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What is SIEM? Definition, Components and Capabilities

Cyberthreats have entered a new age of creation and deployment. Whether motivated by international conflict or financial profit, the ability of groups to tamper with critical pieces of infrastructure has never been greater. External economic pressures and international tensions aren’t the only factors increasing the cyberattack risk: the sheer volume of connected devices and software easily exceeds four figures for established enterprises.

Security Information and Event Management (SIEM) aims to leverage the quantity of data generated by enormous tech stacks and turn the tables on attackers. This article will cover the definition of SIEM, alongside practical applications of SIEM that turn disparate security stacks into a cohesive, context-sensitive whole.

How Does SIEM Work?

SIEM is a comprehensive approach introduced by the Gartner Institute in 2005, aiming to harness the extensive data from devices and event logs within a network. Over time, SIEM software has evolved to incorporate user and entity behavior analytics (UEBA) and AI enhancements, aligning application activity with indicators of compromise. Effectively implemented, SIEM serves as a proactive network defense, functioning like an alarm system to identify potential threats and offering insights into unauthorized access methods.

At its core, SIEM combines security information management (SIM) and security event management (SEM) into a unified system. It aggregates, searches, and reports data from the entire networked environment, making vast amounts of information easily comprehensible for human analysis. This consolidated data allows for detailed investigations and monitoring of data security breaches. In essence, SIEM technology acts as a holistic security management system, continuously monitoring and responding to potential threats in real time.

6 Key SIEM Components and Capabilities

The fundamental elements that constitute a robust Security Information and Event Management system are as varied as the data it ingests. From the core components that aggregate and analyze data to the advanced capabilities that enhance threat detection and response, understanding critical SIEM features will help inform how you choose to safeguard your organization against cybersecurity threats.

#1. Log Management

SIEM software plays a vital role in managing and consolidating log data to ensure a comprehensive understanding of an organization’s IT environment. This process involves collecting log and event data from various sources such as applications, devices, networks, infrastructure, and systems. The gathered data undergoes analysis to provide a holistic overview. Logs from diverse sources are aggregated and normalized into a common format, simplifying analysis. Different log formats, including syslog, JSON, and XML, are accommodated. Collecting this is made possible thanks to the wide range of integration options.
Various SIEM integrations are commonly employed, many of which include:
  • Agents: Embedded into target source servers, SIEM software agents operate as separate services, transmitting log contents to the SIEM solution.

  • API Connections: Logs are gathered through API endpoints, utilizing API keys. This method is frequently employed for third-party and cloud applications.

  • Application Integrations:  Located on the SIEM side, these integrations handle data in diverse formats and use specific protocols from source systems. They extract relevant fields and create visualizations tailored for specific use cases. Many integrations also offer pre-built visualizations for various scenarios.

  • Webhooks : This method is utilized to forward data from the SIEM solution to another platform, triggered by a rule. For instance, an integration with Slack might send alerts to a designated channel, notifying a team of an issue requiring investigation.

  • Custom-Written Scripts: Engineers may execute scheduled, customized scripts to collect data from source systems. These scripts format log data and transmit it to the SIEM software as part of the integration process.
To enhance searchability and comprehension for security analysts, SIEM tools employ log parsing and enrichment techniques. Raw logs are transformed into human-readable information, breaking down data into timestamps, event types, source IP addresses, usernames, geolocation data, and user context. This step streamlines the analysis process and improves the interpretability of log entries.

In addition, SIEM tools ensure the storage and retention of log data in a centralized repository for extended periods. This capability proves invaluable for forensic investigations, historical analysis, and compliance adherence, serving as a crucial resource for maintaining a thorough record of events over time.

#2. Threat Intelligence and Detection

Sophisticated attackers with expertise and ample resources are a reality. If you become their target, they will meticulously seek out vulnerabilities to exploit. Despite employing top-notch security tools, it is impossible to uncover every potential threat. This is where the concept of threat hunting becomes crucial. Its fundamental mission is to identify and uncover precisely these kinds of attackers.

In the realm of threat hunting, data is the linchpin for success. Without a clear view of system activities, effective response becomes unattainable. The decision of which systems to extract data from is often contingent on the analytical scope – of which SIEM offers one of the widest scope available.

#3. Notifications and Alerts

It’s pointless collecting logs if the data isn’t translated to action: notifications keep security analysts ahead of ongoing threats before attackers are able to exploit its weaknesses. Instead of navigating through extensive volumes of raw data, SIEM alerts offer a targeted and prioritized perspective on potential threats. They accentuate events demanding immediate attention, streamlining the response process for security teams.

SIEM alerts are classified based on their severity and significance.

