SIEM Log Management: Log Management in the Future SOC

What Is SIEM?

SIEM software solutions collect log data from multiple sources, such as applications and network hardware, and aggregate it into a centralized platform. They can perform correlation and real-time analytics to alert teams to indicators of compromise (IoCs), such as failed login attempts, letting them respond faster and more effectively to ongoing attacks.

SIEM tools combine the capabilities of Security Event Management (SEM), Security Information Management (SIM), and Security Event Correlation (SEC) into one solution.

What Is Log Management?

Log management refers to the entire process teams use to handle logs generated by the various applications in their IT environment.

Log management can be broken down into a series of independent subprocesses. It usually starts with collecting log data from a data source. The logs are then aggregated into a central location where they can be analyzed. In some cases, log data also needs to be transformed. This means that log data must be reorganized or decomposed to conform to the format standards used by the organization or to make them easier to parse. Logs can then be centrally analyzed or visualized.

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SIEMs vs. Log Management: Similarities and Differences

SIEM and log management share many similarities. Both work with logs from multiple systems, and use them to provide visibility into what is happening in the IT environment. You can use both of them to find issues in your environment and fix them, as well as audit and investigate historical issues. 

However, there are several key differences:

Purpose

• Log management systems are primarily used to collect log data in one place (regardless of the location or nature of the data). You can use generic log management systems for security, but it can be complex to process and analyze the data.
• SIEM systems are focused on security. They can capture secure-related data from a large and diverse IT ecosystem, including data from security tools, and automatically package them in a way security teams can use.

Automation

• Log management is typically not fully automated and does not perform real-time threat analysis. In addition, you must explicitly configure which information to collect, how to save logs, and where to store them.
• Modern SIEMs can perform real-time threat detection and analysis. SIEMs can automatically handle the log management lifecycle, identifying relevant information, processing and storing it automatically.

Central data management

• Log management collects data from system events and logs, but it takes some effort to organize the data into one, standardized data store.
• SIEM makes it easy to centralize your data. It collects logs and events from hundreds of organizational systems. Typically, each device generates events and collects them in flat log files or databases. The SIEM system can store the data (on-premises, in the cloud, or both), convert it to a standardized format, and index it for efficient analysis and exploration.

Compliance capabilities

• Log management tools do not have built-in compliance capabilities. Data security and privacy standards have specific requirements, and it can be difficult to meet them using an out-of-the-box log management system.
• Modern SIEM systems have compliance reporting capabilities. They have built-in reports in the specific format required by compliance standards. This makes SIEM an essential part of an organization’s compliance strategy. 

Threat detection

• Log management tools do not have the ability to intelligently analyze events to identify complex cyber threats. It is possible to identify simple security issues by defining notifications on obvious threat patterns, such as multiple login retries. 
• SIEM tools can identify and alert on cyber threats, even sophisticated threats that span multiple IT systems, or use evasion tactics to hide their tracks. By correlating multiple security events with known patterns of malicious behavior, SIEMs can identify many types of security events on corporate networks. Modern SIEMs also offer behavioral analysis based on machine learning to identify anomalous behavior that doesn’t match a known pattern.

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4 SIEM Log Management Best Practices

Log management is a core function of a security operations center (SOC). It involves defining the depth and scope of the SOC’s visibility. Effective log management is essential to enable fast detection and response and ensure compliance with regulatory requirements. It also facilitates audits and forensic analysis of security incidents.

The volume and variety of logs can be enormous in a modern, fast-paced business environment. The SOC can quickly accumulate massive log volumes, but not all logs are as important for cybersecurity. Log management helps define the logs and sources that you should prioritize. It also helps maintain the log collection infrastructure. 

Many companies prefer a SIEM platform over a standalone log management platform. It detects sophisticated threats with correlation rules, provides greater visibility over diverse technologies and networks, enables advanced data analytics, and maps log coverage to PCI-DSS, NIST, and MITRE ATT&CK frameworks.

Choose the Right Log Sources

SIEM engineers can collect log data from three types of sources:

• Security control systems—examples include an intrusion detection and prevention system (IPS), next-generation firewall (NGFW), web application firewall (WAF), security gateway, endpoint protection platforms (EPP), and web security controls.
• Network infrastructure—examples include DNS servers, DHCP servers, routers, and wireless infrastructure as well as public cloud access and applications.
• End-user applications and systems—examples include security event logs (Windows), operating system logs, PowerShell, sysmon, and custom application logs.

