Real-World SIEM Applications: Harness the Potential of Your Security Operations Center
Are you seeking to strengthen the security of your organization? Discovering real-world SIEM use cases will allow you to unleash your cloud security to its full potential, using SIEM technology to detect advanced threats, protect against data breaches, and more.
In this blog post, we will highlight six SIEM use cases that can significantly boost the capabilities of your Security Operations Center.
Why does an organization require SIEM use cases?
Organizations require SIEM (Security Information and Event Management) use cases in order to better protect their own security data, digital infrastructure and assets from potential security breaches and threats. SIEM use cases provide a structured method of detecting, responding to incidents in real-time, helping organizations:
Focus on critical security threats: By deploying SIEM use cases, organizations can focus their attention on addressing the most urgent security risks while prioritizing alerts based on severity and impact.
Improve Security Team Efficiency: SIEM use cases enable security teams to become more effective by automating repetitive tasks, reducing false positives, and providing timely responses for legitimate threats.
Increase threat detection and response capabilities: SIEM use cases provide a framework for correlating events, detecting patterns, and recognizing anomalies in network activity – leading to faster identification of potential threats.
Facilitate Compliance: Many industries have regulatory requirements regarding monitoring, reporting, and responding to security incidents. Implementing SIEM use cases helps organizations comply more efficiently with these obligations.
Define and Implement SIEM Use Cases
Determine Your Organization’s Specific Security Requirements: Examine existing security policies, risk assessments and incident response plans in order to ascertain your organization’s individual security requirements and priorities and objectives.
Establish SIEM use cases: Based on your organization’s needs, create specific, measurable, and actionable use cases that address key security concerns.
Configure data sources: When configuring data sources on a SIEM platform, make sure it has access to relevant log sources and feeds that support your use cases.
Develop correlation rules and alerts: Craft rules that accurately detect security events or patterns of interest, then configure alerts that notify security teams whenever these occur.
Test and Refine: Ongoing evaluation and refinement of SIEM use cases as needed is key to their effectiveness, with correlation rules and alerts adjusted as necessary.
Building SIEM use cases the right way
Focus on High-Impact Threats: Give top priority to use cases that address the most significant threats facing your organization.
Balance Simplicity and Complexity: Craft correlation rules that are both complex enough to detect threats accurately, yet simple enough so as to minimize false positives.
Engage with stakeholders: Involve all relevant teams – IT, legal and compliance – in your SIEM implementation to ensure its use cases align with organizational goals and regulatory compliance obligations.
Document and Review: To ensure effective implementation of your SIEM use cases, be sure to clearly outline their objectives, requirements and implementation details in an easily searchable format. Furthermore, conduct regular reviews to make sure they remain pertinent and efficient.
1. Advanced Threat Detection
SIEM tools can play a vital role in advanced security threat detection. Security Information and Event Management (SIEM) systems can also identify anomalies and alert you of potential attacks before they escalate into full-fledged assaults.
Utilizing SIEM’s real-time monitoring and automated response capabilities, your SOC can detect and respond to threats such as zero-day exploits, ransomware attacks and phishing attempts; helping ensure that all the valuable assets in your organization remain protected.
2. Insider Threat Monitoring
Insider threats such as employee sabotage or data theft are becoming an increasing worry for many organizations. SIEM technology can assist your SOC team in monitoring for suspicious activity patterns identifying anomalies or unauthoritied access to security devices and operating systems, helping detect and mitigate insider threats before they cause significant harm.
Integrating SIEM with other security tools such as User and Entity Behavior Analytics (UEBA) and Data Loss Prevention (DLP), you can form a comprehensive solution for protecting your entire organization against both external threats and internal risks.
3. Compliance Reporting and Auditing
Conformance to regulatory compliance requirements is of utmost importance for organizations in various industries, and SIEM use cases include automating compliance reporting and auditing processes. With SIEM’s log aggregation, audit trails and reporting capabilities, you can easily demonstrate compliance with regulations such as GDPR, HIPAA, and PCI-DSS.
This will not only simplify the auditing process but will also protect your organization from costly fines and penalties associated with noncompliance.
4. Incident Response and Forensics
SIEM tools can assist your Security Operations Center (SOC) with swiftly responding to security incidents by log monitoring, automating correlation of events with security logs, prioritization alerts and providing contextual data.
SIEM allows your security team to quickly assess the scope and nature of attacks, identify root causes, and take appropriate actions to mitigate damage. Furthermore, its log retention capabilities offer you initial access to valuable data for post-incident forensics studies; helping your team learn from past incidents so as to prevent future ones.
5. Network Visibility and Monitoring
Acquiring visibility into your network’s activities is critical for maintaining an effective security posture, with SIEM use cases often covering security analytics, network monitoring access control, and visibility as part of its purpose.
SIEM tools offer a holistic view of your network by gathering and analyzing log data from multiple sources, giving the Security Operations Center (SOC) tools a comprehensive picture of operating system that allows it to detect anomalies, identify vulnerabilities and monitor user activity more effectively – giving security teams more visibility into threats as they emerge and maintain an inherently more secure environment.
