Utility operating systems at the grid edge pose an overlooked risk

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Andrew Rynhard is chief technology officer for Sidero Labs.

Utilities are increasingly relying on edge computing to support fast, dynamic decision-making across distributed infrastructure. From automated grid balancing to substation control and remote fault detection, edge deployments are helping modernize aging critical infrastructure and drive efficiency.

But as utilities become more software-driven, they’re also introducing new cybersecurity challenges, and nowhere is that more true right now than at the edge.

The expanding edge footprint is a significant security shift. Edge nodes are being deployed at transformer stations, within distributed energy resources, at remote monitoring points and alongside smart meters. These systems often operate in locations where no IT staff is anywhere near, let alone onsite. They may rely on cellular or intermittent connections, and they often run continuously for years without routine maintenance cycles.

For adversaries looking to disrupt utility operations or test the resilience of national infrastructure, edge systems have become an increasingly tempting target. However, the security conversation still tends to revolve around network segmentation, threat detection or endpoint access control. Important as those are, they miss one foundational layer: the operating system.

The overlooked surface: OS-level risk in utilities

Every edge deployment runs an operating system and, in many utility environments, that OS is the weakest link. Traditional Linux distributions (originally built for servers or desktops) still underpin many OT systems, grid controllers and IoT gateways. These OSes are powerful, flexible and familiar. But they weren’t designed for today’s threat environment, nor for the realities of edge deployments that now often run on containerized architecture.

Most conventional OSes are mutable by default. Their configuration can drift, their file systems can be written to by any number of services or processes, and their security settings can be altered over time (often unintentionally). In a centralized data center or enterprise network, these issues are manageable because systems are easy to audit and maintain. At the edge, where access is limited and conditions change, they become liabilities. A system that is secure on Day 1 may no longer be secure on Day 1,000, and you may not know what changed.

For utilities now operating thousands of edge systems, the risk compounds quickly. A small misconfiguration rolled out across 10,000 nodes isn’t just a technical error, but an exploitable pattern. Attackers don’t need zero-day vulnerabilities when they can exploit outdated packages, exposed services or poorly secured update mechanisms.

Why immutability matters at the edge

To meet modern security expectations, utilities’ edge infrastructure needs more than reactive patching or policy enforcement. It also needs to be designed from the ground up to resist tampering, misconfiguration and drift. This is where the concept of an immutable operating system becomes powerful.

An immutable OS is one that cannot be altered during runtime. The system boots into a known-good state (defined and verified ahead of time) and remains in that state throughout operation. No one can log in and manually tweak firewall settings, nor can a rogue process write to the disk. Configuration is declarative, meaning it’s defined through code and automatically enforced on every single node, every single time.

This matters to utilities because the edge is largely inaccessible. If something goes wrong (whether it’s an outage, a breach, or just a silent misconfiguration), physical intervention is costly and slow. Immutable systems reduce the need for human touch. They also make it far easier to reason about security posture at scale. If every node is running the exact same image, with the exact same configuration, verified cryptographically, then audit becomes a matter of validating one system, not thousands.

Immutable systems also simplify updates. Rather than patching live systems in-place (which is a risky prospect in operational technology), you replace the running image with a new, verified version. The update is atomic, meaning it either succeeds completely or fails without altering the running system. That kind of rollback safety is critical when uptime and predictability matter more than raw agility.

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