Some of the most common alert triggers are:
  • Multiple Failed Login Attempts: Triggered by numerous unsuccessful login tries from a single source, this alert is vital for detecting potential brute-force attacks or unauthorized access attempts.

  • Account Lockouts: The culmination of failed login attempts, an account being locked signals a potential security threat. This alert helps pinpoint compromised credentials or unauthorized access attempts.

  • Suspicious User Behavior: Raised when a user’s actions deviate from their usual patterns, such as accessing unusual resources or altering permissions, this alert is crucial for identifying insider threats or compromised accounts.

  • Malware or Virus Detection: SIEM alerts can identify known malware or viruses by monitoring suspicious file behavior or signatures, enabling timely prevention and minimizing potential damage.

  • Unusual Network Traffic:Triggered by abnormal amounts or patterns of network activity, like sudden increases in data transfers or connections to blacklisted IP addresses, this alert signifies potential attacks or unauthorized data exfiltration.

  • Data Loss or Leakage: Generated when sensitive data is transferred outside the organization or accessed by an unauthorized user, this alert is critical for safeguarding intellectual property and ensuring compliance with data protection regulations.

  • System or Service Downtime: Raised during disruptions to critical systems or services, this alert is essential for prompt awareness, investigation, and mitigation to minimize impacts on business operations.

  • Intrusion Detection: SIEM alerts can identify potential intrusion attempts, such as unauthorized access or exploit attempts against vulnerable systems, playing a crucial role in preventing unauthorized access and safeguarding sensitive information.
That’s a lot of alerts, and traditional SIEM tools are guilty of treating most of these with the same degree of urgency. As a result, it’s increasingly important for modern tools to stop belt-feeding alerts at overworked security staff, and start identifying which threats truly matter.

#4. Intelligent Incident Identification

In principle, SIEMs are crafted to sift through data and distill it into actionable alerts for users. Nevertheless, the presence of multiple layers of alerting and intricate configurations often leads to a scenario where users are confronted with “a stack of needles” rather than the intended objective of “finding the needle in the haystack.”

SIEMs often compromise their speed and fidelity due to the sheer attempt to be exhaustive in feature scope.

Fundamentally, these rules – set by an organization’s Security Operations Center (SOC) – pose a dual challenge. If too few rules are defined, the risk of overlooking security threats increases. On the other hand, defining an excess of rules leads to a surge in false positives. This abundance of alerts forces security analysts into a scramble to investigate numerous alerts, with the majority proving to be inconsequential. The resulting influx of false positives not only consumes valuable staff time but also heightens the likelihood of overlooking a legitimate threat amidst the noise.

For optimal IT security benefits, rules must transition from current static criteria to adaptive conditions that autonomously generate and update. These adaptive rules should continuously evolve by incorporating the latest information on security events, threat intelligence, business context, and shifts in the IT environment. Moreover, a more profound level of rules is necessary, equipped with the capability to analyze a sequence of events in a manner akin to human analysts.

Agile and razor-sharp, these dynamic automation systems swiftly identify a greater number of threats, minimize false positives, and reshape the current dual challenge of rules into a highly effective tool. This transformation enhances their capacity to safeguard both SMBs and enterprises from diverse security threats.

#5. Forensic Analysis

One knock-on effect of intelligent analysis is its ability to supercharge forensic analysis. The forensic team plays a crucial role in investigating security incidents by gathering and meticulously analyzing available evidence. Through the careful examination of this evidence, they reconstruct the sequence of events related to the crime, piecing together a narrative that provides valuable clues for ongoing analysis by crime analysts. Each element of evidence contributes to the development of their theory, shedding light on the perpetrator and their criminal motives.

However, the team requires time to become proficient with new tools and configure them effectively, ensuring the organization is well-prepared to defend against cybersecurity threats and potential attacks. The initial phase involves ongoing surveillance, necessitating a solution capable of monitoring the multitude of log data generated across the network. Envision a comprehensive 360-degree perspective akin to a circular guard sentry station.

The subsequent step involves the creation of search queries that support your analysts. In evaluating security programs, two key metrics are often considered: Mean Time to Detect (MTTD), measuring the time it takes to identify a security incident, and Mean Time to Respond (MTTR), representing the time it takes to remediate the incident after discovery. While detection technologies have evolved over the past decade, resulting in a significant drop in MTTD, the Mean Time to Respond (MTTR) remains persistently high. To address this, augmenting data from various systems with rich historical and forensic context is crucial. By creating a single centralized timeline of events, incorporating evidence from multiple sources, and integrating with SIEM, this timeline can be converted into logs and uploaded to the AWS S3 bucket of choice, facilitating a more efficient response to security incidents.

