You have a lot of SIEM data to manage. How can you do it efficiently?

A lot of SIEM to manage for me means an MSSP environment and in that case the first step is a vision of standarization. Define standard log sources, standard use cases, standard health checks, standard reports, etc. This will be more than enough for the 80% of stakeholders. Then you only would need to deal with 20% of custom requirements and use them to update your standard baselines

Find a really good security partner that provides excellent continuous improvement services. Don’t focus on the implementation as most SiEM/SOC providers are good at delivery, the key is to focus on how they will improve triage activities, logging and ingestion, trend analysis,, threat hunting, reporting etc. Furthermore, having a security partner doesn’t meant that you don’t need to have an internal team - context and coverage is key.

Every company has a limited list of truly unacceptable events for business: production stoppages for a certain period, withdrawals from accounts above a certain amount, attacks that could lead to human casualties or environmental harm. This requires smart investments in security tools that deliver results. If a company's cybersecurity is focused on measurable benefits, the development of its digital systems will not be a risk to the business.

Pienso que en particular para el uso de un SIEM, menos siempre es más, trata de antes de ponerte a configurar las reglas de correlación, piensa en que quieres controlar, luego de eso ordena tu infraestructura por servicio, pon un ranking de importancia por cada servicio y comienza por una regla a la vez, hay varios proveedores que te dicen como hacer eso, finalmente piensa en cual es tu capacidad de respuesta y ajusta tu tecnología a esa capacidad. Luego es abrir la llave poco a poco para no terminar todo mojado :)

Another key consideration is to identify your crown jewels, the most critical assets or processes to be onboarded to the SIEM service, thereby prioritizing the data sources for monitoring.

For SOC operations one of the main issues is attrition and fatigue, besides the technical coverage of visibility, which requires the introduction of automation for L1. Many customers, to avoid this challenge opt for managed services or optimizing automation (SOAR) to minimize MTTD/MTTR.

Uno de los factores importantes a considerar en la evaluación de los recursos es sin duda el saber con certeza la cantidad de personas que administrarán la infraestructura tecnológica que existe en el backend como aquellos consumidores finales que generarán las consultas, optimización y visualización de los datos concentrados en el SIEM. Sin embargo otro factor que debe ser considerado en la etapa de la evaluación de recursos es conocer o al menos dimensionar el volumen de eventos por segundo que serán ingestados por esta herramienta tanto en un corto, mediano y largo plazo. Ya que esto también nos puede ayudar a dimensionar los requerimientos presentes y futuros tanto de personal como de hw que soporte a la plataforma.

In many organizations, SIEM data management often centers on collecting extensive details from asset inventories and relying on security operations, either through managed services or internal SOC. Yet, it's crucial to assess the 'detection value' of each event type logged in the SIEM. To efficiently handle SIEM data, teams should dedicate time to evaluate which events and device categories merit logging for effective threat correlation. Additionally, leveraging enterprise security tools like EDR/XDR, which perform SIEM functions, streamlines the process. Focusing on logging threat-related data rather than all end device logs proves more efficient.

If you opt for a managed SIEM service, you still maintain the ultimate responsibility. You need to ensure that the SIEM service adapts to your current organization’s needs, including meeting the applicable legal and regulatory requirements.

Efficiently managing vast SIEM data is like orchestrating a symphony from a multitude of notes. Prioritize and categorize data to focus on the most critical information, like to a conductor emphasizing key musical phrases. Implement automation and machine learning to sift through data swiftly. Regularly audit and prune your data, removing outdated or irrelevant information to keep your system streamlined, much like pruning a tree for healthier growth. Integrate your SIEM with other security tools for a holistic security perspective, ensuring no note is missed in your symphony of data. Lastly, empower your team with ongoing training in the latest SIEM techniques, turning them into proficient players in your cybersecurity orchestra.

One major component not mentioned above to consider is storage and retention. Depending on if you are a regulated industry and what kind of events need to be captured. Examples are NIST recommendations, Healthcare and Financial Industry storage and retention periods (SOX compliance for example). The ability to store and retrieve data (and also use data analytics for long term log storage) are key architectural design considerations regardless what SIEM. How to get the logs to the siem and what to do after it! ??

SIEM is remarkable for its ability to detect and respond flexibly to cybersecurity requests for the customer. These systems should provide a flexible ability to create detection rules with subsequent processing within the SIEM. This is interesting to companies that have an understanding of attack vectors and threats. In the absence of such understanding, it is important for the customer to receive practical expertise from the vendor. Attention should also be paid to the quality of technical support. If the vendor delays solution, their response in the "crunch time" will also be sluggish.

On-Premises SIEM:Pros: Provides full control over infrastructure and data, suitable for organizations with specific compliance requirements.Cons: Requires substantial hardware investment, maintenance, and may have scalability limitations. Cloud-Based SIEM:Pros: Offers scalability, flexibility, and potential cost savings. Allows easy access to resources and updates without on-premises maintenance.Cons: Dependence on internet connectivity and potential security concerns, especially for highly sensitive data.

In the complex landscape of SIEM, efficient data management is pivotal for robust cybersecurity because "Garbage in -> Garbage out" & goal of SIEM is not to make it a compliance storage tool. Key strategies include prioritizing security-specific data to enhance accuracy and focus, the possibility of integrating SIEM with cloud storage for scalable long-term retention, establishing comprehensive data retention policies aligned with organizational and regulatory needs, and ensuring strict adherence to regulatory compliance. This multifaceted approach not only optimizes SIEM systems but also aligns data practices with industry standards, fostering a resilient and proactive cybersecurity framework.

