SIEM Checklist: Specific Metrics to Evaluate SIEM
In today’s rapidly-shifting enterprise landscape, a Security Information and Event Management (SIEM) system plays a pivotal role in safeguarding companies from cyber attackers and employee mistakes. By providing comprehensive monitoring and analysis of security events across an organization’s network, SIEM tools help detect and respond to potential threats.
Combining data from various sources, offering a unified view of an organization’s security posture – or muddying the waters and bogging your security team down with endless alerts – SIEM tools need to be handled with due care and attention. This article will delve into a detailed SIEM checklist, guiding you through essential metrics and features to consider for effective security monitoring – and avoiding the false alarms in the middle of the night. To get to grips with the basics, visit our previous article on what SIEM is.
Combining data from various sources, offering a unified view of an organization’s security posture – or muddying the waters and bogging your security team down with endless alerts – SIEM tools need to be handled with due care and attention. This article will delve into a detailed SIEM checklist, guiding you through essential metrics and features to consider for effective security monitoring – and avoiding the false alarms in the middle of the night. To get to grips with the basics, visit our previous article on what SIEM is.
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Why You Need SIEM for Your Security Monitoring
SIEM systems serve as a central hub for collecting and analyzing security-related data from various sources within an organization’s IT infrastructure. This approach enables a more comprehensive view of security threats, making it easier to identify, assess, and respond to potential risks.
One of the primary reasons organizations opt for a SIEM solution is its ability to provide real-time visibility into an organization’s security posture. By aggregating and correlating data from multiple sources, SIEM tools can detect unusual patterns or anomalies that might indicate a security breach or vulnerability. Another significant advantage of SIEM systems is their role in compliance and regulatory requirements. Many industries are subject to stringent security standards, and SIEM tools can help organizations ensure they meet these requirements by providing detailed logging, reporting, and alerting functionalities.
In the event of a security breach, SIEM tools can quickly gather relevant data, aiding in a swift and effective response. This reduces the potential damage and downtime caused by security incidents. In short, SIEM solutions are extremely beneficial for organizations – you’re welcome to learn more about SIEM benefits.
Let’s delve into the specific metrics you need to evaluate when selecting a SIEM solution.
One of the primary reasons organizations opt for a SIEM solution is its ability to provide real-time visibility into an organization’s security posture. By aggregating and correlating data from multiple sources, SIEM tools can detect unusual patterns or anomalies that might indicate a security breach or vulnerability. Another significant advantage of SIEM systems is their role in compliance and regulatory requirements. Many industries are subject to stringent security standards, and SIEM tools can help organizations ensure they meet these requirements by providing detailed logging, reporting, and alerting functionalities.
In the event of a security breach, SIEM tools can quickly gather relevant data, aiding in a swift and effective response. This reduces the potential damage and downtime caused by security incidents. In short, SIEM solutions are extremely beneficial for organizations – you’re welcome to learn more about SIEM benefits.
Let’s delve into the specific metrics you need to evaluate when selecting a SIEM solution.
SIEM Solution Evaluation Checklist
Implementing a SIEM solution is a strategic decision that goes beyond merely detecting potential threats. It’s about finding the right balance between providing timely threat alerts and not overwhelming the security staff. Its effectiveness is contingent on its ability to mirror the team’s capacity for investigating and triaging alerts. To achieve this, SIEM tools can be broken down into three primary components: the data collection module, the threat detection system, and threat response. In order, these collect, analyze, and alert your team to security events in your tech stack. An evaluation of the correct tool for your organization requires a thorough analysis of the best tool for your needs, starting with the following SIEM checklist:
Asset Integration
The most critical aspect of any SIEM solution is its ability to monitor network connections and analyze running processes. To achieve this, an accurate amd updated list of assets must be kept: these endpoints and servers are where logs are generated – making sure they’re connected to your analysis engine is the only way to achieve 360-degree visibility.
