Increasingly, companies are becoming aware of the importance of building threat detection and hunting capabilities that avoid putting their businesses at risk. Now more than ever, when it comes to both protecting enterprise cybersecurity and delivering effective IT security solutions and services, organizations and MSPs can no longer simply act when cyberattacks occur, but long before they even pose a threat.
In recent months, we’ve seen a sharp rise in software supply chain attacks that infect legitimate applications to distribute malware to users. SolarWinds, Codecov and Kesaya have all been victims of such attacks that went on to impact thousands of downstream businesses around the globe. Within minutes of these high-profile attacks making headline news, CEOs often ask: “Should we be concerned? How is it impacting us? What can we do to mitigate risk?” .
As a (fairly) new member of Splunk’s Threat Research team (STRT), I found a unique opportunity to train machine learning models in a more impactful way. I focus on the application of natural language processing and deep learning to build security analytics. I am surrounded by fellow data scientists, blue teamers, reverse engineers, and former SOC analysts with a shared passion and vision to push the state of the art in cyber defense.