Editor’s note: This is part three of a blog series detailing the technologies powering the ReliaQuest GreyMatter security operations platform and the future of security operations in general.

Introduction

In this ever-evolving security landscape, the only constant is change. To be successful, security operations programs must focus on consistency of both processes and outcomes. Data stitching allows security professionals to be more effective in how they detect, investigate, and respond to security incidents, but there are several critical components to data stitching which must be executed well. In this blog, we will define data stitching, explore its benefits, and review what’s needed to operationalize it.

What Is Data Stitching?

Data stitching is the process by which security data from various sources—such as SIEM, endpoint, network and cloud—is combined, normalized, and presented in a unified manner to streamline security operations. It provides analysts with highly contextualized information relevant to a security incident, rather than those individuals having to manually sift through different tools and data sets. Consisting of a flexible and adaptable framework, data stitching is capable of handling data from multiple sources while providing a uniform output. This uniformity is a critical aspect of security operations as it enables automation across the detection, investigation, and response lifecycle—the subject of the next blog in this series.

Data Stitching: The Solution to Dispersed Data

The increasingly fragmented nature of security poses a significant challenge for enterprises as they look to streamline their security operations program. While data has traditionally been centralized to a single repository, such as the SIEM, that model is no longer feasible due to cost and complexity. Critical sources of telemetry such as endpoint, network and cloud are now sitting outside the SIEM. As a result, organizations are now looking for ways to connect these disparate data sets . Leveraging data-stitching capabilities, like those found within the ReliaQuest GreyMatter security operations platform, you can effectively create a virtual data lake under which all of your security telemetry is available to query in near real time. By pulling together all data relevant to a security incident and normalizing it in a common format, analysts get the context they need to perform a comprehensive investigation—without having to manually pivot between various security tools. This reduction in high-time, low-brain activity leads to efficiency gains, potential cost savings, and improved DIR capabilities across disparate data sources.

3 Requirements for Effective Data Stitching

Of course, for effective data stitching, a few components need to be in place. For example, within ReliaQuest GreyMatter, you will need to have adaptable field mapping, a universal query language, and a normalized event model in order to get the most out of its data-stitching capabilities.

Adaptable Field Mapping

Every organization takes a unique approach to leveraging normalized fields within their security tooling. A security operations platform must support varied technologies including SIEM, EDR, NDR, and cloud while remaining flexible in how it handles the underlying data. To effectively perform this second layer of normalization via data stitching, field mapping needs to be configurable at both the customer and environment level. This ensures that the data fields within your security operations platform are uniform, regardless of the source from which the data was pulled. As a result, threat detections, investigations, and hunts can be rapidly deployed across a customer’s technology stack, including multi-cloud and multi-SIEM environments.

Universal Query Language

As organizations look to add or replace security technologies, one of the greatest challenges they face is the need to master these new tools and their various query languages. Every security tool handles its data differently, and every query language is uniquely structured. It quickly becomes impossible to remain proficient with every query language, particularly as your security tech stack is constantly growing and evolving. A major benefit of data stitching is the ability to remove this complexity and provide all the necessary data via a single, unified query language. Acting as an abstraction layer, the unified query language performs translations on your behalf. This allows you to move past the technology and focus on the security outcomes that matter most to you and your organization. GreyMatter uses its Universal Translator engine to accomplish this.

Normalized Event Model

A foundational component to data stitching is a well-defined and architected normalized event model. This model must be specific enough to perform complex queries against, while flexible enough to ingest data from all connected technologies. Once data is normalized, it becomes much simpler to perform enrichment against it. Additionally, it provides far more flexibility in how you ingest and store data. You may choose to send primary, actionable data to your SIEM while forwarding secondary, contextual data to a data lake. This will in turn lead to significant cost savings. Regardless of where the data resides, GreyMatter provides the ability to stitch it together in near real time.

Putting It All Together

Data stitching is a critical aspect of effective security operations, helping enterprises keep up with the rapidly changing cybersecurity landscape. It enables security professionals to focus on achieving optimal security outcomes rather than wrestling with technology complexities. Through adaptable field mapping, a universal query language, and a normalized event model, organizations can effectively streamline their security operations program. Data stitching within a security operations platform like ReliaQuest GreyMatter can empower organizations to better detect, investigate, and respond to security incidents.