Elastic Security: 1,300 SIEM rules and advanced tools for detection engineering
How to maximize protection with prebuilt rules, alert suppression and threat hunting
KEY TAKEAWAYS
- Elastic Security includes over 1,300 preconfigured SIEM rules and 70 machine learning jobs for threat detection
- Advanced features such as alert suppression and manual rule runs reduce alert fatigue and improve operational efficiency
- Prebuilt rules can be customized without duplication, maintaining automatic updates from Elastic
- Elastic Security supports various types of rules, including ES|QL, KQL, Lucene, and EQL, to cover different threat detection scenarios
- Building block rules (BBR) elevate atomic activity for threat hunting and influence entity risk scores
Elastic Security: advanced tools for detection engineering
Elastic Security introduces new features for detection engineering, offering advanced tools for managing and optimizing detection rules at scale. The platform aims to reduce alert fatigue and improve the security posture of organizations.
Quick Answer
- Elastic Security offers over 1,300 prebuilt detection rules for 54 different data sources
- Features include rule customization, alert suppression, and automatic case creation
- Supports various rule types: ES|QL, KQL, Lucene, EQL, and ML
- Rules are mapped to MITRE ATT&CK tactics and techniques
- Biweekly updates with side-by-side view of changes
New detection engineering capabilities
Among the most relevant innovations, the ability to modify the parameters of prebuilt rules without having to duplicate them stands out, maintaining compatibility with future updates. The prebuilt rules customization feature allows integrating local changes with updates received from Elastic.
The alert suppression feature helps reduce the volume of similar alerts, improving triage efficiency. This feature requires a Platinum license or higher. For Standard levels, the ability to manually run rules to test and evaluate alert quality over periods of up to 90 days past is available.
Advanced alert management
Security teams can now automatically create cases for Elastic Security alerts, facilitating investigations through aggregation capabilities that combine multiple alerts into a single case. This improved approach to alert management is particularly useful for companies needing an efficient managed Security Operations Center.
Prebuilt rules and MITRE ATT&CK mapping
Elastic Security provides over 1,300 prebuilt detection rules for 54 different data sources and more than 70 machine learning jobs, including trained models and anomaly detection jobs. The rules are mapped to MITRE ATT&CK tactics and techniques, offering detailed context for alert configuration and investigation.
The rules are constantly updated and optimized, with biweekly updates allowing you to view changes in a side-by-side view. This continuous update process is crucial for maintaining adequate NIS2 compliance and responding to threat evolution.
Building block rules and threat hunting
Some rules mark alerts as building blocks, used to elevate atomic activities for threat hunting purposes and influence entity risk scores. These rules do not appear in the default Alerts view but can be used to build more robust rules.
To delve into threat hunting techniques, you can consult the dedicated article and visit the hunting library in the detection rules repository. These resources are fundamental for companies seeking to improve their incident response and proactive detection capabilities.
Rule customization
The platform allows modifying prebuilt rules to adapt them to specific needs without having to duplicate them. Customized rules continue to receive updates from Elastic, with a curated update experience that allows integrating local changes with new versions.
This feature is particularly useful for organizations needing a customized MDR solution, allowing detection rules to be adapted to specific operational needs.
Expanding detection coverage with custom rules
In addition to prebuilt rules, Elastic Security offers the ability to create custom rules to cover specific use cases or particular technologies. Advanced correlation capabilities help identify threats and anomalies, improving overall detection capabilities.
Rules can be created using various types of detection logic, including ES|QL, KQL, Lucene, and EQL. Each type of rule is suitable for different detection scenarios, allowing security teams to build a customized and adaptable detection strategy.
Types of detection rules
Elastic Security supports various types of detection rules, each with specific characteristics. ES|QL rules allow writing flexible detection logic, while custom query rules are useful for detecting single events. Event correlation rules are ideal for detecting sequences of events and identifying anomalous behaviors.
Machine learning rules create alerts for anomalies and outliers identified with ML jobs, where severities exceed a predefined threshold. Threshold rules alert when the volume of aggregated events exceeds a specified threshold, while new terms rules detect new terms that were not seen before in a historical time range.
Indicator matching rules help detect matches between incoming threat intelligence and logs or logs with a predefined list of indicators. These features are essential for companies seeking to improve their breach remediation and threat detection capabilities.
Impact on the cybersecurity market
The introduction of these advanced features positions Elastic Security as an increasingly relevant player in the managed security landscape. According to the latest market analyses, the SOC as a Service sector is growing at a CAGR of 12.5%, with a projected value of $15.8 billion by 2027. Elastic's detection engineering capabilities could accelerate this growth, offering more sophisticated tools for alert management and reducing operational fatigue.
Benefits for companies with Platinum licenses
Organizations with a Platinum license can fully leverage the alert suppression features, significantly reducing background noise and improving operational efficiency. According to a recent study, 68% of security teams spend more than 50% of their time managing alerts, a problem that Elastic Security aims to mitigate with its new capabilities. For companies without a Platinum license, the ability to manually run rules to test and evaluate alert quality over periods of up to 90 days past still offers a valuable optimization tool.
Integration with other security tools
Elastic Security detection rules are designed to integrate seamlessly with other security tools, such as SIEM systems and Data Loss Prevention platforms. This integration is crucial for companies seeking to build a cohesive and interoperable security ecosystem. Elastic Security's advanced correlation capabilities allow identifying threats and anomalies more efficiently, improving overall detection capabilities.
Implications for regulatory compliance
Mapping rules to MITRE ATT&CK tactics and techniques provides detailed context for alert configuration and investigation, facilitating compliance with regulations such as the NIS2 regulation and the DORA regulation. Regulatory agencies are increasingly emphasizing the importance of a robust security posture, and tools like Elastic Security can help organizations demonstrate their compliance more effectively.
Implementation challenges
Despite the benefits, implementing these new features can present significant challenges. Customizing prebuilt rules requires advanced technical skills and a deep understanding of the organization's specific security needs. Additionally, managing biweekly updates and integrating local changes with new rule versions can be complex. Companies may need to invest in training or hire detection engineering experts to fully leverage these capabilities.
Advanced use cases
Elastic Security's threat hunting capabilities open new possibilities for organizations seeking to adopt a proactive approach to security. Building block rules, for example, can be used to elevate atomic activities for threat hunting purposes, influencing entity risk scores. This approach is particularly useful for companies operating in high-risk sectors, such as finance or healthcare, where the ability to detect and respond quickly to threats is critical.
Future trends in detection engineering
Future trends in detection engineering indicate a growing use of machine learning and artificial intelligence techniques to improve the accuracy and efficiency of threat detection. Elastic Security is well-positioned to leverage these trends, with more than 70 machine learning jobs already integrated into the platform. Organizations adopting these technologies will be better equipped to address emerging threats and improve their overall security posture.
Conclusion and forecasts
The new detection engineering features of Elastic Security offer advanced tools for managing and optimizing detection rules at scale. The capabilities of rule customization, alert suppression, and threat hunting significantly improve organizations' ability to detect and respond to threats. As the cybersecurity landscape evolves, tools like Elastic Security will become increasingly essential for companies seeking to maintain a robust and compliant security posture.
Looking ahead, detection engineering technologies are expected to continue evolving, with a growing focus on integrating machine learning and artificial intelligence techniques. Organizations adopting these technologies will be better positioned to address emerging threats and improve their detection and response capabilities. Elastic Security, with its advanced features and integration with other security tools, is set to play a key role in this evolving landscape.
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