What Is SIEM? 7 Pillars and 13 Core Features [2025 Guide]

What is Security Information and Event Management (SIEM)?

SIEM stands for Security Information and Event Management. It’s a cybersecurity solution that aggregates and analyzes security data from various sources within an IT environment to detect, analyze, and respond to security threats in real time. SIEM solutions help organizations improve their security posture by providing a centralized view of security events, enabling faster threat detection and response.

SIEM systems collect log data from endpoints, servers, applications, firewalls, Identity solutions, email security, and other sources, helping security teams identify suspicious events and investigate potential threats. By offering real-time monitoring, SIEMs can alert security teams to anomalies or incidents and provide critical insights for remediation.

Here are some of the key aspects of SIEM:

• Data aggregation: SIEM collects and consolidates log data and event information from diverse sources like network devices, servers, applications, and security tools.
• Correlation and analysis: SIEM analyzes the collected data to identify patterns, detect anomalies, and correlate events to reveal potential security threats. 
• Data storage: A SIEM acts as a system of record for security operations, storing log data and other information useful for security analysis and incident response.
• Threat detection: By analyzing data and applying predefined rules and user and etity behavior analytics (UEBA), SIEM can identify suspicious activities, security breaches, and other potential threats. 
• Incident response: SIEM solutions can trigger alerts, generate reports, and automate certain actions to help security teams respond to security incidents. 
• Real-time monitoring: SIEM provides continuous, real-time monitoring of security events, allowing for immediate detection of potential threats and rapid response. 
• Historical analysis: SIEM also enables historical analysis of security data, allowing organizations to investigate past incidents, identify trends, and improve security measures.
• Security automation: Modern SIEMs include advanced features like user and entity behavior analytics (UEBA) and security orchestration and automated response (SOAR), making them useful tools for automating security operations centers (SOCs).

Benefits of using SIEM include:

• Improved threat detection: SIEM enhances the ability to detect security threats and vulnerabilities faster and more efficiently. 
• Centralized security view: SIEM provides a unified view of security events across the entire IT infrastructure, simplifying security management. 
• Enhanced incident response: SIEM enables faster and more effective incident response by providing real-time alerts and automated actions. 
• Compliance: SIEM can help organizations meet regulatory compliance requirements by providing audit trails and reporting capabilities. 
• Increased security posture: SIEM strengthens the overall security posture of an organization by providing continuous monitoring, threat detection, and incident response capabilities.

State of the SIEM Market

SIEM technology has undergone significant evolution since its introduction by Gartner in 2005. Originally developed as a combination of Security Information Management (SIM) and Security Event Management (SEM), SIEM has transformed into a critical tool for Threat Detection, Investigation, and Response (TDIR). 

Today, in addition to providing security event correlation and real-time analysis, SIEM systems assist in comprehensive cybersecurity management, control, and compliance.

The SIEM market is experiencing rapid growth. Market size was estimated at $4.4 billion in 2023 and is expected to reach $11.6 billion in 2030 with a compound annual growth rate (CAGR) of 14.5%. Several factors contribute to this growth:

• Increasing cybercrime: As the scale and scope of cyberattacks continue to rise, the need for robust threat detection becomes more pressing. SIEM systems are a core infrastructure for detecting, investigating, and responding to security incidents.
• IT service expansion: With more organizations relying on real-time data processing, the demand for comprehensive security solutions has escalated. SIEM technology is key to managing and analyzing this increased volume of data.
• Complex IT ecosystems: The growing adoption of cloud infrastructure presents new challenges in securing IT environments. SIEM solutions are indispensable for managing the complexity and scale of modern, multi-cloud, and hybrid IT ecosystems.

How Does SIEM Work? 7 Pillars of Modern SIEM Systems

In the past, SIEMs required meticulous management at every stage of the data pipeline, data ingestion, policies, reviewing alerts, and analyzing anomalies. Increasingly, SIEMs are getting smarter at pulling data together, from more organizational sources, and using AI techniques to understand what type of behavior constitutes a security incident.

1. Data aggregation

Most SIEM systems collect data by deploying collection agents on end-user devices, servers, network equipment, or other security systems like firewalls, email, identity, and EDR, or via protocols syslog forwarding, SNMP, or WMI. Modern SIEMs can integrate with cloud services to obtain log data about cloud-deployed infrastructure or SaaS applications, and can easily ingest other non-standard data sources.

