KubeArmor in 2026: Protecting IoT and Edge Workloads with eBPF

What Is Edge Computing and Why Security Matters?

• Edge computing has moved far beyond just being a buzzword. In 2026, it’s the foundation of how modern systems process data  from AI models running at traffic intersections to connected robots on manufacturing floors. With 5G, AI inferencing, and real-time analytics, workloads are shifting closer to the data source to minimize latency and bandwidth use.
• But this decentralization brings an inevitable challenge, security drift. Every device, every edge node, and every connected system expands the attack surface. Traditional perimeter security models simply don’t scale to hundreds or thousands of distributed endpoints.
• Edge environments demand runtime protection, a system that can continuously observe, control, and enforce security directly where workloads execute. This is exactly where KubeArmor steps in, extending zero-trust and runtime enforcement to the edge.

More data is being created from more locations than ever before. With the increase in IoT devices and the need to process information in real-time creates edge computing a necessity for the future.

Edge computing is a way to bring computational and storage workloads close to the edge where the data is created. The aim is to reduce latency by doing data analysis outside the cloud at the edge of the network where real-time processing of data is required. This also reduces the bandwidth as fewer processes are sent to the cloud.

Edge computing provides reliability as it continues to operate even when the communication channels are down. Furthermore it provides resiliency by reducing a central point of failure, as is the case of centralized cloud servers.

High-level topology for a typical edge computing setup (Source: LF Edge – Open Horizon)

Key benefits offered by edge computing:

• Improved performance and reduced latency
• Cost efficient
• Reliability and Flexibility

Understanding Open Horizon and Its Role at the Edge

Open Horizon is a platform for managing the service software lifecycle of containerized workloads and related machine learning assets.

• Open Horizon, originally developed by IBM and now an open-source project under the LF Edge umbrella, serves as a robust orchestration framework for managing IoT and edge workloads at scale. It automates how services are deployed, updated, and monitored across thousands of geographically distributed nodes.
• By 2026, Open Horizon has evolved to support Kubernetes 1.30+, AI/ML workload automation, and container lifecycle management for resource-constrained edge devices. Its policy-driven design makes it a natural complement to KubeArmor’s runtime enforcement.
• AccuKnox integrates KubeArmor with Open Horizon to deliver a layered security model – where Horizon manages the orchestration and KubeArmor ensures that each containerized edge workload runs within clearly defined behavioral boundaries. The result is a security fabric that scales as easily as the edge itself.

Open Horizon provides features to help manage and deploy workloads from a management hub cluster to edge devices and remote instances of orchestrated clusters. It is:

• Edge Native
• Decentralized – Minimal central Management Hub with independent Agents on each node
• Zero Touch – Installation and device-specific configuration is fully automated
• Disconnected – Fully autonomous agent continues to monitor and manage applications even when disconnected from their Management Hub

Open Horizon components (Source: LF Edge – Open Horizon)

The Biggest Hurdle – Securing Distributed Edge Environments

The explosion of IoT and edge devices has also led to a surge in complex threat vectors. Attackers are no longer just exploiting unpatched firmware  they’re using AI-powered botnets, LLM manipulation techniques, and supply-chain vulnerabilities to compromise devices at scale.Security at the edge must, therefore, extend beyond monitoring, it needs active runtime enforcement. You can’t rely solely on detecting anomalies; you must prevent unauthorized actions before they escalate.

The most identified downside of edge computing is that it can increase attack vectors.

Data at the edge can be difficult to handle when it’s being collected from multiple sources that might not be as secure as a centralized systems. These devices often contains sensitive user data so it becomes more important to protect both the host edge node and the applications running on it.

Open Horizon addresses most of these security issues by following ways:

• All participants are untrusted and must formally establish trust
• Agents are autonomous and each of them has authority only for their node
• Switchboards enable secure communication but can neither read nor write anything
• Exchange relies on an external authn/authz mechanisms
• All code and configuration is hashed and cryptographically signed
• All participants are anonymous and known by the public keys and a node ID

Due to Open Horizon’s autonomous agents, a compromised node doesn’t affect the larger system. But even after all the above security measures, if a malevolent actor somehow gets control of an edge node, they will be able to access and execute anything they want on the node thus compromising the local agent.

Thus it becomes equally important to protect these independent agents too.

2026 IoT Threat Trends

• AI-driven malware that learns and adapts to network defenses.
• Firmware-level persistence exploiting outdated device software.
• Model poisoning attacks targeting on-device AI inference engines.
• Cross-container privilege escalation through misconfigured runtimes.