Traditionally, asset integration was made possible by agents – specialized software that’s installed directly on the endpoint itself. While better than nothing, SIEM tools that rely solely on agents aren’t getting the full picture. Not only are they a hassle to install within complex tech stacks, but some areas simply aren’t suitable for agent software – such as network firewalls and pre-production servers. To guarantee a truly complete view of your assets, your SIEM tool should either be able to ingest logs from any source, integrate with other established solutions, or, ideally, both.
Not only is it important to have the full scope of devices and endpoints, but defining the criticality of these devices within your SIEM tool offers another step beyond. By prioritizing alerts based on the device’s importance, your team can benefit from a foundational shift: from blind alerts to efficiency-driven incidents.
Traditionally, asset integration was made possible by agents – specialized software that’s installed directly on the endpoint itself. While better than nothing, SIEM tools that rely solely on agents aren’t getting the full picture. Not only are they a hassle to install within complex tech stacks, but some areas simply aren’t suitable for agent software – such as network firewalls and pre-production servers. To guarantee a truly complete view of your assets, your SIEM tool should either be able to ingest logs from any source, integrate with other established solutions, or, ideally, both.
Not only is it important to have the full scope of devices and endpoints, but defining the criticality of these devices within your SIEM tool offers another step beyond. By prioritizing alerts based on the device’s importance, your team can benefit from a foundational shift: from blind alerts to efficiency-driven incidents.
Rule Customization
The heart of SIEM threat analysis lies in its rules – at its core, each rule simply defines a specific event occurring a certain number of times within a given period. The challenge is to set these thresholds to differentiate between normal and abnormal traffic in your specific environment. This process requires establishing a network baseline by running the system for a few weeks and analyzing traffic patterns. Surprisingly, many organizations fail to fine-tune their SIEM to their unique environment – without which, SIEM tools threaten to overwhelm your security team with endless useless alerts. While asset prioritization can help boost response time efficiency, rule customization allows teams to reduce false positives in the first place.
Digging deeper, there are two types of rules present. Correlation rules are those above – the ones that take raw event data and transform it into actionable threat information. While important, other asset discovery rules allow for SIEM tools to add more context by identifying the OS, applications, and device information surrounding every log. These are vital because your SIEM tool needs to not only send high-priority alerts when an SQL attack is underway – but it further needs to determine if the attack could be successful in the first place.
For example, if an IP range in the feed is from a known hacker group, the system could elevate the criticality of related events. Geolocation data also plays a role, helping to adjust the criticality based on the origin or destination of network traffic. However, low-quality threat feeds can significantly increase false positives, underlining the importance of choosing a reliable, regularly updated feed.
False positives are more than just minor inconveniences – they can be major disruptions, especially when they result in alerts that need immediate attention in the early hours of the morning. These unnecessary alerts not only disrupt sleep but also contribute to alert fatigue among security personnel, potentially leading to slower response times or missed genuine threats. When a SIEM system has access to configuration management data, it gains insights into the normal operational state of the network and its components. This includes knowledge of scheduled updates, maintenance activities, and other routine changes that could otherwise be misinterpreted as suspicious activities. The integration of change management data into a SIEM solution is crucial for enhancing its accuracy and effectiveness. It enables the system to discern between normal and anomalous activities more effectively.
With a solid foundation of rules, it finally becomes possible for your SIEM solution to start doing its job: detect vulnerabilities.
Digging deeper, there are two types of rules present. Correlation rules are those above – the ones that take raw event data and transform it into actionable threat information. While important, other asset discovery rules allow for SIEM tools to add more context by identifying the OS, applications, and device information surrounding every log. These are vital because your SIEM tool needs to not only send high-priority alerts when an SQL attack is underway – but it further needs to determine if the attack could be successful in the first place.
For example, if an IP range in the feed is from a known hacker group, the system could elevate the criticality of related events. Geolocation data also plays a role, helping to adjust the criticality based on the origin or destination of network traffic. However, low-quality threat feeds can significantly increase false positives, underlining the importance of choosing a reliable, regularly updated feed.
