Discover what sets the best SIEM tools apart. From understanding key features to evaluating top SIEM tools in the market, learn how to choose the best SIEM tool for your organization’s cybersecurity needs.
Welcome to the first installment of our two-part series on the best SIEM (Security Information and Event Management) tools and software. Today, we’re unpacking the essential evolution of SIEM technology and its role in cybersecurity. Our follow-up delves into comparisons of the generations of SIEM tools, guiding you toward the benefits of next-gen modern SIEM.
The Best SIEM Tools: What Separates Them from the Rest?
Historically, SIEM tools emerged as log management systems, but later evolved into powerful security hubs. They transformed cybersecurity by centralizing and analyzing data from across disparate environments and security tools, enabling real-time threat detection and incident response. Today, SIEMs continue to be crucial, offering advanced features like machine learning and user behavior analysis to identify sophisticated attacks, investigate potential breaches, and ensure compliance with regulations. This makes SIEM an indispensable shield in the ever-evolving cybersecurity landscape.
In this blog post, we give a brief overview of how SIEM tools originated and subsequently evolved; outline the three variations of tools on the market; and showcase the critical capabilities of the new standard for state-of-the-art SIEM tools. We provide relevant questions to help guide conversations with SIEM vendors.
Understanding SIEM Tools
SIEM is a software solution or system that provides real-time analysis of security alerts generated by various hardware and software within a network. SIEM collects and aggregates log and other relevant data generated throughout an organization’s technology infrastructure, including networks, servers, applications, and devices. It then uses this information to detect anomalies, identify and respond to security threats, and provide compliance reporting. SIEM systems typically offer features like log management, security event correlation, real-time monitoring, threat intelligence, and incident response. Modern era SIEM solutions use artificial intelligence and machine learning to automate many of the manual processes pertaining to threat detection, investigation, and incident response (TDIR).
For many organizations today, SIEM is a critical tool in terms of enterprise-wide log management, threat detection, and regulatory compliance monitoring. SIEM tools initially focused on collecting and storing IT security logs for auditing and regulatory needs. The market took off as government and industry regulatory requirements such as GDPR, HIPAA and PCI DSS mandated log management, making SIEM a crucial piece of any cybersecurity strategy.
Soon, SIEM capabilities expanded to enable efficient searching and analysis of this data, allowing security teams to quickly identify suspicious activity. This focus on data exploration fueled the next leap—the integration of threat detection features. By correlating events, spotting anomalies, and comparing against known threats, SIEMs transformed into foundational security solutions, laying the groundwork for the sophisticated threat detection systems we see today.
Breaking Down Different SIEM Tools
Just as cybersecurity needs have changed over the years, SIEM tools have undergone a fascinating evolution over the past two decades. There are three distinct generations of tools, defined according to their functionalities and capabilities.
First Generation SIEM
The first generation of SIEM tools, emerging around the mid-2000s, marked a significant shift in cybersecurity practices. These pioneering systems acted as central hubs for security event data, primarily focusing on log collection and compliance monitoring. Their primary use cases revolved around:
Meeting regulatory requirements
By consolidating logs from various systems and offering basic reporting features, SIEMs made compliance with industry regulations (for example, HIPAA, SOX/ISO) and industry data security standards (for example, PCI DSS) more streamlined.
Centralized log management
Replacing the hassle of managing individual logs from different devices, SIEMs provided a unified view, simplifying auditing and security investigations.
Basic security monitoring
Early SIEMs could trigger alerts based on predefined rules, flagging suspicious activities like login attempts from unusual locations or excessive failed logins.
While these tools ushered in a new era of centralized security management, they had limitations that became apparent as cyber threats grew more sophisticated. Their primarily rule-based detection generates false positives, overwhelming security teams with too many alerts. What’s more, many organizations write their own custom rules, which is a time-consuming effort that requires some knowledge of what threats they could face. Additionally, limited data analysis capabilities hamper these tools’ ability to identify complex attacks, and their lack of scalability hinders efficient log handling from rapidly expanding IT environments. Moreover, as data input grows, so do costs. These drawbacks paved the way for the development of the next generation of SIEMs, which were equipped with more advanced features to combat evolving threats.
Two example legacy products that originated in this era of SIEM software that are still on the market today are ArcSight, now offered by OpenText, and QRadar from IBM Security.
