Jonathan Rau, a cybersecurity expert, dives into the contentious world of SIEM systems—often labeled as dead yet continually revamped. He discusses the evolution of these tools, highlighting how initial goals were hindered by complexity and a lack of skilled personnel. Rau emphasizes the importance of purposeful data analysis, warning against using data models without clearly defining the problem. The conversation also critiques the influx of cybersecurity tools, urging a return to basics and a focus on genuine business needs.
The conversation highlights SIEM's evolving nature and its ongoing relevance in security despite criticisms and emerging technologies.
Experts stress the need for security leaders to reassess their data collection practices to enhance relevance and operational efficiency.
Deep dives
The Evolution of SIEM Technology
SIEM technology has undergone significant changes over the years, leading to discussions about its current effectiveness. Initially designed to aggregate and analyze security data, many experts now view it as an 'undead' concept that continues to survive despite its limitations. As various new technologies and solutions emerged, such as cloud-native implementations and security analytics tools, the foundational purpose of SIEM seemed diluted. The conversation highlights the challenge within the security industry to balance between the cumulative tools used and the efficiency of the SIEM systems themselves.
Challenges in Security Tool Integration
The multitude of security tools currently in use has created a chaotic environment for security teams, leading to issues with data overload. With reports indicating that organizations can have dozens to even hundreds of security tools, the challenge lies in managing an overwhelming volume of telemetry and ensuring all tools effectively communicate. As security professionals continuously hunt for solutions, they often find themselves incorporating redundant tools that complicate analysis rather than streamline it. This indicates a pressing need for security leaders to reassess their toolsets and identify redundancies, potentially improving operational efficiency.
Value of Data Science in Security
The conversation emphasizes the importance of data science in enhancing security measures but points out a disconnect in its application. Security teams often struggle to understand what data is necessary for effective monitoring and incident response, leading to an inflation of irrelevant data collected. Experts urge security leaders to revisit the foundational questions regarding the purpose of their data collection practices and align tools that directly address their specific security needs. By moving away from the mentality of needing to log everything, organizations can focus on utilizing data science more effectively to enhance security posture.
Understanding The Next Steps in Security Strategy
To improve security outcomes, professionals are advised to take step back and evaluate their current practices and resources critically. This involves engaging with analysts to clarify what everyday challenges they face and tailoring the security strategy to address those specific issues. Eliminating unnecessary tools and focusing on what truly adds value to the security process is a crucial part of refining approaches. The ultimate goal is to create a streamlined security environment where communication and data relevance lead to effective responses rather than endless cycles of data analysis without actionable outcomes.
TL;DR: This week on the pod, Jonathan Rau joins to talk about SIEM. The thing we all lover to hate on, that thing that's been declared dead, and yet it's on its umpteenth incarnation. What does the future hold? Why is it still an investment organizations make? What makes it a good versus bad use-case? Tune in, find out.