frameworks operate on the assumption that risks can be identified in advance, assessed for impact and likelihood, and mitigated through specific controls. But complexity introduces risks that defy this paradigm:
- Emergent behaviors: Properties that appear only when components interact
- Cascading failures: Chain reactions that propagate unpredictably
- Unknown unknowns: Vulnerabilities we cannot anticipate until exploitation (also known as black swans)
Conventional risk frameworks do not incorporate the above into their controls, yet these are the risks that have led to many of the biggest failures of the past few years.
Case Studies
The Log4j Vulnerability
The Log4j vulnerability (CVE-2021-44228) demonstrated how a simple component in a complex ecosystem can create catastrophic, system-wide risk. A single vulnerability in a widely-used logging utility affected millions of devices globally. Most organizations couldn't respond efficiently because they simply didn't know where all instances of Log4j existed in their sprawling technology stacks.
Colonial Pipeline
The 2021 Colonial Pipeline attack represents a perfect storm of complexity-induced vulnerability. What appeared to be a straightforward ransomware attack against an energy company revealed a disturbing truth: the complexity of interconnected operational technology (OT) and information technology (IT) systems had created unforeseen attack vectors and catastrophic dependency chains.
The attack succeeded not because of particularly sophisticated techniques, but because system complexity obscured critical security gaps. A single compromised password provided access to a VPN that lacked multi-factor authentication, which ultimately led to the shutdown of a pipeline supplying 45% of the East Coast's fuel. The company's response was equally hampered by complexity - they shut down the entire pipeline operation because they couldn't determine the extent of the breach or isolate affected systems from operational ones.
The aftermath cost millions in ransom, tens of millions in remediation costs, and created widespread fuel shortages. Most tellingly, the complexity of Colonial's systems meant that even after paying the ransom, the decryption tool worked so slowly that the company largely relied on their own backups for recovery.
Near-Miss: The CVE Program
In 2022, MITRE faced significant criticism when proposed budget cuts threatened the Common Vulnerabilities and Exposures (CVE) program—the very system designed to help manage the complexity of security vulnerabilities across the digital ecosystem. The potential cancellation revealed a troubling paradox: as system complexity increases exponentially, our mechanisms for tracking vulnerabilities in those systems face resource constraints.
The CVE system itself had become so complex and overwhelmed that it had begun to experience significant delays in processing vulnerability reports, sometimes taking months to assign CVE IDs to critical vulnerabilities. The program had grown from handling hundreds of vulnerabilities annually to tens of thousands, reflecting the explosion of complexity in modern systems.
Public outcry from the cybersecurity community ultimately saved the program from cancellation, but the incident highlights a sobering reality: our vulnerability management systems are struggling to keep pace with the complexity they're designed to address. The very infrastructure created to help us manage complexity risks has itself become vulnerable to complexity overload.
The exact same scenario repeated itself last week (mid-April 2025), when the CVE program was once again at risk of being cancelled and the contract was only renewed at the 11th hour.
The Fundamental Question: Should We Continue Down This Path?
Rather than simply accepting ever-increasing complexity as inevitable, perhaps the most important question we should be asking is whether we want to continue down this path at all. The cybersecurity community has long operated under the assumption that more sophisticated systems, more advanced tools, and more complex countermeasures are the answer to emerging threats. But what if this approach is wrong?
The Case for Technological Discernment
Throughout history, the most enduring systems have been those characterized by elegant simplicity, suggesting we may be approaching a complexity threshold beyond which security becomes mathematically impossible. This complexity also creates a dangerous illusion of control - as dependencies multiply and interactions become more abstract, our ability to predict system behavior diminishes proportionally.
Already, most organizations are operating infrastructures so complex that no single person fully understands them. A compelling alternative emerges when we consider that the next major innovation in cybersecurity might not be more complexity, but less. Designing systems with strict complexity constraints could force more elegant, inherently secure solutions, recognizing that often the most secure component is one that doesn't exist at all. The strategic removal of unnecessary functionality may prove our strongest defense against the vulnerabilities that complexity inevitably introduces.
Personal Experience: Real-World Combat Is Different From An Audit
Here's where I get a bit personal. I used to be in the Infantry. We had a saying, "slow is smooth, smooth is fast." New recruits that had seen combat on TV often tried to go as fast as possible which resulted in them tripping, getting their rifle barrel jammed up with mud and their strap tangled up in their body armor, and being overcome with exhaustion within the first five minutes of an exercise or mission.
Experienced soldiers understood the need to base their action on methodical, simple, and time-honed movements. They focused on drilling magazine changes, ready ups, and heel-toe walking. Cybersecurity is no different. In a combat situation, organizations that have perfected the basics will offer a much better response to an existential threat than one that just bought an expensive license to the latest hotness that they heard about at RSA over hand-crafted cocktails.
Practical Approaches to Reversing Course
The truth is that under the hood, most IT capabilities are still built using protocols and principles that have existed for 30+ years. The foundations for secure, reliable systems don't require the latest AI-powered tools or bleeding-edge technologies, they require disciplined application of proven approaches that have stood the test of time.
Consider how fundamental security principles continue to address our core needs:
- Role-Based Access Control (RBAC), a concept formalized in the 1990s, still provides the most rational approach to managing permissions and preventing unauthorized access. When implemented through established protocols like LDAP (Lightweight Directory Access Protocol), organizations can create authentication systems that are both robust and comprehensible.
- Network segmentation through basic subnetting—a practice as old as TCP/IP itself—remains one of the most effective security controls. Creating logical boundaries between system components limits lateral movement in ways that today's micro-segmentation tools attempt to replicate with vastly more complex implementations.
- The humble firewall, with clear ingress and egress rules, still provides security benefits that are both substantial and transparent compared to next-generation tools whose rule processing can be nearly impossible to audit.
- Secure file transfers through protocols like SFTP or SCP offer a perfect example of capability without unnecessary complexity. These protocols accomplish what organizations need without the opaque complexity of many modern data transfer solutions that add features at the expense of comprehensibility.
- Cybernetic feedback loops, the basic principle of using system outputs to inform adjustments to inputs, provide the foundation for effective change control as well as system monitoring and incident response. This approach doesn't require sophisticated AI anomaly detection; it simply requires thoughtful instrumentation of systems and clear thresholds for action.
- Immutable, timestamped logging (implemented through technology as basic as append-only files with cryptographic signing) provides accountability that many blockchain-based solutions attempt to replicate with orders of magnitude more complexity.
- Even inventory management (e.g., knowing what exists in your environment) doesn't require sophisticated asset discovery tools. Infrastructure as code and basic network scanning tools like Nmap can provide this visibility without the opacity of agent-based solutions that introduce their own potential vulnerabilities.
The path forward may not be adopting even more complex technologies, but rather returning to these fundamental principles and implementations. This doesn't mean rejecting all innovation, but rather asking whether each new layer of technology truly addresses a need that cannot be met with simpler, more established approaches. It means recognizing that the latest isn't always the greatest, especially when "latest" also means "most complex" and "least understood."
Conclusion
The cybersecurity industry stands at a crossroads. We can continue the arms race of complexity, building ever more sophisticated systems to defend against increasingly advanced threats. In this scenario, cybersecurity vendors may make a lot of money, but it is a path that will ultimately lead to systems that are fundamentally beyond our ability to secure. Or we can challenge the assumption that more complexity is inevitable and begin the difficult work of simplification.
Perhaps the most profound security innovation won't come from adding another layer of defensive technology, but from having the courage to question whether the path of ever-increasing complexity is one we want to continue following at all. In a world obsessed with technological advancement, choosing simplicity may be our most radical and effective security strategy.