Root Cause Analysis
Demanding AWS customers have multiple AWS accounts, collect data from multiple sources, and simple searches based on regular expressions are not enough to conduct in-depth analysis of suspected security-related events. Today, when a security issue is detected, such as compromised credentials or unauthorized access to a resource, security analysts cross-analyze several data logs to understand the root cause of the issue and its impact on the environment. In-depth analysis often requires scripting and ETL to connect the dots between data generated by multiple siloed systems. It requires skilled data engineers to answer basic questions such as “is this normal?”. Analysts use Security Information and Event Management (SIEM) tools, third-party libraries, and data visualization tools to validate, compare, and correlate data to reach their conclusions. To further complicate the matters, new AWS accounts and new applications are constantly introduced, forcing analysts to constantly reestablish baselines of normal behavior, and to understand new patterns of activities every time they evaluate a new security issue.
Amazon Detective makes it easy to analyze, investigate, and quickly identify the root cause of potential security issues or suspicious activities. Amazon Detective automatically collects log data from your AWS resources and uses machine learning, statistical analysis, and graph theory to build a linked set of data that enables you to easily conduct faster and more efficient security investigations.
Amazon Detective is a fully managed service that empowers users to automate the heavy lifting involved in processing large quantities of AWS log data to determine the cause and impact of a security issue. Once enabled, Detective automatically begins distilling and organizing data from AWS Guard Duty, AWS CloudTrail, and Amazon Virtual Private Cloud Flow Logs into a graph model that summarizes the resource behaviors and interactions observed across your entire AWS environment.
Amazon Detective uses machine learning models to produce graphical representations of your account behavior and helps you to answer questions such as “is this an unusual API call for this role?” or “is this spike in traffic from this instance expected?”. You do not need to write code, to configure or to tune your own queries.