Arkose Labs announced Brett Johnson, a former cybercriminal, identity thief, and hacker has joined the company as Chief Criminal Officer.
Johnson stepped away from a life of cybercrime and now devotes his career to working with enterprises to help deter fraud.
“We’re on a mission to create an online environment where all consumers are protected from malicious activities, by undermining the very thing that fraudsters are going after – a profitable return on their attacks,” said Arkose Labs Founder and CEO Kevin Gosschalk. “We have a clear and distinct objective – to increase the costs of attacks so that they aren’t worth the resources bad actors are putting into them. To that end, fresh intelligence is key, and Brett’s expertise is in identifying and collecting that type of information.”
In this new role, Johnson will help shape intelligence-gathering strategies that result in unique and timely insights to help make fraud efforts less lucrative for bad actors. His hands-on education, practical experiences, and real-world knowledge from his life as a cybercriminal provide the Arkose Labs customer base even more information about fraudsters’ tactics and motivations.
One of the world’s top experts on cybercrime, identity theft, fraud and cybersecurity, Johnson gained wisdom by building the first organized cybercrime community, Shadowcrew, a precursor to today’s Darknet Markets, that laid the foundation for the way modern cybercrime channels still operate today. After being convicted of 39 felonies and serving 7.5 years in federal prison, Johnson stepped away from a life of crime to help individuals and companies protect themselves from the type of person he used to be.
This engagement complements Arkose Labs’ ongoing commitment to its customers’ successes and heightens the company’s focus on sourcing new information and data as an advantage over fraudsters.
“When you know what motivates fraudsters, you can stop them,” said Johnson. “I see this opportunity as a ‘1+1 = 3’ situation, combining more intelligence with world-class technology and a robust dataset to stop fraudsters. This approach identifies the threats already out there as well as threats that are coming down the pike; it’s how we’re going to disrupt the ROI models of even more fraudsters.”