This article initiates a series on the Open Cybersecurity Schema Framework (OCSF). Future articles will detail implementation strategies and specific use cases, offering insights into OCSF's role in security data management. This series is relevant for both security leadership assessing architectural decisions and engineers focused on data pipeline implementation.

——————

If you've been in security operations for any length of time, you know the drill. An alert fires. You check your SIEM. Then your EDR. Then those cloud logs that live in their own special universe. And somewhere in the middle of this investigation, you find yourself wondering why—in 2025—you're still manually translating between "user_name," "userid," and "account_identifier."

It's a problem as old as security tooling itself. Every vendor builds their logging format to suit their specific needs, which makes perfect sense from their perspective. This presents challenges for security analysts attempting to correlate disparate events, such as suspicious authentication attempts and network anomalies from different tools.

The typical enterprise runs somewhere between 45 and 75 security tools these days. Each one speaks its own dialect of security event language. We've gotten so used to this babel that we hardly question it anymore. We just budget for the translation work—about 23% of security engineering time, according to recent studies. Think about that. Nearly a quarter of your team's effort goes into making tools talk to each other, not actually finding threats.

Disparate security log formats incur significant costs; a recent IDC report estimated annual expenses for maintaining data integration at $1.2 to $2.1 million for a typical enterprise. This data heterogeneity also impacts threat detection speed, contributing to delays in response times.

Addressing the Challenge with OCSF

So what is OCSF, exactly? The Open Cybersecurity Schema Framework (OCSF) aims to address this data translation challenge through a standardized approach. It's a collaborative effort—AWS, Cisco, IBM, Splunk, and others came together to build on work that Broadcom had started with Symantec's ICD schema. The objective was to establish a common, open standard for security event data.

OCSF differentiates itself through its focused and incremental adoption model. It prioritizes common security events and supports mapping from existing vendor schemas, allowing for parallel or phased integration rather than requiring complete replacement. Vendors don't have to throw out their existing schemas—they can map to OCSF or support it alongside their native formats.

The framework itself is built around a few key concepts that work together to create a comprehensive but flexible system. Event Classes form the foundation—these are essentially templates for different types of security activities. When you're dealing with an authentication event, for instance, you'll always find the same fields in the same places: user information, source and destination endpoints, status codes. No more guessing games.

These Event Classes are organized into Categories—eight of them in the current version, covering everything from System Activity to Network Activity to Findings. It's a logical hierarchy that helps with data organization, but more importantly, it makes querying and partitioning data much more efficient.

Then there are Objects—reusable components that appear across different event types. A User object looks the same whether it's part of an authentication event or a file access log. This consistency streamlines data correlation and analysis. The same goes for Device objects, Process objects, File objects—all the entities that security events revolve around.

Profiles represent OCSF's approach to extensibility. These optional overlays add specialized attributes for specific use cases without modifying the core schema. Organizations can apply profiles to include cloud-specific metadata, compliance-related fields, or threat intelligence enrichment. Multiple profiles can be combined as needed, allowing the framework to adapt to diverse requirements while maintaining its standardized foundation.

The State of Adoption

Since its September 2023 release, OCSF has seen substantial adoption, with approximately a thousand contributors and 200 organizations reporting production deployments

AWS Security Lake is a notable example, automatically converting AWS service logs (e.g., CloudTrail, VPC Flow Logs, GuardDuty findings) into OCSF format and storing them as Parquet files. This combination of OCSF normalization with Parquet's columnar storage optimizes data for analytical workloads.

But it's not just AWS. Major security vendors like Datadog, SentinelOne, Rapid7, and Palo Alto Networks have implemented OCSF support. Some are using it as an export format, others as their native schema. The varied adoption patterns indicate the framework's adaptability to diverse operational requirements.

What's particularly interesting is how the framework has evolved based on real-world feedback. Version 1.5.0, the current release, reflects lessons learned from actual implementations. The community-driven development process ensures the schema's evolution is directly informed by practitioner requirements.

Governance and Evolution

The November 2024 transition to Linux Foundation governance was a significant milestone. For those who follow open source projects, this signals a certain maturity—the project has grown beyond what any single company can or should control. The Technical Advisory Committee now oversees development through a formal RFC process.

This governance structure promotes predictable, vendor-neutral evolution of the framework. Semantic versioning further supports stable adoption by indicating compatibility with future releases, which is critical for foundational data schemas.

Practical Considerations

If you're thinking about OCSF implementation, there are a few things to keep in mind. The core schema covers common security events quite comprehensively, but every organization has unique needs. The extension mechanism lets you add custom attributes while maintaining compatibility with the base schema. It's a good balance between standardization and flexibility.

The tooling ecosystem is also worth exploring. The schema browser at schema.ocsf.io is an excellent resource for understanding the framework's structure. There are validators to check your implementation, and a growing collection of mapping tools to help with migration.

Speaking of migration—it's not trivial. Organizations report spending 2 to 4 months on comprehensive implementations. That includes mapping existing data sources, updating detection rules, and training teams on the new schema. Unlike migrations to alternative proprietary formats, OCSF adoption offers the benefit of aligning with an open standard supported by a wide array of vendors.

Looking Ahead

OCSF provides a practical, vendor-neutral framework for data standardization in the security industry. While it does not address every data integration challenge, it represents a substantial advancement in current practices.

The framework's rapid adoption indicates it addresses an industry demand. Increased vendor support and organizational deployment are expected to generate network effects, as the value of a common schema enhances with broader adoption, reducing integration effort across the ecosystem.

OCSF presents a viable approach for security teams facing data integration complexities. Its practical framework can reduce the overhead of security data management, thereby potentially improving overall security effectiveness by simplifying analysis.

——————

In our next article, we'll dive into the technical details of OCSF's architecture. We'll explore specific event classes, walk through real mapping examples, and share practical tips for getting started with implementation. If you're ready to move beyond the theory, that's where we'll begin.