False positives are more than just minor inconveniences – they can be major disruptions, especially when they result in alerts that need immediate attention in the early hours of the morning. These unnecessary alerts not only disrupt sleep but also contribute to alert fatigue among security personnel, potentially leading to slower response times or missed genuine threats. When a SIEM system has access to configuration management data, it gains insights into the normal operational state of the network and its components. This includes knowledge of scheduled updates, maintenance activities, and other routine changes that could otherwise be misinterpreted as suspicious activities. The integration of change management data into a SIEM solution is crucial for enhancing its accuracy and effectiveness. It enables the system to discern between normal and anomalous activities more effectively.
With a solid foundation of rules, it finally becomes possible for your SIEM solution to start doing its job: detect vulnerabilities.
Vulnerability Detection with UEBA
While vulnerability detection is, on paper, the core focus of SIEM, it’s third in this list because the rules surrounding detection are as important as vuln detection. One specific vulnerability detection capability that’s included should be User & Entity Behavior Analytics (UEBA). UEBA sits on the other side of the risk analysis coin – while some SIEM tools rely on rules alone, UEBA takes a more proactive approach and analyzes user behavior itself.
Suppose we aim to analyze the VPN usage patterns of a user named Tom. We could track various details of his VPN activity, such as the duration of his VPN sessions, the IP addresses used for connections, and the countries from which he logs in. By collecting data on these attributes and applying data science techniques, we can create a usage model for him. After accumulating sufficient data, we can employ data science methods to discern patterns in Tom’s VPN usage and establish what constitutes his normal activity profile. By relying on risk scores instead of individual security alerts, UBEA frameworks benefit from drastically lower false positives. For instance, a single deviation from the norm does not automatically trigger an alert to analysts. Instead, each unusual behavior observed in a user’s activities contributes to an overall risk score. When a user accumulates enough risk points within a certain timeframe, they are then classified as either notable or high-risk.
Another benefit of UEBA is its ability to closely adhere to access controls. With the previously-established deep asset visibility, it becomes possible for SIEM tools to not only monitor who is accessing a file, device, or network – but also whether they’re authorized to do so. This can allow your security tooling to flag issues that otherwise would slip under the traditional IAM radar, such as account takeover attacks or malicious insiders. When issues are discovered, incident response templates help automate the sequence of steps that happen immediately after an alert is triggered. These help analysts rapidly verify the attack in question, and take corresponding actions to prevent further damage. When these are able to change based on the details of the alert, further time can be saved. Dynamic incident response workflows allow security teams to triage and respond to threats in lightening-fast time.
Suppose we aim to analyze the VPN usage patterns of a user named Tom. We could track various details of his VPN activity, such as the duration of his VPN sessions, the IP addresses used for connections, and the countries from which he logs in. By collecting data on these attributes and applying data science techniques, we can create a usage model for him. After accumulating sufficient data, we can employ data science methods to discern patterns in Tom’s VPN usage and establish what constitutes his normal activity profile. By relying on risk scores instead of individual security alerts, UBEA frameworks benefit from drastically lower false positives. For instance, a single deviation from the norm does not automatically trigger an alert to analysts. Instead, each unusual behavior observed in a user’s activities contributes to an overall risk score. When a user accumulates enough risk points within a certain timeframe, they are then classified as either notable or high-risk.
Another benefit of UEBA is its ability to closely adhere to access controls. With the previously-established deep asset visibility, it becomes possible for SIEM tools to not only monitor who is accessing a file, device, or network – but also whether they’re authorized to do so. This can allow your security tooling to flag issues that otherwise would slip under the traditional IAM radar, such as account takeover attacks or malicious insiders. When issues are discovered, incident response templates help automate the sequence of steps that happen immediately after an alert is triggered. These help analysts rapidly verify the attack in question, and take corresponding actions to prevent further damage. When these are able to change based on the details of the alert, further time can be saved. Dynamic incident response workflows allow security teams to triage and respond to threats in lightening-fast time.
Active and Passive Network Scanning
- Active Network Scanning: This involves proactively probing the network to discover devices, services, and vulnerabilities. Active scanning is akin to knocking on doors to see who answers – it sends out packets or requests to various systems to gather information. This method is essential for obtaining real-time data about the network’s state, identifying live hosts, open ports, and available services. It can also detect security weaknesses, such as outdated software or unpatched vulnerabilities.