Pre-processing may happen at edge collectors, with only some of the events and event data passed to centralized storage.

2. Correlation and analysis

The central purpose of a SIEM is to pull together all the data and allow the correlation of logs and events across all organizational systems.

An error message on a server can be correlated with a connection blocked on a firewall, and a wrong password attempted on an enterprise portal. Multiple data points are combined into meaningful security events, and delivered to analysts by notifications or dashboards.

3. Data storage

Traditionally, SIEMs relied on storage deployed in the data center, which made it difficult to store and manage large data volumes.

As a result, only some log data was retained. Next-generation SIEMs are built on top of modern data lake technology such as Amazon S3 or Elasticsearch, allowing nearly unlimited scalability of storage at a low cost. This makes it possible to retain and analyze 100% of log data across even more platforms and systems.

4. Threat detection

SIEM systems detect threats by analyzing event data using predefined correlation rules, statistical models, and machine learning algorithms. They identify suspicious patterns, such as repeated failed logins, privilege escalations, or unusual data transfers, which may indicate brute-force attacks, insider threats, or malware activity. Advanced SIEMs also use threat intelligence feeds to match internal events against known indicators of compromise (IOCs).

Modern SIEMs incorporate user and entity behavior analytics (UEBA) to establish baselines of normal activity and flag deviations in real time. This enables detection of sophisticated attacks like lateral movement or zero-day exploits that may bypass traditional signature-based detection methods.

5. Incident response

Once a threat is detected, SIEM platforms can initiate incident response workflows to contain and mitigate the impact. This includes automated actions like disabling user accounts, blocking IP addresses, or isolating compromised endpoints. Integration with security orchestration, automation, and response (SOAR) tools enhances this capability, allowing playbooks to guide response efforts.

Analysts can use SIEM dashboards and reports to investigate incidents, perform root-cause analysis, and document response steps. This accelerates mean time to detect (MTTD) and mean time to respond (MTTR), critical metrics for minimizing breach damage.

6. Real-time monitoring

SIEMs provide continuous monitoring by collecting and analyzing log data in near real time. Security teams receive alerts for high-priority incidents within seconds, enabling proactive defense against fast-moving threats like ransomware. Dashboards visualize live event streams, highlighting critical issues across networks, endpoints, and cloud services.

Real-time monitoring also supports compliance requirements by ensuring that security events are tracked and addressed as they occur. It enables organizations to identify gaps in security coverage and improve visibility across hybrid IT environments.

7. Historical analysis

SIEM platforms store large volumes of historical data, enabling forensic investigations of past incidents. Analysts can reconstruct attack timelines, trace lateral movement, and identify compromised assets. This is essential for understanding the full scope of breaches and preventing recurrence.

In addition, historical analysis helps in identifying long-term trends and recurring patterns of suspicious activity. Organizations can use these insights to fine-tune detection rules, strengthen security controls, and produce compliance reports for audits.

5 Key Benefits of SIEM

SIEM combines two functions: security information management and security event management. This combination provides real-time security monitoring, allowing teams to track and analyze events and maintain security data logs for auditing and compliance purposes.

1. Improved Threat Detection

SIEM solutions enhance threat detection by correlating events from multiple sources to identify complex attack patterns. They combine rule-based detection, threat intelligence feeds, and anomaly detection techniques to catch known and unknown threats, including advanced persistent threats (APTs) and insider attacks.

By leveraging machine learning and behavior analytics, modern SIEMs can flag subtle deviations from normal activity, such as lateral movement or data exfiltration, that traditional tools often miss. This allows organizations to detect and address threats earlier in the attack lifecycle.

2. Centralized Security View

A SIEM provides a unified platform for monitoring security events across on-premises systems, cloud environments, and remote endpoints. This centralization eliminates blind spots and improves visibility into the entire IT ecosystem.

Security teams can monitor all activity through a single dashboard, simplifying investigations and reducing the complexity of managing multiple point solutions. Consolidated logs and events enable more efficient correlation and threat hunting.

3. Enhanced Incident Response

With SIEM, organizations can automate responses to security incidents, such as blocking malicious IP addresses or disabling compromised user accounts. This automation reduces response times and limits the potential damage of attacks.

Integrated incident management workflows and playbooks guide analysts through triage, investigation, and remediation. This ensures consistent and effective handling of incidents, even in environments with limited cybersecurity staff.