This environment demands kernel-level visibility and control, and that’s exactly where eBPF-based runtime protection tools like KubeArmor stand out, enforcing policies right inside the operating system without affecting workload performance.

KubeArmor x Open Horizon

Accuknox’s open source application hardening solution based on KubeArmor and Discovery Engine provides:

• Deep observability of edge workloads
• Ability to do policy enforcement at granular level
• Ability to automatically generate least permissive security posture

How KubeArmor Secures IoT Edge Workloads

What Is KubeArmor?

KubeArmor is a cloud-native runtime security enforcement system that restricts the behavior (such as process execution, file access, and networking operation) of containers and nodes (VMs) at the system level.

• KubeArmor is an open-source runtime enforcement system that brings proactive security to Kubernetes, IoT, and edge workloads. Built on eBPF (Extended Berkeley Packet Filter) and Linux Security Modules (LSMs) like AppArmor and SELinux, it enables fine-grained control over what a workload can or cannot do  right down to file access, process execution, and network behavior.
• Originally incubated within the CNCF sandbox, KubeArmor has grown into one of the most active runtime protection projects, supported by developers and security teams across industries. It’s now trusted in environments ranging from small edge nodes to hyperscale clusters.
• In essence, KubeArmor translates zero-trust principles into runtime reality  every workload is isolated, observed, and controlled with least-privilege policies.

KubeArmor operates on top of Linux Security Modules (LSMs) like AppArmor, BPF-LSM and SELinux which provides a kernel-level security enforcement. It uses eBPF based system monitoring for providing container aware logs for policy violations by monitoring the container’s processes operations.

How eBPF Enables Lightweight Edge Protection

eBPF has become the backbone of modern kernel-level observability and enforcement. For IoT and edge devices  where CPU, RAM, and storage are limited. eBPF offers a low-overhead way to instrument the kernel without modifying the kernel itself.

Here’s why that matters:

• Low Resource Consumption: eBPF programs run efficiently inside the kernel space, ideal for devices with limited capacity.
• Deep System Visibility: Every system call, file event, and network connection can be observed without agents or intrusive hooks.
• Real-Time Enforcement: KubeArmor uses eBPF to instantly block unauthorized actions, preventing compromise before it propagates.

This makes eBPF-based security a natural fit for edge environments where both efficiency and depth of protection are non-negotiable.

KubeArmor on Open Horizon

Enforcement: KubeArmor allows operators to apply security postures at the kernel-level (using LSMs like AppArmor, BPF-LSM). It can protect both the host and workloads running on it by enforcing either some predefined security policies or automatically generated least permissive security policies (using Discovery Engine).

The generated logs can provide great insight on the current operations happening inside the workloads. Further, the alerts on policy violation provide detailed reason for the violation.

Let’s apply a sample policy to prevent unauthorized updates to root certificates and restrict access to certificates folders.

The subsequent alert generated on violation of above policy:

Here the alert shows that the process update-ca-certificates (with full path) when run by parent process /bin/bash resulted in a “Permission denied” due to a policy action of “Block” being applied.

KubeArmor can be run both on the Open Horizon Management Hub and the Agents as a system service or in container mode.

Note: The PodName field in the alert makes more sense in context of k8s workloads

Observability: KubeArmor can provide container-aware observability information about the operations happening:

1. from Agent node to Management Hub (and vice-versa)
2. between the containers and the agent edge node
3. inside the containers running on the Agent node

For providing container-aware observability, KubeArmor takes use of an eBPF-based system monitor, which tracks process life cycles in containers and nodes.

Discovery Engine

Discovery Engine discovers the security posture for your workloads and auto-discovers the policy-set required to put the workload in least-permissive mode.

The engine leverages the rich visibility provided by KubeArmor and Cilium to auto discover the systems and network security posture.

Auto policy discovery is an open source policy recommendation system. It is a plug-in for Kubernetes environments that discovers network and system policies based on the collected network and system logs from the various container network interfaces (CNIs). The engine leverages aggregation techniques to reduce the number of policies discovered, uses pod labels for rules specification, and handles the discovery across multiple dimensions (networks, systems).

The Discovery Engine can be used to generate least-permissive allow policies for both host and the containers running on it. These policies when applied provides an isolated Zero Trust environment where only necessary operations are allowed rest everything is denied by default.

