We started WitFoo because we were moved by the pain we were seeing on the faces of our customers in previous endeavors. We knew that there had to be fundamental changes to how security software supported the craft. We decided we would study, listen and follow the needs of our front line investigators. We would build what they need to win against adversaries and to communicate with their broader business.
One of the areas we research heavily at WitFoo is how to reduce the number of investigations our customers have to perform each day. Internally, we call this the “n” problem. Another area of focus is how to reduce the amount of time our customers spend on each investigation. We refer to this as the “t” problem. The lower we drive n and t, the more work our customers can accomplish each day.
Better detection mechanisms through algorithms (code) & machine learning (pattern recognition) are valuable tools to the human responders. Playbook Automation can reduce the routine and certain tasks an analyst must perform so she can focus on what is important.
Playbook automation collects data from different security and logging tools and makes decisions on behalf of the incident responder.
Computer scientists love the idea of artificial intelligence (AI). It is the centerpiece of many mainstream science fiction works. It’s also a preferred buzzword of lazy vendors and marketers. Until computers can convince (trick) a reasonable human being that they are living beings (Turing test) all claims of AI are misleading at best. In this installment, I won’t debunk the types of claims of AI. We will examine the difference between how computers and humans think and the implications of the differences.
When I was learning how to troubleshoot and repair electronics in the Navy, I would sometimes challenge one of the instructors on how something worked. If I delved into a complicated subject I was often told it worked on “FM” which meant f***ing magic. That rarely stopped me however, and I often found the concepts were not overly complicated, just not directly relevant to my training.
There is some FM in information security that I’d like to demystify as we examine how tools can enable and not hinder the craft. We’ll examine algorithms and machine learning in this installment.
Cybersecurity Incident Response has only been a part of human history for a couple of decades. Over the short course of time, industry leaders, analysts and vendors have put a heavy focus on the importance of technology solving problems within the craft. In this series, we will examine the preeminent importance of the craftsman over his tools and the role tools should play in making the world safer.