4. Compliance

SIEM platforms simplify compliance by collecting, storing, and reporting on security event data in line with regulatory requirements such as GDPR, HIPAA, and PCI DSS. They provide predefined templates and audit trails to demonstrate adherence during assessments.

Log retention and searchable archives enable organizations to respond quickly to auditor requests and reconstruct incidents for forensic investigations, which is critical for maintaining regulatory certification.

5. Increased Security Posture

By providing continuous monitoring and actionable insights, SIEM strengthens an organization’s overall security posture. Security teams can proactively identify vulnerabilities, misconfigurations, and emerging threats before they escalate.

The ability to analyze both real-time and historical data allows organizations to refine their security policies and adapt to evolving attack techniques. This ongoing improvement reduces risk exposure and increases resilience against cyberattacks.

14 Core SIEM Features

1. Alerting – Analyzes events and helps escalate alerts to notify security staff of immediate issues, either by email, other types of messaging, or via security dashboards.
2. Dashboards and Visualizations – Creates visualizations to allow staff to review event data, see patterns, and identify activity that does not conform to standard processes or event flows.
3. Compliance – Automates the gathering of compliance data, producing reports that adapt to security, governance and auditing processes for standards like HIPAA, PCI/DSS, HITECH, SOX, and GDPR.
4. Retention – Stores long-term historical data to enable analysis, tracking, and reporting for compliance requirements. Especially important in forensic investigations, which can occur long after the fact.
5. Threat Hunting – Allows security staff to run queries from multiple sources via SIEM data, filter and pivot the data, and proactively uncover threats or vulnerabilities.
6. Incident Response – Provides case management, collaboration, and knowledge sharing around security incidents, allowing security teams to quickly synchronize on the essential data, communicate, and respond to a threat.
7. SOC Automation – Integrates with other security solutions using APIs, and lets security staff define automated playbooks and workflows that should be executed in response to specific incidents.
8. User and entity behavior analytics (UEBA) – Goes beyond rules and correlations, leveraging AI and deep learning techniques to look at patterns of human behavior. This can help detect insider threats, targeted attacks, and fraud.
9. Security orchestration and automation response (SOAR) – Advanced SIEMs integrate with enterprise systems and automate incident response. For example, the SIEM may detect an alert for ransomware and perform containment steps automatically on affected systems, before the attacker can encrypt the data, while simultaneously creating communications or other notifications.
10. Complex threat identification – Correlation rules can’t capture many complex attacks, because they lack context, or can’t respond to new types of incidents. With automatic behavioral profiling, SIEMs can detect behavior that suggests a threat.
11. Detection without rules or signatures – Many threats facing your network can’t be captured with manually-defined rules or known attack signatures. SIEMs can use machine learning to detect incidents without pre-existing definitions.
12. Lateral movement detection – Attackers move through a network by using IP addresses, credentials, and machines, in search of key assets. By analyzing data from across the network and multiple system resources, SIEMs can detect this lateral movement.
13. Automated incident response – Once a SIEM detects a certain type of security event, it can execute a pre-planned sequence of actions to contain and mitigate the incident. SIEMs are becoming full security orchestration and automation response (SOAR) tools.
14. Agentic AI Assistance – Provides analysts with an embedded AI assistant that helps guide investigations, automates follow-up actions, and brings together relevant context from across the platform. This capability reduces manual work by correlating events, identifying anomalies, and suggesting next steps. It speeds up threat triage and supports more consistent and effective responses across the security operations center.

The Role of AI in Modern SIEM

AI improves modern SIEM systems by automating critical processes like data aggregation, normalization, and enrichment. It collects security data from diverse sources and converts it into a standardized format for consistent analysis. By enriching this data with external threat intelligence, AI provides context that helps distinguish between normal events and potential threats, reducing false positives and improving detection accuracy.

Machine learning enables AI-driven SIEM to analyze historical data, establish behavioral baselines, and identify anomalies that indicate suspicious activity. Unlike traditional rule-based detection, AI can detect complex attack patterns and subtle deviations, such as abnormal login behavior or unusual data transfers, which could signal insider threats or compromised accounts.

AI also automates incident response by triggering predefined actions, such as isolating affected devices or blocking malicious traffic. Additionally, AI can analyze past incidents and attack patterns to predict future threats, allowing organizations to proactively address vulnerabilities and reduce security risks.

