Sigma Rules Pushed as 'Write Once, Detect Anywhere' Standard
Security experts are advocating for wider adoption of Sigma, an open-source format for detection rules, to create vendor-agnostic security logic. The approach lets SOCs write a detection once and then convert it for use in Splunk, Sentinel, or other SIEMs, streamlining rule deployment in multi-client and hybrid environments.
Developed by Florian Roth and Thomas Patzke, Sigma was created to be a common language for security analysts, allowing them to share detection methods without being locked into a specific vendor's query language. This open-source project provides the specification for the YAML-based rule format, a converter for various SIEM platforms, and a large repository of community-contributed rules. The structure of a Sigma rule is designed for clarity and reusability, containing key sections like title, log source, detection logic, and optional fields for false positives and severity level. Many rules are also tagged with corresponding MITRE ATT&CK techniques, such as T1003 for credential dumping, which aids in mapping detections to specific adversary behaviors and tracking threat coverage. For Splunk engineers, tools like `sigmac` or web-based converters like Uncoder.io are used to translate these generic YAML rules into the Splunk Search Processing Language (SPL). Once converted, the SPL query can be directly used in Splunk's Search & Reporting app or saved as an alert to provide real-time notifications on detected threats. This methodology directly supports the implementation of the DoD's Zero Trust "User & Identity" pillar, which requires continuous verification and monitoring of user accounts. By deploying a rich library of Sigma rules focused on identity-based attacks—such as credential dumping, Kerberos manipulation, and suspicious access token usage—organizations can create high-fidelity alerts that signal potential compromises of user identity. To ensure these detections work effectively across diverse log sources, it is crucial to normalize data to Splunk's Common Information Model (CIM). The CIM provides a standardized set of fields and tags for different data types, such as authentication and network traffic, allowing the logic within a converted Sigma rule to function regardless of the original data source. The public Sigma repository contains a vast number of rules specifically designed to detect identity-centric threats. There are rules to identify attempts to dump credentials from memory using tools like Mimikatz, detect Kerberoasting attacks by spotting suspicious Kerberos ticket requests, and flag the creation of new user accounts on servers within an Active Directory environment, which should be a rare event. By operationalizing this flow—from community-sourced Sigma rules to CIM-compliant Splunk alerts—detection engineers can build a robust, vendor-agnostic defense against identity-based threats. This approach not only streamlines the onboarding of new log sources and clients but also directly maps to the control frameworks essential for demonstrating DoD Zero Trust compliance.
