Anatomy of Twitter Bots: Fake Followers
In this post, we’ll explore how fake followers operate, showing how to find an initial list of fake followers and then using this initial list to uncover a larger botnet measuring at least 12,000 accounts.
Olabode is a Data Scientist at Duo Security where he wrangles data, prototypes data-related features, and makes pretty graphs to support engineering, product management, and marketing efforts. Prior to Duo, Olabode studied usable security at the University of Florida. When he’s not at work, he spends his time exploring data involving topics such as sports analytics, relative wages and cost of living across the United States.
In this post, we’ll explore how fake followers operate, showing how to find an initial list of fake followers and then using this initial list to uncover a larger botnet measuring at least 12,000 accounts.
Visually mapping social network connections reveals patterns that may otherwise be hidden in the data. Plus, these graphs serve as compelling pieces of generated artwork. This post shows the step-by-step process to create a graph of your own social network using Gephi.
Duo Labs releases their results of a three-month long research project on identifying Twitter bots and botnets at a large scale ahead of their talk at Black Hat USA 2018, along with plans to open-source their data collection code source.
Duo Labs conducted a U.S.-census-representative survey to learn more about two-factor authentication (2FA) usage, how people learned about it, which technologies they’ve used as as a second factor, and more. Get the full report on our data here.
Google took a lot of important steps forward to improve the security of Android devices in 2016. We recap the biggest developments, including touch id and SafetyNet API improvements.