Second Generation SIEM
The second generation of SIEMs emerged around 2011, addressing the scalability limitations of their predecessors. Leveraging big data principles, they can handle massive volumes of logs, enabling organizations to ingest and analyze terabytes of security data daily. This empowered better search capabilities, allowing historical data analysis and quicker threat identification. Additionally, SIEM 2.0 introduced SOAR (Security Orchestration, Automation, and Response) capabilities, automating repetitive tasks like incident investigation and response, streamlining workflows for SOC teams.
SOAR
SOAR tools help integrate various security systems and automate tasks to improve the efficiency of security operations centers (SOCs).
While valuable for scaling and automation, SIEM 2.0 wasn’t without limitations. The sheer volume of data often created alert fatigue, with analysts overwhelmed by noise instead of focusing on real threats. Furthermore, while some SIEMs offered basic analytics, true threat detection and context-aware insights remained elusive. This led organizations to seek specialized tools for specific needs, for example, user and entity behavior analysis (UEBA), network traffic analysis (NTA), and endpoint detection and response (EDR).
UEBA
Some SIEM vendors attempted to provide these additional tools by acquiring a solution and bolting it onto the SIEM. For example, one SIEM vendor acquired a UEBA tool and offered it as part of the SIEM, but it remained a siloed tool with a separate user interface, making it awkward to use. It usually took the UEBA 60 to 90 days to create a baseline of normal activity for the organization and required constant manual re-tuning. It also added a lot of new alerts to triage due to alerting on individual anomalies, whether risky or not. Although the added tool improved the ability to ingest more data, it also led to an overload of data, high costs, and scalability and reliability problems, especially with search queries. The lesson here is, end customers need to look beyond the features checklist and understand how such features are implemented.
Network Traffic Analysis (NTA)
A security process that uses advanced analytics to monitor, capture, and analyze network traffic for the purpose of detecting and responding to malicious activities and potential threats.
Endpoint Detection and Response (EDR)
A cybersecurity solution that continuously monitors and gathers real-time data from endpoints to identify, investigate, and respond to potential threats.
Three companies that resemble this generation of SIEM are Splunk, LogRhythm, and Sumo Logic.
Third Generation SIEM
Third generation SIEM, also known as Next-Gen SIEM, signifies a revolutionary leap in security intelligence. Unlike its predecessors, Next-Gen SIEM transcends log aggregation and basic correlation, transforming into a true security nerve center. Its primary use cases revolve around three pillars:
Enhanced Threat Detection
Next-Gen SIEM leverages powerful AI and machine learning (ML) algorithms to analyze vast amounts of data from disparate sources, including logs, network traffic, endpoint activity, identity and user behavior. This comprehensive view, combined with threat intelligence feeds, allows for the detection of sophisticated attacks that might evade traditional signature-based methods.
Automated Response and Remediation
Armed with behavioral analytics and anomaly detection, Next-Gen SIEM can automatically trigger predefined actions when suspicious activity is identified. This can range from isolating compromised endpoints to blocking malicious traffic, thus significantly reducing response time and minimizing damage.
Improved Investigation and Forensics
By correlating events across various sources, Next-Gen SIEM provides a complete picture of an attack, aiding in faster root cause analysis. Its advanced search and query capabilities empower security analysts to more easily conduct in-depth investigations and identify the full scope of the breach armed with context.
Next-Gen SIEM’s overall effectiveness as a security system is driven by its cloud-native architecture. Unlike siloed, on-premise SIEMs, Next-Gen SIEM is built for scalability and elasticity, easily handling massive data volumes and dynamic workloads. It offers flexible deployment options, readily integrating with cloud-based security tools and facilitating centralized management.
Furthermore, the seamless integration of behavioral analytics and ML/AI sets Next-Gen SIEM apart. It can learn from historical data and user behavior, establishing baselines and identifying deviations that indicate potential threats. This proactive approach significantly outperforms basic rule-based detection, uncovering novel attack methods and zero-day exploits.
Three companies that clearly fall into the category of Next-Gen SIEM products are Gurucul, Securonix, and Exabeam.
Conclusion
In this initial part of our series on SIEM tools and software, we’ve explored the evolution and fundamental aspects of SIEM in cybersecurity. The forthcoming post will shift our focus to the most advanced features of SIEM tools, presenting a comprehensive comparison chart of the different generations. This analysis will help you understand the enhancements in SIEM technology over time and guide you in identifying the most suitable SIEM solution, equipped with advanced features, for your organization’s specific security requirements.