#6. Reporting, Auditing and Dashboards

Critical to any proficient SIEM solution, dashboards play an integral role in the post-aggregation and normalization stages of log data analysis. Once data is gathered from various sources, the SIEM solution readies it for analysis. The results of this analysis are then translated into actionable insights, which are conveniently presented through dashboards. To facilitate the onboarding process, numerous SIEM solutions include pre-configured dashboards, streamlining the assimilation of the system for your team. It’s important for your analysts to be able to customize their dashboards when necessary – this can lend a keen edge to human analysis, allowing rapid support to move in when compromise occurs.

How SIEM Compares with Other Tools

Security Information and Event Management (SIEM), Security Orchestration, Automation, and Response (SOAR), Extended Detection and Response (XDR), Endpoint Detection and Response (EDR), and Security Operations Center (SOC) are integral components of modern cybersecurity, each serving distinct roles. Breaking each tool’s down into its focus, function, and use case, here’s a quick overview of how SIEM compares to neighboring tools:

Focus Functionality  Use Case
SIEM Primarily centered on log and event data analysis for threat detection and compliance. Aggregates, correlates, and analyzes data to generate alerts and reports. Ideal for monitoring and responding to security incidents based on predefined rules.
SOAR Orchestration and automation of security processes. Integrates tools, automates response actions, and streamlines incident response workflows. Enhances efficiency by automating repetitive tasks, incident response, and workflow coordination.
XDR Expands beyond traditional SIEM capabilities, integrating data from various security tools. Provides advanced threat detection, investigation, and response across multiple security layers. Offers a more comprehensive and integrated approach to threat detection and response.
EDR Concentrates on monitoring and responding to threats at the endpoint level. Monitors endpoint activities, detects and responds to threats, and provides endpoint visibility. Essential for detecting and mitigating threats targeting individual devices.
SOC As the organizational entity overseeing cybersecurity operations, its focus is on protecting customers and keeping security processes efficient. Comprises people, processes, and technology for continuous monitoring, detection, response, and mitigation. Centralized hub managing security operations, often leveraging tools like SIEM, EDR, and XDR.
In summary, these tools complement each other, and organizations often deploy a combination to create a robust cybersecurity ecosystem. SIEM is foundational, while SOAR, XDR, EDR, and SOC offer specialized functionalities and extended capabilities in automation, comprehensive threat detection, endpoint security, and overall operations management.

How (Not) to Implement SIEM

Like all tools, your SIEM must be properly set up in order to provide the best results. The following mistakes can have a deeply detrimental effect on even high-quality SIEM software:
  • Scope Oversight: Neglecting to consider the scope of your company and the necessary data ingestion may cause the system to perform three times the intended workload, leading to inefficiencies and resource strain.

  • Lack of Feedback: Limited or absent feedback during trials and implementation deprives the system of threat context, resulting in an increased number of false positives and undermining the accuracy of threat detection.

  • “Set it and Forget it”: Adopting a passive “set it and forget it” configuration style hinders the SIEM’s growth and its ability to incorporate new data. This approach limits the system’s potential from the outset and renders it increasingly ineffective as the business expands.

  • Exclusion of Stakeholders:Failure to involve stakeholders and employees in the roll-out process exposes the system to employee errors and poor cybersecurity practices. This oversight can compromise the overall effectiveness of the SIEM.
Instead of fumbling around and hoping to bump into the best SIEM solution for your use case, the following 7 steps can ensure hassle-free SIEM implementation that best supports your security teams and customers:
  • Draft a plan that takes your current security stack, compliance requirements, and expectations.
  • Identify crucial information and data sources within your organization’s network.
  • Ensure you have a SIEM expert on your team to lead the configuration process.
  • Educate staff and all network users on best practices for the new system.
  • Determine the types of data that are most critical to protect within your organization.
  • Choose the types of data you want your system to collect, keeping in mind that more data isn’t always better.
  • Schedule time for test runs before final implementation.
Following successful SIEM implementation, security analysts are granted new insight into the application landscape they’re protecting.

Stellar Cyber’s Next-Gen SIEM Solution

Stellar Cyber’s Next-Generation SIEM is an integral component of the Stellar Cyber suite, meticulously crafted to empower lean security teams, allowing them to concentrate their efforts on delivering the precise security measures essential for the business. This comprehensive solution optimizes efficiency, ensuring that even resource-light teams can operate at scale.

Effortlessly incorporating data from various security controls, IT systems, and productivity tools, Stellar Cyber seamlessly integrates with pre-built connectors, eliminating the need for human intervention. The platform automatically normalizes and enriches data from any source, incorporating crucial context like threat intelligence, user details, asset information, and GEO location. This enables Stellar Cyber to facilitate comprehensive and scalable data analysis. The result is unparalleled insight into tomorrow’s threat landscape.

To learn more, you’re welcome to read about our Next Gen SIEM platform capabilities.

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