Machine Learning Security for DC Comics

dccomics

4M

log messages processed a day

10,000

suspicious requests identified

DC Entertainment is home to the iconic brands DC Comics, Vertigo, and MAD Magazine. Along with chronicling the adventures of Superman, Batman, Green Lantern, Wonder Woman, The Flash, and many more, DC houses the creative division charged with strategically integrating its content across Warner Bros. Entertainment and Time Warner.

BUSINESS PROBLEM

DC Entertainment serves up to 2 million requests per day and during events like San Diego Comic Con that number can be up to 4x higher. This increased traffic can adversely affect site performance. To make it worse, DC Entertainment site is routinely crawled by third parties looking for security vulnerabilities or new leaks ahead of announcements. Sorting through this traffic to identify malicious traffic is a monumental task to accomplish at the best of times, and an impossible task in anything near real time.

SOLUTION

Metal Toad set up an AWS data pipeline using an SNS trigger to start a Lambda job when CloudFront logs were stored in S3. The Lambda parsed the logs, removing unnecessary columns. Data scientists identified SageMaker’s IPInsights as a suitable algorithm and parsed several days of logs into test and training data.

The first set was pretty obviously malicious based on just looking at the query parameters, and could probably have been handled by tuning the WAF on CloudFront better. 

The second find was better. The data scientist originally thought that these second groups may be a false positive. Deeper analysis of the IP addresses found a few gems, including a few WhiteHat scanning companies. 

With this new data, Metal Toad could block problem IP addresses and ensure that DC Entertainment could stay secure for another Comic Con.

 

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