Tips from the expert

Steve Moore is Vice President and Chief Security Strategist at Exabeam, helping drive solutions for threat detection and advising customers on security programs and breach response. He is the host of the “The New CISO Podcast,” a Forbes Tech Council member, and Co-founder of TEN18 at Exabeam.

In my experience, here are tips that can help you better implement and maximize the effectiveness of your SIEM solution:

Adopt behavioral baselines incrementally
Start small when building behavioral baselines for UEBA functionality. Introduce profiles for high-priority entities first (e.g., privileged accounts or critical servers) before scaling to broader environments.

Prioritize log source optimization
Ensure the right log sources are integrated with your SIEM, and validate their configurations periodically. Misconfigured log sources can lead to missed detections or noisy, irrelevant alerts.

Focus on data normalization early
Before feeding data into your SIEM, implement strong normalization processes to ensure data is consistent and comparable. This reduces correlation errors and enhances detection capabilities.

Implement custom alert tuning
Generic SIEM rules often generate high false positive rates. Tailor alerts to your organization’s specific infrastructure, known risks, and operational baselines to improve accuracy.

Leverage threat intelligence integration
Enrich SIEM data with threat intelligence feeds, focusing on those relevant to your industry and geography. This contextualizes alerts and enhances the ability to detect emerging threats.

Monitor SOAR playbook performance
Periodically audit automated workflows to ensure they remain effective and aligned with new threats or operational changes. Poorly maintained playbooks can inadvertently delay responses or escalate false positives.

Common SIEM Integrations

SIEM systems integrate with a wide array of security tools and technologies to enhance threat detection, incident response, and overall security management. These integrations allow SIEMs to aggregate data from various sources and automate responses, making them a cornerstone of modern security operations.

1. Threat Intelligence Platforms (TIPs)
Integrating SIEM with threat intelligence platforms allows organizations to enrich their data with external threat feeds, providing context to detected events. This helps in identifying emerging threats and correlating internal activity with known attack patterns or indicators of compromise (IOCs). Threat intelligence integration improves the accuracy of detections and reduces false positives.

2. Security Orchestration, Automation, and Response (SOAR)
SIEMs often integrate with SOAR platforms, or have their functionality built in in order to automate incident response workflows. This integration allows for a more rapid and coordinated response to security incidents. For example, upon detecting a malicious activity, the SIEM may trigger the SOAR system to contain the threat by isolating affected endpoints, blocking malicious IP addresses, or executing remediation actions without human intervention.

3. Endpoint Detection and Response (EDR) and Extended Detection and Response (XDR)
Integration with EDR solutions enables the SIEM to gather detailed endpoint data. This enhances the SIEM’s ability to detect threats on individual devices, providing a more granular view of potential attacks. By correlating endpoint data with other network-wide event data, SIEMs can detect lateral movement or uncover advanced persistent threats (APTs) that would otherwise go unnoticed.

Extended Detection and Response (XDR) platforms, often built on top of EDRs, unify detection and response across endpoints, networks, and cloud workloads, often with a strong emphasis on automating response actions at the endpoint level. While XDR may serve as a reasonable option for teams lacking SOAR capabilities, it does not replace the broader visibility, analytics, and workflow automation provided by an integrated SIEM and SOAR stack.

4. Network Detection and Response (NDR) and Network Traffic Analysis (NTA)

Organizations seeking deep visibility into network activity can choose between Network Detection and Response (NDR) platforms or Network Traffic Analysis (NTA) solutions integrated with a SIEM.

NDR tools offer advanced threat detection by combining full-packet inspection, enriched flow data, machine learning, and automated response capabilities. Purpose-built for detecting lateral movement, command-and-control activity, and stealthy attacks, NDR solutions add behavioral analytics and real-time threat mitigation to security stacks.They may be ideal for those that do not have SIEM and SOAR functionality – similar to the need for XDR. 

NTA solutions, when paired with a modern SIEM, offer a cost-effective and scalable alternative. By analyzing traffic patterns and forwarding key telemetry into the SIEM, NTA delivers critical insights into anomalies and potential threats. Combined with a SIEM’s correlation, investigation, and response workflows, this pairing provides a practical path to network-layer threat detection without the complexity or cost of a standalone NDR. For many teams, this approach balances performance with budget, enabling strong network visibility and response across hybrid environments.

