Chopping AI Down To Size: Turning Disruptive Technology Into A...
Most people know the story of Paul Bunyan. A giant lumberjack, a trusted axe, and a challenge from a machine that promised to outpace him. Paul doubled down on his old way of working, swung harder, and still lost by a quarter inch. His mistake was not losing the contest. His mistake was assuming that effort alone could outmatch a new kind of tool.
Security professionals are facing a similar moment. AI is our modern steam-powered saw. It is faster in some areas, unfamiliar in others, and it challenges a lot of long-standing habits. The instinct is to protect what we know instead of learning what the new tool can actually do. But if we follow Paul's approach, we'll find ourselves on the wrong side of a shift that is already underway. The right move is to learn the tool, understand its capabilities, and leverage it for outcomes that make your job easier.
AI is now embedded in almost every security product we touch. Endpoint protection platforms, mail filtering systems, SIEMs, vulnerability scanners, intrusion detection tools, ticketing systems, and even patch management platforms advertise some form of "intelligent" decision-making. The challenge is that most of this intelligence lives behind a curtain. Vendors protect their models as proprietary IP, so security teams only see the output.
This means models are silently making risk decisions in environments where humans still carry accountability. Those decisions come from statistical reasoning, not an understanding of your organization, its people, or its operational priorities. You cannot inspect an opaque model, and you cannot rely on it to capture nuance or intent.
That is why security professionals should build or tune their own AI-assisted workflows. The goal is not to rebuild commercial tools. The goal is to counterbalance blind spots by building capabilities you control. When you design a small AI utility, you determine what data it learns from, what it considers risky, and how it should behave. You regain influence over the logic shaping your environment.
A large portion of security work is translational. Anyone who has written complex JQ filters, SQL queries, or regular expressions just to pull a small piece of information from logs knows how much time that translation step can consume. These steps slow down investigations not because they are difficult, but because they interrupt your flow of thought.
AI can remove much of that translation burden. For example, I have been writing small tools t
Source: The Hacker News
