How to build a self-sustaining SOC strategy

Security leaders are in the tricky position of determining how much new AI-driven cybersecurity tools will actually benefit their security operations centers (SOCs). While the hype around generative AI is still everywhere, security teams must deal with reality: they are constantly bombarded with alerts from endpoint security platforms, SIEM tools, and phishing emails reported by internal users. They also face a severe talent shortage.

This guide provides actionable steps that organizations can take to further automate processes and build an autonomous SOC strategy, addressing the critical talent shortage on security teams. Employing artificial intelligence and machine learning in a variety of techniques, these systems simulate the decision-making and investigative process of a human analyst.

We’ll start by defining the goals of your Autonomous SOC strategy and looking at key processes that can be automated, then we’ll look at various AI and automation products, and finally, we’ll look at some examples of how these tools can be used as part of your Autonomous SOC strategy.

Autonomous SOC Strategy Goals

The goal of an autonomous SOC strategy is to automate every step of alert triage from start to finish, mitigating risk by independently investigating, triaging, and resolving. Raise as many alerts as possible without human intervention.

It’s important to set expectations here. The goal of an autonomous SOC strategy is not to replace all humans on your security team with AI technology. As with any comprehensive cybersecurity strategy, the bottom line is to protect your organization by incorporating “people, process, and technology.” No rational security professional believes you can remove humans from the equation.

An autonomous SOC acts like an additional team of Tier 1 or Tier 2 analysts, extending the capabilities and skills of the team. Systems should be designed to escalate significant threats to human analysts. An autonomous SOC: Work for peopleUsing technology that fits your processes makes your work easier and enhances your capabilities.

6 Key SOC Processes to Automate

First, you need to realize that every SOC is different (we’ll discuss automation tools in the next section). You need to consider the specific needs of your SOC and prioritize automating workflows that create bottlenecks or burden your team. Repetitive, time-consuming manual tasks are key opportunities to consider automating.

Here we describe six key SOC processes that provide an overview of what we call an autonomous SOC.

1. monitor – An autonomous SOC continuously monitors and collects alerts from integrated security tools 24/7, ensuring no potential threats are missed.
2. Gathering evidence – Upon receiving an alert, the Autonomous SOC collects all relevant data related to the alert, including evidence from files, processes, command lines, process arguments, URLs, IPs, parent and child processes, memory images, etc.
3. investigate – The Autonomous SOC uses AI and a variety of advanced techniques to analyze each piece of evidence collected, including sandboxing, genetic code analysis, static analysis, open source intelligence (OSINT), memory analysis, and reverse engineering. The results of these individual analyses are compiled into a holistic assessment of the entire incident using generative AI models.
4. Triage – The Autonomous SOC categorizes the risk associated with each alert and decides whether to escalate based on the findings. Additionally, the Autonomous SOC reduces noise by automatically remediating false positives in the detection system, which do not require any other action.
5. respond – Critical threats are immediately escalated to analysts. For every identified threat, the Autonomous SOC provides an assessment, recommendation, and creates a ticket in a case management system, including detection content and out-of-the-box hunting rules to guide the response process.
6. report – The autonomous SOC generates reports and provides information to the team with tuning suggestions, enabling continuous improvement of security operations.

These steps use technology to “autonomously” sift through alerts and escalate only those that truly require human analysis, allowing you to effectively manage high volumes of alerts and significantly reduce the time spent on false positives.

SOC automation tools for building an autonomous SOC

On a practical level, you need the right tools to execute your strategy. Let’s look at some of the key tools that you can integrate into your system to design a phased implementation plan.

1. SOAR ProductsIt’s a well-established product category, with many SOC teams using security orchestration, automation, and response (SOAR) tools to automate tasks. SOAR can be challenging because it typically involves advanced engineering and building complex playbooks. Some SOARs have recently integrated AI or offer pre-built playbooks and no-code tools that simplify automating some processes.
2. Autonomous SOC ProductsThis is an emerging product category that uses native automation workflows and AI to ingest, investigate, and triage alerts. The newest startups in this category launched in 2023 or 2024 using technologies based on generative AI. More mature autonomous SOC products have integrated generative AI, using it to complement core technologies such as genetic analysis and machine learning.
3. AI Co-Pilot Products: This is the newest category emerging in 2023. New “co-pilot” tools will use generative AI to assist analysts, allowing them to easily query systems for answers during investigations. These may integrate with other tools to accelerate incident response or even act autonomously, but it’s not clear how effective and popular these AI assistants will be.

