Establishing a proactive security posture involves a data-driven approach to threat detection, investigation, and response. In the past, this was challenging because there wasn't a centralized way to collect and analyze security data across sources, but with Amazon Security Lake it is much simpler. Whether you're a security company improving and refining your threat intelligence for customers, or you're investigating security threats within your own environment, there are a few important things you need to know. This blog will cover the tools, frameworks and data types you'll need to threat hunt in Amazon Security Lake.

Developing a proactive security strategy can potentially save an organization millions of dollars per year. According to IBM, the average cost of a data breach in 2023 added up to a staggering $4.45 million, up 15% over the last three years. This is especially true for cloud-native environments, which face unique security challenges due to their dynamic nature. Instead of waiting to respond to cybersecurity incidents after they happen, it's much better to embrace a proactive approach, and prevent them in the first place.

Establishing an effective cyber threat hunting program is among the top priorities of enterprise security leaders seeking a proactive approach to detecting and counteracting potential threats. Furthermore, implementing a proactive threat hunting program, security teams that leverage formalized frameworks or threat hunting methodologies are far more likely to detect vulnerabilities or in-process malicious activities in their environments than those that do not. However, data from a 2023 threat hunting survey revealed that while 73% of organizations have adopted a defined threat hunting framework, only 38% actually follow it.

Modern data-driven organizations are synergizing operations observability, business intelligence, and data science with digital business observability programs that break down data silos, increase productivity, and drive innovation. Digital business observability combines IT and business data with cutting-edge data science techniques, enabling deeper analysis and unlocking valuable insights that propel innovation across use cases from sales and marketing to product design and financial operations.