LAS VEGAS -- A new open source tool looks to make monitoring AWS credentials easier and more effective for large organizations.The tool, dubbed Trailb
LAS VEGAS — A new open source tool looks to make monitoring AWS credentials easier and more effective for large organizations.
The tool, dubbed Trailblazer, was introduced during a session at Black Hat USA 2018 on Wednesday by William Bengtson, senior security engineer at Netflix, based in Los Gatos, Calif. During his session, Bengtson discussed how his security team took a different approach to reviewing AWS data in order to find signs of potentially compromised credentials.
Bengtson said Netflix’s methodology for monitoring AWS credentials was fairly simple and relied heavily on AWS’ own CloudTrail log monitoring tool. However, Netflix couldn’t rely solely on CloudTrail to effectively monitor credential activity; Bengtson said a different approach was required because of the sheer size of Netflix’s cloud environment, which is 100% AWS.
“At Netflix, we have hundreds of thousands of servers. They change constantly, and there are 4,000 or so deployments every day,” Bengtson told the audience. “I really wanted to know when a credential was being used outside of Netflix, not just AWS.”
That was crucial, Bengtson explained, because an unauthorized user could set up infrastructure within AWS, obtain a user’s AWS credentials and then log in using those credentials in order to “fly under the radar.”
However, monitoring credentials for usage outside of a specific corporate environment is difficult, he explained, because of the sheer volume of data regarding API calls. An organization with a cloud environment the size of Netflix’s could run into challenges with pagination for the data, as well as rate limiting for API calls — which AWS has put in place to prevent denial-of-service attacks.
“It can take up to an hour to describe a production environment due to our size,” he said.
To get around those obstacles, Bengtson and his team crafted a new methodology that didn’t require machine learning or any complex technology, but rather a “strong but reasonable assumption” about a crucial piece of data.
“The first call wins,” he explained, referring to when a temporary AWS credential makes an API call and grabs the first IP address that’s used. “As we see the first use of that temporary [session] credential, we’re going to grab that IP address and log it.”
The methodology, which is built into the Trailblazer tool, collects the first API call IP address and other related AWS data, such as the instance ID and assumed role records. The tool, which doesn’t require prior knowledge of an organization’s IP allocation in AWS, can quickly determine whether the calls for those AWS credentials are coming from outside the organization’s environment.
“[Trailblazer] will enumerate all of your API calls in your environment and associate that log with what is actually logged in CloudTrail,” Bengtson said. “Not only are you seeing that it’s logged, you’re seeing what it’s logged as.”
Bengtson said the only requirement for using Trailblazer is a high level of familiarity with AWS — specifically how AssumeRole calls are logged. The tool is currently available on GitHub.