Market-leading SIEM to quickly detect, investigate, and respond to threats.
Key takeaways
SIEM platforms have become a cornerstone of modern security operations — pulling in log data from across your environment, surfacing threats, and helping teams respond fast. But what does that actually look like in practice?
From detecting real-time attacks to automating compliance reporting, SIEMs power a wide range of high-impact security use cases. In this article, we’ll walk through 10 of the most valuable ways organizations use SIEM every day — with real-world examples and key benefits for each.
Need a deeper dive into how SIEM works? Start with our SIEM explainer.
SIEMs collect and normalize logs from diverse systems (including firewalls, servers, applications, and endpoints, etc.) into a common format for efficient analysis. This normalization includes parsing timestamps, IPs, usernames, event IDs, and other critical fields into structured data.
Having a SIEM system enables strong awareness of activity across business systems and ensures that logs are being tracked should you require them for investigations.
Since all of the collection is handled in a singular interface, organizations are able to gather and normalize data easily. This enables powerful data analytics applications and supports data governance principles.
Here’s how a SIEM normalizes logs across hybrid environments:
An organization uses a SIEM to ingest logs from Windows servers, Linux systems, network firewalls, and cloud environments (like AWS and Azure). The SIEM normalizes this data into a standardized schema, such as Common Event Format (CEF) or Log Event Extended Format (LEEF), allowing security analysts to query and correlate events more easily.
This use case enables security teams to have:
SIEMs detect threats in real time by continuously monitoring logs with correlation rules, anomaly detection, and behavioral analytics, identifying patterns like:
SIEM platforms can also counter threats with AI-based threat detection capabilities. To identify suspicious activity, SIEMs will analyze:
Here's what real-time threat detection can look like in action:
A correlation rule in a SIEM detects a failed login attempt followed by a successful login and subsequent privilege escalation on a critical server, all within five minutes. This sequence triggers a high-severity alert, prompting immediate investigation.
In another example, Children's National Hospital utilized Splunk Enterprise Security to detect 40% more threats compared to when a SIEM solution was not implemented.
This use case enables:
SIEMs enable compliance reporting by generating audit reports and enforcing retention policies., as required by applicable regulatory frameworks. With SIEMs, the reporting process is easily automated and tracked.
Additionally, a SIEM solution stores logs in a central database, which makes forensic investigations fuss-free and transparent. These logs are a reliable way to demonstrate compliance with applicable regulations.
Here’s how this use case looks in the real world:
A healthcare organization uses a SIEM to generate HIPAA-compliant reports that show:
This use case means teams across the business have:
SIEMs track user behavior to identify anomalies that may signify account compromise, data misuse, or policy violations. This includes monitoring:
Over time, modern SIEM solutions have developed more sophisticated features, including user behavior analytics (UBA) and entity behavior analytics (UEBA), to pick up deviations from the norm.
Here’s an example of this user behavior monitoring:
A SIEM detects that an employee who typically accesses systems during 9 a.m. to 5 p.m. from a New York IP is now accessing a finance server at 3 a.m. from a foreign IP. This deviation from normal behavior triggers a medium-severity alert.
This use case means security teams have access to:
SIEMs detect advanced persistent threats (APTs) by correlating benign events into a broader threat picture. APTs are prolonged, well-coordinated, well-funded cyberattacks where undetected intruders steal sensitive data, usually with the goal of:
APT campaigns can unfold over weeks or months and consist of multiple stages: reconnaissance, initial access, lateral movement, and exfiltration. A robust SIEM solution should be able to correlate seemingly separate events to identify an APT intruder.
Here’s how a risk-based alerting strategy plays out in practice:
A SIEM correlates unusual DNS queries, unauthorized access attempts to databases, and large outbound data transfers over non-standard ports — and plots them on a timeline. This timeline reveals a slow-moving APT attempting to exfiltrate sensitive intellectual property.
This use case results in:
Modern SIEMs integrate with cloud-native monitoring tools to provide unified visibility into cloud and hybrid environments.
More enterprise data is being entrusted to cloud environments, like those from the big 3, among countless others: AWS CloudTrail, Azure Security Center, Google Cloud Operations Suite. SIEMs with cloud integrations provide powerful monitoring capabilities of all logs stored in the cloud.
