A Cyber Collision of Speed, Conflict & Complexity

Cybersecurity is undergoing a fundamental shift. What was once primarily about preventing corporate espionage, hooliganism, and opportunistic criminals has now taken on geopolitical stakes. And now we're all in the crosshairs.

At the same time, the discipline itself is evolving. Whereas the focus was previously on vulnerabilities and perimeter defense, the threatscape today has become far more complex and we've all become far more interconnected and broadly inter-dependent.

But that's not all. There's also the compounding risk factor of AI. These systems are being adopted at a rate far outpacing the security controls meant to govern them.

In this new world, the measure of good cybersecurity has moved from intrusion prevention to control plane integrity.

Current Events As Cause for Concern

Geopolitical cyber operations are no longer edge cases or distant concerns. They are active, escalating, and increasingly indiscriminate. In the Iran conflict, cyberwarfare is being waged to disrupt infrastructure, degrade visibility, and extend impact far beyond any single target. These operations are not precise. They are expansive.

And in a globally connected economy, that makes collateral damage inevitable.

The Stryker attack highlights how a single incident can ripple across supply chains, healthcare systems, and global operations.  A medical device manufacturer – not a government entity, not a defense contractor – was pulled directly into a geopolitical conflict.

The objective was not data theft or ransom. It was disruption. Systems were wiped, operations were impaired, and recovery required rebuilding trust across core infrastructure.

Even without direct device compromise, disruption at the manufacturer level can introduce delays in updates and vulnerability response, or interruptions to servicing and support. Ultimately that'll affect the end user and in this case, potentially the patient.

If you find that thought worrying, you're right. Unfortunately, it's also a defining characteristic of modern cyber risk.

In a highly globalized and interconnected environment, no organization operates in isolation. Every enterprise is a node in a supply chain, a dependency for customers, a platform others rely on.

That means cyber risk is no longer confined to your perimeter, your vulnerabilities, or even your decisions. It is inherited from the ecosystem you operate in.

From Exploitation to Control Plane Abuse

Modern attacks leverage control planes instead of exploits, with configurations as the dominant vector. 

In the Stryker incident, attackers didn’t exploit a software flaw. They compromised identity infrastructure and leveraged endpoint management tooling to wipe hundreds of thousands of devices globally.

No malware. No exploit chain. Just legitimate control planes used maliciously.

It's important to point out that the attack did not exploit some unknown risk. It took advantage of known gaps that were not continuously validated or continuously enforced. That's increasingly becoming the norm.

This is the new attack model:

• Identity becomes the entry point
• Configuration becomes the weapon
• Management systems become the execution layer

Once inside the control plane, attackers inherit administrative authority, policy enforcement capability, and global operational reach.

Security is no longer about preventing access to systems. It is about ensuring the systems that control everything cannot be misused.

Misconfiguration at Machine Speed

AI is accelerating cyber risk – not just by empowering attackers, but by expanding exposure inside organizations.

While adversarial use of AI is a concern, the more immediate risk lies in how AI is being deployed internally: rapidly, broadly, and often without sufficient governance.

AI is now actively shaping enterprise environments. It writes and executes code, modifies systems, accesses credentials, and interacts with business-critical workflows in real time. Agents operate across endpoints, developer environments, browsers, and operating systems.

This introduces a new reality: environments are being built and modified faster than they can be secured.

As a result, the primary AI risk is not exploitation – it is misconfiguration.

From prompt injection and unsafe execution modes to silent data exfiltration and persistent memory, most emerging AI risks stem from failures in configuration, permissions, and control.

The Moltbook breach illustrates this clearly. A single missing control – row-level security – exposed millions of credentials. No sophisticated attack was required. The system was simply deployed faster than it could be secured.

Misconfigurations have always been a leading cause of incidents. What has changed is their scale, speed, and impact.

AI is amplifying all three.

The Detection–Remediation Gap

This is where modern security models begin to break down.

