Unlocking the Power of Amazon Security Lake for Proactive Security

Introduction

It’s no secret that security is one of the main challenges of application development and modernization. It plays a main role not only in how we build our applications, but also in how we maintain them.

There are many ways to protect our applications, from the way we write our code to the way we deploy it. But all these different approaches meet the same challenge: How do we use data to identify real security incidents and, if they already occurred, how do we prevent them from happening again?

Achieving this in modern applications often goes beyond traditional security boundaries. Security practitioners must not only understand core security principles, but also how applications are built, how they function, and how data flows through them.

There is access to rich data including application logs, usage telemetry, and relationships between resources. However, the challenges lie not in collecting it, but in translating diverse data formats into a common language and surfacing actionable insights amid the noise of everyday application behavior.

This article explores how those insights can be used to detect real security incidents and prevent them from happening again.

What is Amazon Security Lake?

Amazon Security Lake is trying to solve these challenges by making fragmented security logs and data into a centralized data lake system for a better visibility, searching, investigation, and consolidation. It offers a way to collect, store and analyze data from different regions and sources, including AWS services such as Amazon EKS, AWS Security Hub, Amazon Route53, AWS WAF, and third-party sources such as SaaS providers and on-premises alternatives. This helps to identify security incidents quicker and to prevent them from happening again, providing security operations (SecOps) teams with one place where they can find all the relevant information needed to identify security incidents in the cloud infrastructure.

One of the biggest challenges in monitoring cloud application logs is normalizing the data into a unified schema based on Open Cybersecurity Schema Framework (OCSF), a vendor-agnostic framework allowing for analysis and correlation with a common language, often requiring complex parsing and data pipelining processes.

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