A typical implementation might look like this:
The SIEM ingests AWS IAM access logs, S3 access logs, and Azure Activity Logs. It detects the creation of a new IAM user with administrator privileges during non-business hours, followed by access to sensitive S3 buckets.
This use cases enables:
Security teams use SIEMs for proactive threat hunting by querying logs, searching for indicators of compromise (IOCs), and identifying malicious patterns. This proactive approach extends the SIEM beyond passive alerting and event correlation.
Here’s how threat hunting using SIEMs works:
A security analyst uses a SIEM to investigate connections to a suspicious IP address identified by a threat intel feed. The analyst uncovers a pattern of beaconing behavior from several endpoints, revealing a dormant command-and-control (C2) channel.
With the threat hunting use case, security analysts now have:
SIEMs have been known to integrate with security orchestration, automation, and response (SOAR) technology. SIEM-to-SOAR integrations mean playbooks can execute automatically in response to security alerts, enabling actions such as:
SIEMs typically do not have overlapping alerts with SOARs. This is by design: to ensure there isn’t alert fatigue. This reduces manual handling of alerts and therefore enables faster response time — security teams are now less overloaded with alerts and better able to address threats quickly.
Here’s an example:
A SIEM detects signs of ransomware activity such as mass file encryption and registry modifications. The SOAR platform automatically isolates the affected machine from the network, sends notifications, and creates a case in the ticketing system.
This use case offers tangible benefits like:
SIEMs provide better endpoint visibility by ingesting telemetry from EDR platforms. This enables the SIEM to correlate endpoint behavior with network and authentication data, providing more complete coverage.
This example illustrates the use case:
A suspicious PowerShell process is detected by the EDR. The SIEM correlates this with unusual authentication attempts to critical systems, revealing a compromised endpoint being used for lateral movement.
This use case enables:
Organizations use SIEMs to monitor the activities of anyone who accesses internal systems, including external vendors, contractors, and partners. An important part of risk management, this ensures that third-party users comply with security policies.
Here’s what this use case might look like:
The SIEM monitors VPN and SSH logins by third-party maintenance providers. Anomalous access from an unexpected geographic region or an unusual time of day triggers an alert.
This use case gives the organization:
The 10 use cases above can apply to practically any enterprise or organization. But what about SIEM in specific industries — how do they differ? Let’s look at some industry-specific applications for SIEM.
SIEM empowers financial institutions to monitor high-value transactions as well as provide an easy way to access logs and audit trails for compliance. SIEMs have also seen use case in Fintech applications.
Here are some examples:
Progressive Insurance used a SIEM tool, Splunk Enterprise Security, to protect $120 billion in market capitalization.
SIEM make it easy to better protect and monitor sensitive PII like personal identifiers and highly confidential medical information in healthcare. Here are some examples:
Manufacturing can benefit from SIEM solutions, especially with automating surveillance and collecting logs from logistics activities. Here are some examples:
Government and public-sector agencies can benefit from SIEM solutions, with a focus on monitoring access to classified information and state secrets. This is crucial in protecting national security and its assets.
Here are some examples:
SIEM platforms have become indispensable and are used widely across various industries. The potential that SIEMs bring continues to rise as more organizations integrate them with other platforms like SOARs and EDR platforms.
Start protecting your organization with SIEMs to bolster your threat detection and overall monitoring measures today. Get started with this free product tour of Splunk Enterprise Security.
Common SIEM use cases include log aggregation, threat detection, compliance reporting, insider threat monitoring, and cloud visibility.
SIEM platforms use correlation rules, anomaly detection, and behavioral analytics to identify suspicious patterns and trigger real-time alerts.
Yes, SIEMs automate compliance reporting and audit trails for regulations like HIPAA, PCI DSS, GDPR, and SOX.
Modern SIEMs incorporate cloud-native capabilities, AI-driven analytics, and support for dynamic environments like SaaS, containers, and hybrid clouds.
By correlating behavior patterns, monitoring privileged access, and applying UEBA, SIEMs can detect unusual internal activity that may signal insider threats.
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This posting does not necessarily represent Splunk's position, strategies or opinion.
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