As cybersecurity attack vectors evolve, security logging and monitoring are becoming even more important. Effective logging and monitoring enables organizations to detect and investigate security incidents quickly. Cloud-based attackers are getting more sophisticated, and often rely on stolen credentials to escalate privileges and move laterally within corporate IT networks. Many do so undetected, which is why modern IT systems require a watchful eye on log data to detect suspicious activity and inform incident response efforts.

In cybersecurity, it's a big challenge to handle diverse data formats across various platforms. The Open Cybersecurity Schema Framework (OCSF) aims to address this by standardizing data security formats and simplifying the process of threat hunting. Major players like IBM, AWS and others are working together to standardize data with this open-source project, emphasizing its importance.

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.