5. Identity and Access Management (IAM)
Integrating SIEM with IAM solutions helps monitor and manage user access and authentication data. This integration allows SIEMs to detect unauthorized access attempts, privilege escalation, and potential insider threats by analyzing user behavior and login patterns. By incorporating IAM data, SIEMs ensure that only authorized users have access to critical systems and data.

6. Cloud Security Tools
As organizations increasingly move to the cloud, integrating SIEM with cloud security tools is vital. These integrations enable the SIEM to gather security logs and data from cloud services such as AWS, Azure, and Google Cloud. This ensures that cloud infrastructures are monitored for suspicious activities and compliance with security policies.

7. Vulnerability Management Systems
SIEMs can be integrated with vulnerability management tools to provide insight into the risk profile of systems and applications. This integration allows for the correlation of detected vulnerabilities with active security events, helping prioritize remediation efforts based on real-time threats.

8. Firewall and Intrusion Detection Systems (IDS)
Firewalls and IDS solutions are primary data sources for SIEMs, providing real-time logs about network traffic, blocked connections, and potential intrusion attempts. By integrating these systems, SIEMs can correlate network activity with other events to detect coordinated attacks, such as denial-of-service (DoS) attacks or advanced persistent threats (APTs).

These integrations enable a SIEM to function as a central hub for security data, providing a comprehensive view of an organization’s security posture and enhancing the ability to detect, investigate, and respond to threats quickly and effectively.

Comparing SIEM vs. Other Cybersecurity Solutions

UEBA vs. Rule-Based SIEM

User and entity behavior analytics (UEBA) and security information and event management (SIEM) are complementary tools in modern cybersecurity. Most modern SIEM solutions include UEBA technology.

Focus on Behavior vs. Events:
UEBA specializes in monitoring and analyzing user and entity behavior to detect anomalies that might indicate insider threats, account compromise, or targeted attacks. It builds profiles over time and flags deviations from normal behavior. A rule-based SIEM only focuses on event data, collecting logs from various systems, correlating them, and applying rules to identify security incidents. Some SIEM vendors who do not have a mature UEBA will often market the number of rules, where for those that are good at it, reduce that overall figure to reduce false positives and complexity. 

Detection Without Rules:
Rule-Based SIEM systems rely heavily on predefined rules and correlation logic. UEBA, however, uses machine learning and advanced analytics to detect threats without needing specific rules or known attack signatures. This makes UEBA particularly effective against novel or sophisticated attacks that evade traditional SIEM detection.

Complementary Use:
Modern SIEMs often incorporate UEBA functionality as part of their capabilities. UEBA enhances SIEM by providing insights into behavioral anomalies, while SIEM provides the infrastructure for log management, data correlation, and incident response. Together, they offer a holistic approach to threat detection and response.

SIEM vs. SOAR

Security information and event management (SIEM) and security orchestration and automation response (SOAR) serve distinct roles in cybersecurity, though many modern SIEM solutions include SOAR technology.

Data Aggregation vs. Automation:
SIEM systems are primarily designed for collecting, storing, and analyzing security data from across the organization. Their main purpose is to detect threats and provide alerts. SOAR, in contrast, focuses on automating and orchestrating responses to incidents, streamlining workflows, and reducing the time to contain and mitigate threats. Today, look for SOAR functionality within your SIEM for best results.

Incident Response:
While SIEM alerts analysts about potential security events, SOAR takes it further by executing automated playbooks to respond to incidents. For example, upon detecting a malware infection via the SIEM, a SOAR system might automatically isolate the infected system, notify stakeholders, and update firewall rules.

Integration:
SOAR platforms are designed to integrate with SIEMs and other security tools. They use SIEM data as an input, enriching it with threat intelligence and automating response actions. This integration enables organizations to scale their security operations, reducing the reliance on manual processes.

SIEM vs. XDR

Security information and event management (SIEM) and extended detection and response (XDR) are both solutions for threat detection and response, but they differ in scope and architecture.

Breadth vs. Depth:
SIEM systems are designed to aggregate and correlate data from a wide range of sources across the organization, such as servers, firewalls, and endpoints. XDR, on the other hand, focuses on integrating and optimizing detection and response capabilities across specific environments, like endpoints, networks, and cloud workloads.

Data Correlation:
SIEM relies on rules, correlation logic, and machine learning to detect security events. XDR goes a step further by natively integrating data from a vendor’s suite of security tools, enabling deeper context and more precise detection. This native integration reduces the complexity of managing multiple tools and ensures better visibility across key attack surfaces.