- Passive Network Scanning: In contrast, passive scanning quietly observes network traffic without sending out any probes or packets. It’s like eavesdropping on conversations to gather intelligence. This method relies on analyzing traffic flow to identify devices and services. Passive scanning is particularly valuable for its non-intrusive nature, ensuring no disruption to normal network activities. It can detect devices that active scanning might miss, such as those only active during certain periods.
Both active and passive scanning are integral to a comprehensive SIEM tool. Active scanning provides direct, immediate insights, while passive scanning offers ongoing surveillance. Together, they form a layered defense strategy, ensuring that no stone is left unturned in the pursuit of network security and integrity.
Dashboard Personalization
Different operational levels within an organization require their own view of your tech stack’s security. Management, for example, needs high-level summaries focused on business issues, not technical details. In contrast, security technicians benefit from in-depth, comprehensive reports. A SIEM tool that can support this level of personalization not only ensures that each team member receives the most relevant information for their role – it also allows for better communication between team members and management, without further extra reliance on third-party tooling.
Clear Reporting and Forensics
Effective reporting is integral to a SIEM solution. It should provide clear, actionable insights that align with the distinct needs of various organizational tiers, from top-level management to technical staff. This ensures that everyone involved in security monitoring and response has the necessary information to make informed decisions and act efficiently.
Next-gen SIEM Evaluation
Stellar Cyber’s next-gen SIEM solution is engineered to handle the complexities of modern cybersecurity with a scalable architecture designed to manage large volumes of data. It effortlessly ingests, normalizes, enriches, and fuses data from every IT and security tool. Then, by leveraging a powerful AI engine, Stellar Cyber efficiently processes this data, making it an ideal solution for any scale of operation.
At the heart of Stellar Cyber’s robust performance lies its microservice-based, cloud-native architecture. This design allows for horizontal scaling in response to demand, ensuring the system can handle any volume of data and user load required for your security mission. This architecture emphasizes resource sharing, system monitoring, and scaling, enabling you to focus solely on security without the burden of system management concerns.
Flexibility in deployment is a key aspect of Stellar Cyber’s solution. It is adaptable to various environments, whether on-premises, in the cloud, or hybrid setup, ensuring seamless integration with your existing infrastructure. Moreover, Stellar Cyber is inherently designed for multi-tenancy from the ground up. This feature guarantees flexible and secure operations for organizations of all sizes and types. Additionally, the solution’s multi-site capability ensures that data remains resident within its specific region. This is crucial for compliance and scalability, especially in complex operating environments where data residency and sovereignty are essential.
Stellar Cyber’s approach not only meets the current demands of cybersecurity but is also future-proof, ready to evolve with your organization’s needs. Whether you’re managing a small enterprise or a large-scale operation, Stellar Cyber’s solution is equipped to provide superior security monitoring and threat management. Discover more about our Next Gen SIEM platform and see how it can enhance your organization’s security posture.
At the heart of Stellar Cyber’s robust performance lies its microservice-based, cloud-native architecture. This design allows for horizontal scaling in response to demand, ensuring the system can handle any volume of data and user load required for your security mission. This architecture emphasizes resource sharing, system monitoring, and scaling, enabling you to focus solely on security without the burden of system management concerns.
Flexibility in deployment is a key aspect of Stellar Cyber’s solution. It is adaptable to various environments, whether on-premises, in the cloud, or hybrid setup, ensuring seamless integration with your existing infrastructure. Moreover, Stellar Cyber is inherently designed for multi-tenancy from the ground up. This feature guarantees flexible and secure operations for organizations of all sizes and types. Additionally, the solution’s multi-site capability ensures that data remains resident within its specific region. This is crucial for compliance and scalability, especially in complex operating environments where data residency and sovereignty are essential.
Stellar Cyber’s approach not only meets the current demands of cybersecurity but is also future-proof, ready to evolve with your organization’s needs. Whether you’re managing a small enterprise or a large-scale operation, Stellar Cyber’s solution is equipped to provide superior security monitoring and threat management. Discover more about our Next Gen SIEM platform and see how it can enhance your organization’s security posture.