Different environments require different tools, but adopting tools is becoming increasingly easier, allowing you to choose tools that work together. The security products you use should support integration with SOC automation tools, allowing you to automate the investigation and alert triage process for all types of alerts.

Three Different Examples of Autonomous SOC Strategies

Every security team and organization has different needs, so an autonomous SOC strategy needs to be adaptable. Here are some example autonomous SOC strategies to show how different types of security teams and organizations can implement them.

Example 1

Consider the following scenario: A SOC team already has SOAR that provides automation, but the alert triage workflow is not fully automated. Triage, investigation, and response are handled by a small in-house team of SOC analysts with the assistance of an outsourced managed security services provider. They want to improve their mean time to response because they are still doing a lot of manual tasks and have too many false positives. They don’t want to automate more processes by building and maintaining more complex incident response playbooks. They have decided to use an autonomous SOC platform that can integrate with their detection tools.

The diagram above shows the processes automated by the Autonomous SOC product, which will be a key part of this team’s strategy.

First, they integrate with their endpoint security product to monitor and triage alerts. They test the results and build confidence in the autonomous SOC system for endpoint alerts, and use SOAR for alert escalation and case management. This system ensures that endpoint alert triage times average less than two minutes. Once analysts are confident that the autonomous SOC process is effectively implemented, the team integrates the autonomous SOC product to also ingest and triage user-reported phishing emails and SIEM alerts.

Example 2

Now let’s look at a SOC team at a managed detection and response provider who believes adopting an AI-driven strategy will be a competitive advantage to enhance client services and increase revenue. They need to monitor and triage alerts from numerous clients who use different tools for detection and response.

The company decided to implement an autonomous SOC strategy that included the use of an autonomous SOC product that could integrate with all of their clients’ tools. This would allow them to efficiently monitor, investigate, and triage all alerts from multiple client environments, reducing triage time through AI and automation. By expanding their capabilities with AI and automation, the MSSP team could onboard additional clients and handle more alerts without facing the challenge of recruiting and hiring additional analysts. After implementing the autonomous SOC product, they could also expand their offerings to their clients and offer new services such as compensation for phishing emails reported by users.

Example 3

Now imagine an example of a SOC team that has established an autonomous SOC strategy: an autonomous SOC product investigates and triages alerts from integrated detection systems, and SOAR is used for escalation and case management. After these tools are fully implemented, the team adds an AI copilot to help the security team query for further information.

While this helps illustrate how these tools fit into different parts of the SOC, it’s not very realistic because tools like AI Copilot are so new that few teams are using them effectively yet.

Three Advantages of Autonomous SOC Products

The process of monitoring, investigating, and triaging alerts represents a huge opportunity for automation for many SOC teams. Because the alert triage process involves many repetitive and time-consuming tasks, streamlining this workload with an autonomous SOC product makes analysts more efficient and effective.

Autonomous SOC products offer an attractive option because they are built to be easy to deploy and integrate with other security tools, helping address challenges such as alert volume and staffing shortages.

These specialized products offer three key advantages:

1. Reduce risk by ensuring all artifacts and alerts ingested from integrated alert sources are comprehensively investigated and efficiently triaged.
2. Using AI automation to triage alerts and make decisions to resolve certain types of alerts helps analysts focus on real threats and prevents alert fatigue.
3. Escalate the most critical alerts through autonomous SOC processes and provide critical information to help analysts prioritize response to critical incidents.

Ultimately, artificial intelligence and automation can consolidate data sources and provide a unified, automated triage experience to enhance investigations, support analysts, and improve response times. Your autonomous SOC strategy should be designed to use these advanced technologies to support and extend the capabilities of your security teams.

About Intether

Intezer is a leading provider of AI-powered technology for autonomous security operations. Focused on innovation and quality, their Autonomous SOC platform is designed to investigate incidents, make triage decisions, and escalate findings for serious threats like a seasoned Tier 1 SOC analyst – but without the burnout, skills gap, and alert fatigue.

Intezer’s customers include Fortune 500 companies such as Adobe and Equifax, mid-market enterprises, and MSSPs who use Intezer’s Autonomous SOC platform to triage alerts and fully automate Tier 1 SOC processes.

Intezer was founded in 2016 with a mission to research and develop technology to help SOC teams that are overwhelmed with workload and alerts and understaffed. Its autonomous SOC platform was first released in 2022. Its core technology uses an artificial intelligence framework that incorporates machine learning, generative AI, and proprietary genetic analysis.

Want to learn more? Schedule a demo with Intezer to see the Autonomous SOC Platform in action.