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.
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How Does SIEM Work?
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
#1. Log Management
- 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.
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
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
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.
#4. Intelligent Incident Identification
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
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
How SIEM Compares with Other 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. |
How (Not) to Implement SIEM
- 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.
- 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.
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.