Operational Complexity:
Traditional rule-based SIEM systems often require significant configuration and tuning to be effective. XDR, being vendor-specific, typically offers faster deployment and simplified operations, but it may lack the flexibility to incorporate third-party tools or custom data sources that SIEM can handle.

SIEM Use Cases

Security monitoring

SIEMs help with real-time monitoring of organizational systems for security incidents. A SIEM provides a unique perspective on security incidents because it has access to multiple data sources — for example, it can combine alerts from an intrusion detection system (IDS) with information from an antivirus (AV) product and authentication logs. It helps security teams identify security incidents that no individual security tool can see, and helps them focus on alerts from security tools that have special significance.

Advanced threat detection

SIEMs can help detect, mitigate, and prevent advanced threats, including:

• Malicious insiders – A SIEM can use browser forensics, network data, authentication, and other data to identify insiders planning or carrying out an attack.
• Data exfiltration (sensitive data illicitly transferred outside the organization) – A SIEM can pick up data transfers that are abnormal in their size, frequency, or payload.
• Outside entities, including advanced persistent threats (APTs) – A SIEM can detect early warning signals indicating that an outside entity is carrying out a focused attack or long-term campaign against the organization.

Forensics and incident response

SIEMs can help security analysts determine that a security incident is taking place, triage the event, and define immediate steps for escalation and remediation.

Even if an incident is known to security staff, it takes time to collect data to fully understand the attack and stop it — the SIEM can automatically collect this data and significantly reduce response time. When security staff discovers a historic breach or security incident that needs to be investigated, SIEMs provide rich forensic data to help uncover the kill chain, threat actors, and mitigation.

Compliance reporting and auditing

SIEMs can help organizations prove to auditors and regulators that they have the proper safeguards in place and that security incidents are known and contained.

Many early adopters of SIEMs used it for this purpose:  aggregating log data from across the organization and presenting it in audit-ready format. Modern SIEMs automatically provide the monitoring and reporting necessary to meet standards like HIPAA, PCI/DSS, SOX, FERPA, and HITECH.

SIEM Implementation Best Practices

Inventory Data Sources

Before implementing a SIEM solution, create a comprehensive inventory of data sources across your IT environment. Include all systems that generate logs, such as servers, endpoints, firewalls, routers, IDS/IPS systems, and cloud services. Don’t forget SaaS applications, databases, and specialized systems such as OT/IoT devices, which often generate valuable security data.

For each data source, identify what types of logs it produces (e.g., access logs, error logs, authentication attempts) and how they align with your security objectives. Ensure the data can be ingested via supported protocols such as syslog, SNMP, WMI, or APIs. Mapping out these sources not only ensures comprehensive coverage but also helps identify and eliminate blind spots, which attackers often exploit.

Plan for Scalability

A SIEM implementation needs to be future-proof, able to handle increasing volumes of log data and a growing number of integrated systems. Choose a platform that supports elastic storage, such as cloud-native data lakes or hybrid setups, so you can manage both current and future needs. Scalability planning is particularly critical for organizations with aggressive expansion plans or those operating in rapidly growing environments like cloud and IoT.

In addition to storage, consider the processing capacity of the SIEM. As log ingestion grows, ensure that the system can maintain real-time analysis and alerting without delays. Discuss scalability plans with the vendor to understand limitations and costs. Planning for scalability upfront reduces the likelihood of system slowdowns or costly upgrades as your organization evolves.

Deploy in Phases

Implementing a SIEM across an entire organization in one go can overwhelm both the security team and the system itself. Instead, adopt a phased approach to minimize risk and disruption. Begin by focusing on critical systems, such as those that house sensitive data, support business-critical processes, or face the highest risk of attack.

Test the SIEM with these systems, refining log collection, correlation, and alerting as you go. Use insights from the initial phase to improve processes before rolling out to additional systems. This iterative approach allows you to identify and resolve issues early, fine-tune configurations, and build confidence in the system’s effectiveness without overwhelming the security team.

Establish Roles and Processes

A SIEM is only as effective as the team operating it. Define roles and responsibilities within your security operations center (SOC) to ensure accountability and streamline workflows. Typical roles might include log management specialists, security analysts, incident responders, and compliance auditors. Assign clear ownership for activities like monitoring alerts, creating rules, and maintaining the system.

