Overview

Effective log management and collection, crucial for cybersecurity, enhance threat detection, incident analysis, and compliance through a comprehensive approach that includes gathering logs from various sources and managing them via versioned, and scalable systems. Addressing challenges such as data volume and diverse formats, this practice requires innovative tools, skilled personnel, and regular audits, forming the backbone of a robust security framework capable of navigating the complexities of a dynamic cyber environment.

The 3 C’s

The importance of the 3 C’s — Comprehensive, Centralized, and Consistent — empowers detection engineers to have a holistic, efficient, and adaptive approach to security, enhancing threat detection and analysis, incident investigation, and compliance across diverse and evolving environments.

Comprehensive Collection: Collect logs from all relevant sources within your environment. This can include but aren’t limited to; on-prem, cloud infrastructure, EDR, SaaS Applications, and build logs.

• Volume of Data: The sheer volume of log data can be overwhelming, making it challenging to store, process, and analyze effectively.

  • Leverage projects such as LogSlash to reduce log volume.

    
    

Centralized Log Management: Store logs in a centralized location to facilitate easier access, analysis, and correlation. Centralized log management systems also help in securing log data.

• Isolated: Security logs should be stored in an isolated fashion with minimal user access, leveraging only programmatic access to routine activity such as metrics gathering.

• Cheap, Scalable, Flexible: Logs can grow exponentially in a short amount of time, log storage should be inherently cheap and scalable.

  • AWS S3 is a no-brainer to me.

• Ingestion-as-code: Different systems and applications will require custom code to ingest log data.

  • Leverage Terraform and Github to maintain and version control custom ingestion code.

Consistent Log Format: Standardizing log formats across different systems, when possible, aids in analysis and correlation. This can be achieved through log normalization.

• Extract, Transform, Load: Different systems and applications often produce logs in various formats, complicating the process of normalization and correlation.

  • Leverage projects such as Substation or Airbyte can aid in reducing complexity.

• Data Contracts: Implement data quality checks to ensure data adhere to standards before causing havoc downstream.

  • Leverage projects such as Soda to ensure data quality standards are being met.

Other Thoughts

• Archiving: Implement archiving strategies to retain logs for the required duration.

• Skilled Personnel: Effective log analysis requires skilled personnel. One of the foundations of a good detection engineer is being intimate with the data thats being collected. I highly recommend reviewing the Event Maturity Matrix (EMM).

• Regular Audits and Reviews: Periodically review log management policies and practices to ensure they are effective and comply with evolving compliance requirements.