SOC automation solution guide 2026 with examples

SOC automation can be a confusing category as there is no single type of SOC automation solution or tool, and most security teams use several different approaches at the same time.

However, the need for SOC automation is much clearer with recent data on SOC automation showing that 93% of organizations are using or planning to use automation in their security workflows.

Similarly, more than a third of security teams say they are overwhelmed by repetitive manual tasks, and 92% of security professionals say automation reduces mean time to respond. Yet just 6% of organizations describe their automation programs as fully mature.

Clearly SOC automation is not a fully explored market segment so this guide is designed to help clarify the SOC automation market options by looking at the core technologies that are used in SOC automation right now.

So, what actually is an SOC automation solution?

There is no single definition of an SOC automation solution. There are several different types of technology that can automate parts of security operations, ranging from simple scripts through to AI agents capable of carrying out multi-step investigations.

1. AI and security agents (Agentic Security Operations platforms)

AI and security agents automate more complex SOC work that previously required an analyst to interpret information, decide what to do next, and move between multiple security tools.

Rather than only following a fixed sequence of predefined steps, agentic systems can use context from alerts, past cases, security tools, internal processes, and other sources to work through more variable investigations.

Agentic Security Operations platforms can sit across existing technologies such as SIEM, EDR, and SOAR, using those tools to automate a larger portion of the analyst's workflow.

Agentic Security Operations Platform example: Legion Security.

Legion Security is an SOC automation solution that learns how analysts investigate alerts and turns those processes into visual workflows that can be inspected and edited. Its platform can then carry out those workflows using the same interfaces and tools used by analysts.

In Legion's published Virgin Money case study, the bank started with a backlog of around 50,000 security alerts. Legion says its agentic automation processed 30,000 of those alerts in under two months, reducing the backlog by more than 60%.

2. SOAR platforms

Security orchestration, automation, and response (SOAR) platforms connect different security products and automate processes across them.

They typically work through predefined workflows known as playbooks. A playbook might enrich an alert with threat intelligence, check an IP address, isolate an endpoint, create a ticket, notify an analyst, and document the response.

SOAR is useful when a security process involves several tools and follows a relatively predictable sequence.

Example: Palo Alto Networks Cortex XSOAR. Cortex XSOAR uses playbooks made up of

tasks, conditions, commands, scripts, and integrations to automate investigation and response processes.

3. Built-in SIEM automation

Security information and event management (SIEM) platforms collect security data from different systems, correlate activity, and generate alerts when events match detection rules.

This gives analysts one central place to investigate activity rather than checking firewalls, endpoints, cloud platforms, servers, and other systems separately.

Many modern SIEM platforms now include automation features too. These can automatically assign incidents, enrich alerts, run response workflows, create tickets, or trigger remediation when certain conditions are met.

Example: Microsoft Sentinel. Sentinel supports automation rules and playbooks that can perform actions when alerts or incidents are created or updated. Microsoft gives the example of automatically isolating a compromised machine and blocking the affected account.

4. EDR automation

Endpoint detection and response (EDR) software monitors laptops, desktops, servers, and other endpoints for suspicious activity.

Automation within an EDR platform can take immediate action on the device itself. Common examples include terminating a malicious process, quarantining a file, collecting forensic information, running a script, or isolating a compromised endpoint from the network.

This makes EDR automation particularly useful for rapid containment.

Example: CrowdStrike Falcon. Falcon can isolate compromised hosts automatically, execute response commands and scripts, remove malicious files, terminate processes, and automate remediation workflows.

5. XDR automation

Extended detection and response (XDR) expands detection and response beyond the endpoint.

An XDR platform combines information from areas such as endpoints, identities, email, networks, cloud infrastructure, and applications. This lets the platform correlate activity across several parts of an attack rather than treating each alert independently.

Automation can then investigate or respond to activity using this wider context.

Example: Microsoft Defender XDR. Defender XDR includes automated investigation and response capabilities that can investigate detected threats and perform remediation actions across supported Microsoft security products.

6. Scripts and APIs

Some of the simplest SOC automations are custom scripts.

Python, PowerShell, and similar tools can automate repetitive tasks such as looking up an IP address, collecting endpoint information, updating a blocklist, querying a security product, or passing information from one system to another.

These automations can save analysts a lot of manual work and can be highly tailored to a particular environment.

The trade-off is maintenance. Someone has to build the script, test it, manage credentials and permissions, update it when APIs change, and troubleshoot it when something breaks.

Example: A Python script could take an IP address from an alert, query several threat intelligence services, add the results to the incident, and automatically flag known-malicious infrastructure for an analyst.

7. Security data pipelines

Security data pipelines automate a different part of security operations: managing security data before it reaches tools such as the SIEM.

A pipeline can automatically collect, parse, normalize, enrich, filter, transform, and route telemetry. This lets security teams control both the quality and volume of data moving through the SOC.

Rather than sending every log into an expensive SIEM, for example, the pipeline might send detection-critical data to the SIEM and route lower-value telemetry to cheaper storage.

This makes security data pipelines a form of SOC automation focused on the data feeding detection and investigation rather than the investigation itself.

Example: Realm Security. Realm sits between security data sources and destinations such as SIEMs, XDR platforms, data lakes, and AI SOC tools. It can normalize, enrich, filter, transform, and route security data before it reaches those systems.

SOC automation solutions are moving beyond predefined workflows

SOC automation itself is not new. Security teams have used scripts, SIEM rules, EDR response actions, and SOAR playbooks for years.

What is changing is how much of an investigation can be automated.

Traditional automation works particularly well when teams already know the exact steps that should happen like if X occurs, perform Y. Agentic security operations platforms extend that model to workflows where the path may change based on the evidence the system finds.

Legion Security, for example, describes an approach where the platform learns how analysts already investigate alerts, captures that process as an inspectable workflow, and then executes repeatable parts of the investigation across the tools the SOC already uses.

That points toward a different model for SOC automation. Instead of automating isolated tasks one by one, security teams can increasingly automate larger portions of the investigation process, leaving analysts to concentrate on exceptions, difficult cases, and decisions where human judgment carries the most value.