In addition, develop and document standard operating procedures (SOPs) for common tasks, such as triaging alerts, escalating incidents, and responding to specific threat scenarios. Regularly train your team on using the SIEM platform and analyzing its outputs. With well-established roles and processes, you can improve efficiency, reduce response times, and ensure a consistent approach to security.

Plan for Compliance

Compliance is a significant driver for many organizations adopting SIEM solutions. To make compliance easier, map regulatory requirements to SIEM capabilities, such as log collection, retention policies, and reporting. Identify which data sources are relevant to specific standards like PCI DSS, HIPAA, GDPR, or SOX, and configure the SIEM to gather and retain logs accordingly.

Automate the generation of compliance reports that highlight metrics such as access logs, failed login attempts, and policy violations. Schedule periodic reviews of the SIEM’s compliance settings to ensure they remain up-to-date with regulatory changes. Additionally, use the SIEM to track and document incident response activities, as these are often subject to audit requirements. Effective compliance planning not only simplifies audits but also helps demonstrate a proactive approach to regulatory obligations.

Exabeam Fusion SIEM

Exabeam Fusion SIEM is a cloud-delivered solution that combines SIEM with UEBA, SOAR, and full-spectrum TDIR in an AI-driven platform. At the core of Fusion SIEM is Exabeam Nova, a multi-agent AI system that automates the entire detection, investigation, and response lifecycle. Nova accelerates triage with behavioral analytics, guides analysts with threat timelines, and provides executive-level summaries to help leaders track posture and prioritize improvements. Fusion SIEM simplifies security operations with pre-packaged use cases, prescriptive workflows, and guided search—helping organizations reduce alerts by up to 60%, cut investigation time by 80%, and respond to incidents up to 50% faster than with legacy tools. With scalable cloud-based log storage, seamless integration, and comprehensive compliance reporting, Fusion SIEM delivers the speed, context, and efficiency required for modern security teams. 

With Fusion SIEM you can:

• Use threat detection events, investigation, and response from multiple tools
• Collect, search, and enhance data from anywhere
• Detect threats missed by other tools through UEBA analytics 
• Achieve successful outcomes with prescriptive, threat-centric use case packages
• Enhance productivity and reduce response times with Exabeam Nova, the onboard Agentic AI
• Measure security coverage, identify gaps, and prioritize improvements with Outcomes Navigator
• Meet regulatory compliance and audit requirements with ease

Read the Gartner Report

Gartner^® Magic Quadrant™ for SIEM | 2024

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How Does SIEM Work? 7 Pillars of Modern SIEM Systems

5. Incident response

 

 

 

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How Exabeam Fusion Works

Data from anywhere enhances visibility — Visibility is the first pillar of security operations, but it is a challenge to achieve as modern organizations are making data available everywhere. Inefficient and overly complex traditional logging tools often require knowledge of proprietary query language, and are slow to deliver results. The continuous spread of data, infrastructure, and applications requires a new level of analytics for full visibility. Fusion SIEM collects data from the endpoint to the cloud, eliminating blindspots to give analysts a full picture of their environment. Rapid, guided search boosts productivity, and ensures analysts of all levels can access valuable data exactly when they need it.

Prescriptive TDIR use case packages and automation – It has become too complicated to build an effective SOC using legacy SIEMs and a selection of purpose-built security products. Every SOC is unique, with its own mix of tools, level of staffing and maturity, and processes and there is no standard way to tackle cybersecurity. Fusion SIEM solves this by leveraging prescriptive, threat-centered TDIR Use Case Packages that provide repeatable workflows and prepackaged content that spans the entire TDIR lifecycle. These use cases include all the content necessary to operationalize that use case, including: prescribed data sources, parsers, detection rules and models, investigation and response checklists, and automated playbooks.

Meet regulatory compliance and audit requirements – Organizations must adhere to compliance regulations. Creating and maintaining compliance reports is time consuming but necessary. Whether you’re subject to GDPR, PCI, HIPAA, NYDFS, NERC, or utilizing a framework such as NIST or directives from DISA or CISA, Fusion SIEM significantly reduces the operational overhead of compliance monitoring and reporting. Fusion SIEM’s pre-packaged reports provide huge time savings spent correlating information, solves the risk of missing vital data, and eliminates the need to manually create compliance reports through report builder tools.