Prioritize and organize SIEM correlation use cases
Categorize Use Cases: Your SIEM use cases should be organized based on criteria like threat type, asset impact or risk level.
Prioritize Use Cases: Assess each use case based on its potential impact and likelihood.
Plan Implementation: Establish a phased implementation plan, prioritizing high-priority use cases first and gradually expanding it as necessary.
Assess Progress: Regularly evaluate the performance of your SIEM use cases and adjust priorities as necessary to maintain optimal threat detection and response capabilities.
SIEM Correlation Rules with Logic
To increase monitoring performance and the efficiency of your SIEM solution, it’s crucial to create and implement high-value correlation rules. These rules based on the logic between events and activities help your SOC quickly identify threats and vulnerabilities more accurately.
This section will examine some high-value SIEM correlation rules attack patterns that can help your organization enhance its security posture.
1. Multiple Failed Logins Followed by a Successful Login
Logical fallacies: Multiple failed login attempts could be evidence of an attacker trying to brute force their way into an account, and if these brute force attack efforts lead to successful log in attempts it could indicate they’ve gained entry with compromised user credentials.
Correlation Rule:
Watch for suspicious behavior: multiple failed login attempts within 15 minutes that are followed by successful log in for the same account, in case this pattern indicates potential unauthorized access. When this pattern is observed, raise an alert regarding potential unauthorized access.
2. Large Data Transfers Outside Business Hours
Data exfiltration often occurs outside of regular working hours when there is less oversight for security purposes, making it easier for attackers to remain undetected and remain undetected by security systems.
Correlation Rule:
Monitor audit logs for large data transfers log files (e.g., over 1 GB) that occur outside normal business hours and, if detected, raise an alert regarding possible data exfiltration.
3. Geographically Improbable Access
Logical Explanation: If two logins from the same account within a short period from different geographical areas are detected within days, this could indicate that an attacker has compromised it.
Correlation Rule:
Monitor for successful logins from geographically distant locations (e.g., different countries) at odd times (30 minutes is ideal). If this occurs, raise an alert as possible account compromise or data breach may have taken place.
4. New User Account Creation Followed by High-Privilege Actions
Attackers typically create new user accounts with elevated privileges in order to compromise user credentials, gain control of systems and network devices and sustain persistent attacks.
Correlation Rule:
Monitor for new user account creation followed by high-privilege actions (such as adding them to an admin group, changing firewall rules or disabling security features within one hour), then raise an alert as this indicates an insider threat or account compromise.
5. Unusual Traffic Patterns
Logic: Unusual traffic patterns, including sudden spikes in volume or traffic directed toward nonstandard ports, could indicate malicious activity such as command and control (C2) communications or data exfiltration attempts.
Correlation Rule:
Monitor for traffic spikes (200% or greater relative to baseline) or traffic directed to non-standard ports (e.g., any port other than 80 or 443 for web traffic) which indicate possible malicious activity and should raise an alert immediately.
6. Multiple Vulnerability Scans from a Single Source
Logical Analysis: Attackers may conduct vulnerability scans in order to assess weaknesses in an organization’s network and security controls and systems. Multiple scans coming from one source could signal possible reconnaissance activity.
Correlation Rule:
Monitor for multiple vulnerability scans from one IP address within 24 hours from one another, which would signal potential reconnaissance activity. When detected, raise an alert.
Summary
Integrating high-value correlation rules into your SIEM solution can significantly enhance the SOC’s threat detection capabilities. By focusing on the relationships between various critical events, and activities, these rules help identify threats more efficiently.
Refining and updating your correlation rules regularly to match the changing threat landscape will help ensure maximum effectiveness of protection.
Create Correlation Rules in Splunk Enterprise Security Tools
Splunk Enterprise Security (ES) is a widely adopted SIEM solution, offering comprehensive monitoring and analysis capabilities.
Why do companies utilize Splunk?
Splunk is widely utilized by companies for its powerful data analytics and log management capabilities, especially its ability to:
Collect and analyze large volumes of data from various sources.
Give real-time monitoring and alerting capabilities.
Provide customizable dashboards and reporting features.
Unlock advanced searching and data correlation capabilities.
Support multiple security and compliance use cases, including SIEM.
In this section, we will create a Splunk ES correlation rule based on the log analysis of one of the logics mentioned earlier – Multiple Failed Logins Followed by a Successful Login. This rule can help identify any potential unauthorised access and alert your SOC of potential concerns.
1. Multiple Failed Logins Followed by a Successful Login
To create a correlation rule in Splunk ES for this logic, follow these steps:
Navigate to the Splunk ES app within your Splunk environment.
Navigate to Content Management Configure > Manage > System.
Click “Create New and select Correlation Search.”
Enter the following details:
Title: Failed Logins Interrupting Successful Login
Description: Detects multiple failed login attempts followed by successful log in attempts for the same account within a short period, potentially signalling any unauthorized access.