Key Updates in KubeArmor v0.11+

The latest KubeArmor v0.11+ releases have introduced several capabilities tailored for IoT and AI-edge workloads:

• ARMv9 Compatibility: Extends runtime protection to new-generation edge processors.
• AI Anomaly Detection: Uses behavior baselines to flag irregular activity from AI or ML containers.
• OpenTelemetry Integration: Enables unified observability pipelines for both runtime and network events.
• Improved Policy Templates: Ready-to-deploy policy packs for edge devices, sensors, and gateway workloads.

📘 Reference: KubeArmor GitHub Releases

Deploying KubeArmor with Open Horizon

Integration Overview

Open Horizon can deploy KubeArmor as part of its edge services layer. Each node managed by Horizon runs an agent that handles registration, deployment, and updates. By integrating KubeArmor within this stack, security policies are pushed automatically to devices as they come online.

services:
  - name: kubearmor
    image: kubearmor/kubearmor:latest
    deployment:
      type: docker
      restart_policy: always
    policies:   - ./policies/edge-protection.yaml

This YAML snippet creates a simplified configuration where Horizon deploys KubeArmor with predefined runtime policies across distributed devices.

Discovery Engine and Policy Enforcement

The Discovery Engine within KubeArmor continuously profiles workloads to understand what normal behavior looks like  then suggests security policies automatically.

Once enforced, runtime policies define exactly which files, directories, or processes can be accessed. Any deviation, such as an unauthorized script execution or binary modification  triggers a block and an alert.

AccuKnox’s enterprise edition builds on this with automated policy orchestration and centralized visibility, giving teams a single dashboard to manage thousands of edge nodes.

Example Deployment on ARM Edge Devices

• KubeArmor supports ARM-based hardware widely used in edge environments such as Raspberry Pi 5, Jetson Orin Nano, and NXP i.MX9.

A typical setup looks like this:

sudo apt update && sudo apt install docker.io
docker run -d --name kubearmor --privileged \
  -v /var/run/docker.sock:/var/run/docker.sock \
  kubearmor/kubearmor:latest

Within seconds, the device gains runtime enforcement capabilities. Combined with Open Horizon, updates and policy changes flow automatically, ensuring protection stays consistent even across disconnected or remote nodes.

Real-World Applications and Use Cases

Smart City Infrastructure

City-level IoT systems – from traffic sensors to surveillance nodes run on distributed, containerized workloads. KubeArmor enforces runtime isolation, ensuring compromised nodes can’t laterally move within the network.

Industrial IoT and Manufacturing

Factories use smart controllers, robots, and edge servers that often run legacy Linux stacks. KubeArmor protects these devices from unauthorized firmware access and file modifications, reducing downtime risks.

Edge AI and 5G Networks

Telecom operators and AI service providers deploy edge inferencing clusters for latency-sensitive applications. With KubeArmor, they can apply fine-grained execution policies that safeguard model integrity and prevent data leakage at runtime.

KubeArmor vs Falco vs Cilium Tetragon

For detailed comparisons, explore related blogs on Best Container Security Tools for Runtime Protection.

Ready for a Personalized Edge Security Assessment?

👉 Schedule Your Assessment

As IoT and edge ecosystems expand, proactive runtime protection becomes non-negotiable.
Book a free consultation with AccuKnox experts to evaluate your current edge security posture and explore how KubeArmor can harden your distributed workloads.

FAQ 

1. What is KubeArmor?

KubeArmor is an open-source runtime security solution that enforces access control and behavioral policies for Kubernetes and edge workloads using eBPF and LSMs.

2. How does KubeArmor protect IoT devices?

It isolates workloads, monitors system calls, and blocks malicious behavior directly at the kernel level, minimizing performance overhead for constrained IoT devices.

3. What’s new in KubeArmor 2026 releases?

Recent versions add AI threat detection, ARMv9 support, and enhanced observability integrations with OpenTelemetry.

4. How does KubeArmor compare to Falco or Tetragon?

KubeArmor focuses on inline policy enforcement, while Falco and Tetragon excel at detection. Many teams combine them for full-spectrum runtime defense.

Conclusion

Containers are lightweight with a very low footprint making them a natural fit for edge devices.

With edge computing shifting towards containerized workloads and in few cases to orchestrated kubernetes workloads, it becomes important to have a security solution which can not only provides enforcement into different forms of deployment but can also provide real-time container-rich observability.

KubeArmor supporting un-orchestrated containers, K8s workloads and bare metal VMs makes it an ideal universal engine. It’s kernel-level runtime security enforcement and container aware observability brings best of both the worlds.