Most tools are built for visibility, not control. EDR monitors behavior. IAM governs identity. Vulnerability scanners flag issues. But each operates within its own domain, producing signals rather than outcomes.

Today’s risk does not exist in isolation. It spans identity, endpoints, applications, and execution layers simultaneously. And yet, detection and remediation remain fragmented across systems.

That fragmentation creates a structural gap.

Detection happens in one place. Remediation happens in another. Between them lies latency, operational friction, and uncertainty – all of which translate directly into exposure.

In a control plane-driven attack model, that delay is critical. Once an attacker gains access, they can act immediately using legitimate systems. There is no exploit chain to interrupt and no malware to quarantine. The window for response is measured in minutes, not days.

Closing that gap is not a matter of faster alerts. It requires a fundamentally different approach.

Remediation must be immediate, coordinated, and safe by design. That means:

• Understanding dependencies across systems in real time
• Predicting the operational impact of every change
• Enforcing corrections without disrupting critical workflows
• Reversing changes instantly if needed

This is particularly acute in environments like healthcare, where uptime, validation, and compliance constraints make every change consequential.

The challenge is no longer identifying risk. It is eliminating it – safely, continuously, and at the speed the environment operates.

A New Model: Continuous Control Across Four Domains

Maintaining control in a modern environment requires more than visibility. It requires continuous enforcement across four distinct domains – each addressing a different failure point in how control is lost.

Configuration Hardening – Establishing a Trusted State

Control begins with knowing that systems are configured securely and remain that way.

This is not a one-time baseline. It is continuous enforcement of desired state across endpoints, identities, and AI systems. Drift must be detected and corrected in real time, before it becomes exposure.

Without this, every other control operates on an unstable foundation.

Vulnerability Remediation & Patching – Eliminating Known Risk

Unresolved vulnerabilities are not theoretical – they are active exposure.

Tracking risk is no longer sufficient. Vulnerabilities must be remediated quickly and safely, with automation that accounts for system dependencies and operational impact.

The objective is not prioritization. It is elimination.

Continuous Compliance – Proving Control at All Times

Compliance can no longer be a periodic exercise. It must reflect the live state of the environment.

This means continuously validating that systems, identities, and configurations align with policy – including emerging areas like AI usage and data access.

In this model, compliance is not evidence of past posture. It is proof of present control.

Application & AI Control – Governing What Actually Executes

Ultimately, risk materializes through execution.

Organizations must control which applications, scripts, AI agents, and plugins are allowed to run – and under what conditions. This includes enforcing trusted execution paths and preventing unauthorized or unsafe behavior at runtime.

Without this layer, attackers can operate freely inside legitimate systems.

Together, these domains shift security from observation to control – ensuring that even as environments evolve, authority over them is never lost.

The Bottom Line

What we are seeing is not an evolution of cyber risk. It is a loss of control at scale.

Stryker shows what happens when disruption becomes the objective. Moltbook shows how quickly exposure can be created. And nation-state conflicts show that once it exists, it will be exploited – whether you are the target or simply in the blast radius.

In a globally connected, AI-accelerated environment, no organization is isolated and no exposure is contained.

Risk propagates. Misconfigurations compound. And attackers no longer need to break in – they can operate through the systems designed to run your business.

Which is why cyber risk is now treated as a material business factor – one that directly impacts operational continuity, liquidity, regulatory posture, and investor confidence.

At the board level, the conversation has already changed. The question is no longer how attacks happen, but whether the business can continue operating when they do. Can we maintain control of our systems, our dependencies, and our outcomes?

It is no longer enough to detect, prioritize, and respond. Organizations must be able to:

• Continuously enforce a secure state
• Safely remediate exposure at scale
• Maintain control across identity, configuration, applications, and AI
• Do so without disrupting the business itself

Because in this model, the cost of losing control is not a security incident. It is operational failure.