The SOC team chooses the log sources based on usage patterns, their impact on threat detection, coverage, auditing requirements, and adaptability to the organization’s log management platform.

Identify Requirements for Threat Detection and Log Management 

The most important step when using a SIEM for log management is to know your needs. Research the dynamic threat landscape to identify how adversaries might leverage new attack vectors and techniques to exploit security vulnerabilities. 

First, define your organization’s attack surface, security priorities, relevant threat types, and historical correlation requirements to enable threat hunting. Next, list the privacy and security regulations applicable to the organization to ensure compliance. You can use preparation lists to inform decisions about the volume of logs your store and manage. Leverage the MITRE ATT&CK framework to help plan your cybersecurity strategy.

Integrate SIEM with Your Log Sources and Optimize Log Levels

Some SIEM solutions require significant care and feeding to make the most of security log management. Eliminating blindspots should be the number one consideration when choosing a solution, because log visibility is critical to threat detection. Start by integrating your SIEM solution to minimize future issues with log management. 

Prioritize and integrate log sources and optimize log events based on the requirements established during integration testing. It is also important to define the rules for log failure alerts—define the frequency of log collection for important sources.

Continuously Improve Your Log Visibility with Threat Intelligence

Knowing the threat landscape is key to ensuring effective log visibility, but the modern cybersecurity landscape is constantly changing. Thus, it is important to have a continuous process for monitoring and administering SIEM in the face of visibility issues such as log failures, blind spots, and emerging threats. 

Blindly navigating your log management can result in delays and false negatives. An important best practice is to make informed assessments of the log management platform and data-driven security implementation decisions. Continuously evaluate your log visibility using automated and manual red-team approaches to identify and mitigate new security gaps—leverage automation to detect log failures and performance issues.

Learn more in our detailed guide to SIEM logging

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Security Log Management with Exabeam

Exabeam Security Log Management allows you to ingest, parse, store, and search log data at scale with a cloud-native data lake, hyper-quick query performance, and dashboarding across multi-year data. At its foundation are four key capabilities: cloud-scale visibility, comprehensive log collection, fast, intuitive search, and an automated investigation experience.

Cloud-scale visibility

Exabeam Security Log Management is the industry’s most advanced cloud-native solution for security use cases. A powerful user interface, allows you to onboard and monitor ingestion of on-premises or cloud data and build and monitor parsers, and visualize the data consumption and the health of every Exabeam service. Drive desired security outcomes to close critical gaps by understanding your data source coverage and configuration. Learn precisely what to do to improve your security posture by seeing recommended information, event streams, and parsing configurations that adapt to your organization’s needs.

Comprehensive log collection

The product securely ingests, parses and stores logs, and uses a new common information model (CIM), data enrichment using threat intelligence, and other context, to help create security events that identify named fields, and normalize them for accelerated analysis and added security context. A wizard enables custom parser creation from new or templated log sources, making it easy to develop, deploy, and manage error-free parsers.

• Support for 200+ on-premises products 
• Multiple transport methods: API, agent, syslog, SIEM data lakes 
• 34 cloud-delivered security products
• 11 SaaS productivity applications
• 21 cloud infrastructure products
• Over 8,000 pre-built log parsers
  

Fast, intuitive search capabilities

An essential capability of Exabeam Security Log Management is Search — a single interface that allows analysts to search across hot, warm, cold, and frozen data at the same speed. The time savings is valuable as investigations usually entail multiple queries and require that search terms be refined over multiple iterations to obtain the desired results. Search across real-time or historical data is also no longer a barrier. SOC teams do not have to import and wait for historical data to be restored and processed. And there’s no learning curve; analysts don’t need to learn a proprietary query language. Create powerful visualizations from your parsed log data quickly. Build a dashboard minutes from 14 different pre-built chart types, or generate them from search queries and correlation rules..

Automated investigation experience

Turn your searches into powerful threat-hunting rules in one click. Properly designed correlation rules enable enterprises to surface a broad range of abnormal behavior and events. To identify these anomalies, define conditions that function as triggers by comparing incoming events with predefined relationships between entities. Write, test, publish, and monitor custom correlation rules for your most critical business entities and assets, including defining higher criticality for those that correspond to Threat Intelligence Service-sourced activity. Add context enrichment to events from multiple commercial and open source threat intelligence feeds, which aggregate, scrub, and rank them, using proprietary machine learning algorithms to produce a highly accurate, up-to-date stream of IoCs.

See Exabeam in action: Request a demo