Search: Use this search query to generate a correlation rule:
(index=authentication action=failure OR action=success)
| stats count(eval(action="failure")) as failed_count count(eval(action="success")) as success_count min(_time) as first_time max(_time) as last_time by src, user
| eval duration=last_time-first_time
| where failed_count >= 5 AND success_count >= 1 AND duration <= 900
| table _time src user failed_count success_count duration
This search query filters authentication events (both failures and successes), then calculates the count of failed and successful login attempts for each source IP address (src) and user account (user).
Additionally, this query also determines the time duration between each first and last login attempt; finally filtering its results only to cases with at least five failed login attempts and one successful login attempt within 15 minutes (900 seconds).
Continuing Further:
Set the Earliest Time and Latest Time fields to set the search timeframe; for instance, set this field to “15m@m and now” to search within 15 minutes of now.
Select an appropriate Severity level, such as High.
Select “Create Notable Event.” Depending on your needs, other actions could also be applied such as sending email alerts or initiating custom scripts.
Save the correlation search.
Once a correlation search is saved, Splunk ES will run it regularly over a given time range and create notable events or trigger other actions when search criteria are met – helping your SOC detect and respond more efficiently to potential unauthorized access incidents.
Here are the Splunk search queries for the remaining use case logics:
2. Large Data Transfers Outside Business Hours
This query searches for events with large data transfers (greater than 1 GB) outside regular business hours (8 AM to 6 PM). Replace the index with the appropriate network or firewall index for your environment.
(index=network OR index=firewall)
| eval transfer_size_MB = round(bytes/1024/1024, 2)
| eval hour = strftime(_time, "%H")
| search transfer_size_MB > 1024
| where (hour < "08" OR hour >= "18")
| table _time src_ip dest_ip transfer_size_MB
3. Geographically Improbable Access
This query detects successful logins from different countries within an improbable time frame (30 minutes). Replace the index with the appropriate authentication index for your environment.
(index=authentication action=success)
| stats min(_time) as first_time max(_time) as last_time by src, user
| eval duration=last_time-first_time
| iplocation src
| stats min(eval(duration)) as min_duration max(eval(duration)) as max_duration values(Country) as countries by user
| where min_duration <= 1800 AND max_duration > 0 AND mvcount(countries) > 1
| table _time user countries min_duration max_duration
4. New User Account Creation Followed by High-Privilege Actions
This query searches for user activity events that begin with a new user account creation and end with a high-privilege action within a one-hour time frame. Replace user_creation and high_privilege_action with the appropriate field values for your environment, and update the index accordingly.
(index=user_activity)
| transaction user startswith="user_creation" endswith="high_privilege_action" maxspan=1h
| table _time user src
5. Unusual Traffic Patterns
(index=network_traffic)
| bin _time span=1h
| stats sum(bytes) as total_bytes by _time, src_ip, dest_ip
| eventstats avg(total_bytes) as avg_bytes stdev(total_bytes) as stdev_bytes by src_ip, dest_ip
| eval is_spike=if(total_bytes >= avg_bytes + (2 * stdev_bytes), 1, 0)
| search is_spike=1 OR dest_port!=80 OR dest_port!=443
| table _time src_ip dest_ip dest_port total_bytes
This query searches for unusual traffic patterns, such as traffic spikes (200% above the baseline) and traffic directed to non-standard ports (e.g., not 80 or 443 for web traffic). Replace the index with the appropriate network traffic index for your environment.
6. Multiple Vulnerability Scans from a Single Source
(index=vulnerability_scans)
| stats count by src_ip, _time
| bin _time span=1d
| stats count by src_ip
| where count >= 2
| table _time src_ip count
This query searches for multiple vulnerability scans originating from a single IP address within a 24-hour time frame. Replace the index with the appropriate vulnerability scans index for your environment.
Please note that you may need to modify the search queries according to your specific environment, data sources, and field names.
Optimize Your SIEM Correlation Rules
Review and Update Correlation Rules Regularly: As your organization’s threat landscape shifts, be sure that your correlation rules remain effective at detecting and responding to new threats.
Validate and Test Correlation Rules: Validate and test correlation rules against historical data to ensure they generate accurate alerts while limiting false positives.
Adjust rule thresholds: To prevent alert fatigue and ensure security teams can prioritize their efforts effectively. Adjust thresholds accordingly.
Integrate threat intelligence feeds: Integrating external threat intelligence sources will allow you to improve the accuracy of your correlation rules and stay abreast of emerging threats.
Utilize Machine Learning and AI: Leverage advanced analytics capabilities such as machine learning and artificial intelligence to enhance the accuracy and efficiency of your correlation rules over time.
Monitor Rule Performance: Review the performance of your correlation rules regularly, paying special attention to key performance indicators like false positives, false negatives, and missed detections.
Collaborate with Your Security Team: Involve your security team in reviewing the effectiveness of your correlation rules, gathering feedback from them on their use and making any necessary modifications based on their input.
Conclusion
Implementing real-world SIEM use cases can significantly expand your Security Operations Center’s capabilities. By taking advantage of SIEM technology for advanced threat detection, insider threat monitoring,, compliance reporting, incident response, network visibility and network analytics capabilities – you can unleash its full potential and create an effective security solution for your organization.