After setting your goals and assessing your resources, start comparing various SIEM services. Evaluate them based on criteria like data collection and integration, analysis and correlation capabilities, data visualization and dashboard functionality, alert generation and prioritization, incident response and remediation, compliance and reporting features, scalability and performance, security and reliability, and user experience and support. Seeking reviews and testimonials from other users, and requesting demonstrations or trials from providers, can also offer valuable insights. This comprehensive approach ensures you select a SIEM service that best fits your organization's specific security requirements and operational context.

Let the systems that feed your Siem do some thinking. Certain events are almost always a security event and should receive a security tag and a severity rating. This pre filtering can be used to optimize your data and make it a bit lighter to digest by the Siem.

Guidelines for optimal performance and threat detection. 1. Meticulously configure log parsing rules for accurate extraction; adapt configurations to evolving log formats and sources 2. Develop and refine custom correlation rules for your threat landscape; enhance detection accuracy while minimizing false positives 3. Regularly update monitored log sources 4. Adjust memory allocation and processing settings to optimize SIEM server performance; conduct regular audits to address processing bottlenecks 5. Encourage efficient search queries; leverage indexing and caching for faster recurrent query speeds 6. Maintain detailed documentation for all SIEM configurations

In my experience even though the siems are set up, they are not optimised correctly to an organisations requirement which in turn beats its purpose.

Optimizing and tailoring your log collection process is very important otherwise you will be wasting resources and money . Have alignment of log collections mapped to your information security policy and business need. Use logging levels on products tailored to your needs bring logging levels to an acceptable risk level.

Identify and integrate data sources comprehensively, including network devices, servers, applications, endpoints, and cloud services.Ensure that log formats are compatible and consistent for effective analysis. Define rules based on security policies, compliance requirements, and organizational needs.Apply rules to filter and categorize events, reducing noise and focusing on relevant security incidents. Implement filters to exclude irrelevant events and normalize data formats for consistency.Ensure that the SIEM can handle different log formats and normalize them for unified analysis.

When incidents are detected, it is necessary to act quickly, which is why SIEM systems are enhanced with tools that help operators reduce investigation and response times. For this, the SIEM system should have a responsive interface and automate some of the routine tasks for analysts (for example, checking false positives).

O texto oferece um guia claro e sequencial para a implementa??o eficaz de servi?os SIEM. Ao destacar a importancia da defini??o de objetivos, avalia??o de recursos, compara??o de op??es, otimiza??o da configura??o e revis?o contínua, fornece uma abordagem abrangente para ajudar as organiza??es a escolherem e operarem servi?os SIEM alinhados às suas necessidades específicas. A inclus?o de insights práticos de especialistas adiciona uma dimens?o realista ao processo, enquanto a ênfase na personaliza??o destaca a adaptabilidade essencial dessas solu??es.

Regular review and adjustment of your SIEM service settings are essential for maintaining its effectiveness. It's important to monitor the performance and health of the SIEM, addressing any issues or errors that arise. Measuring the effectiveness and efficiency of the SIEM is key to ensuring it aligns with your security objectives. Continually updating and refining rules, filters, policies, and thresholds to reflect the evolving threat landscape and security environment is crucial. By doing so, you can ensure that your SIEM service remains relevant, reliable, and a robust part of your cybersecurity strategy.

1- Do not enable all default rules, this will have negative impact on SIEM performance. 2- Follow a use case life-cycle: after enabling or creating a rule, test it , then move it to production and maintain/tune it , then disable it , if the logic or conditions are not needed any more.

Logging Level: Adjust the logging level to balance the amount of information collected. Higher logging levels may provide more detail but can also generate more data, while lower levels may miss important events. Compliance Requirements: Ensure that your data collection aligns with any regulatory or compliance requirements that your organization needs to meet. Customization: Tailor your SIEM configuration to the specific needs and risks of your organization. Customize alert thresholds and rules to match your security policies. Regular Review: Regularly review and update your data collection strategy based on the evolving threat landscape and changes in your organization's infrastructure.

It’s indeed challenging, but there are several strategies to do it efficiently: Prioritize Log Sources: Focus on key log sources related to critical assets and their potential impact. Automate Generic Processes: Use automation for Level 1 analysis. Effective Filtering: Set strong filtering rules to distinguish vital alerts from minor ones, set alerting on the most critical events/alerts. But use these minor ones for Threat hunting, in my experience sometimes these minor ones are the first signs of an attacker activity. Advanced Analytics and Threat Intelligence: Apply correlation logic for pattern recognition and anomaly detection, integrate threat intelligence for context and create relative adversaries TTP-based detection rules.

In order to efficiently handle SIEM data, it is important to establish specific objectives, give priority to pertinent data sources, standardize data, automate tasks, incorporate threat intelligence, update correlation rules, allocate resources for dependable storage, foster collaboration, offer ongoing training, and regularly assess and enhance the infrastructure.

All my peers make great points. One of the greater challenges is not only how to process the data but how much data do you need, how long do you need it for and what can you do with the data you are logging. In many cases we tend to be data hoarders and want to maintain data for a long period of time. The approach here is based on several factors: Program maturity, workforce skills, budget and industry. Taking those factors into play you can create a unique process and way to look at this data, use, process and store it effectively.