Ethical Hacking News
AI is transforming the way security professionals work, but it's not a replacement for human judgment and creativity. Instead, it's a tool that needs to be understood and harnessed to achieve better outcomes. By building or tuning their own AI-assisted workflows, security professionals can regain influence over the logic shaping their environment and make more informed decisions.
Ai is not a replacement for human judgment and creativity, but a tool that needs to be understood and harnessed. Security teams should build or tune their own AI-assisted workflows to counterbalance blind spots. Ai can remove friction and raise velocity in security work by automating routine tasks. Developing capabilities with ai requires mapping existing operations, engaging with systems, automating tasks, building ML literacy, and participating in community learning.
AI is changing the way security professionals work, but it's not a replacement for human judgment and creativity. Instead, it's a tool that needs to be understood and harnessed to achieve better outcomes.
The use of AI in cybersecurity has become widespread, with most security products incorporating some form of "intelligent" decision-making. However, this intelligence often lives behind a curtain, and vendors protect their models as proprietary IP. This means that security teams can only see the output, not the underlying logic or reasoning.
To counterbalance these blind spots, security professionals should build or tune their own AI-assisted workflows. By designing small AI utilities, they can determine what data the model learns from, what it considers risky, and how it behaves. This allows them to regain influence over the logic shaping their environment and make more informed decisions.
AI can also remove friction and raise velocity in security work. Complex JQ filters, SQL queries, and regular expressions are common translation steps that slow down investigations. AI can take these steps out of the way, allowing security professionals to focus on what they're trying to investigate rather than the mechanics of the query language.
In practice, this means being able to express intent in plain English and having the model produce most of the code. The model gets you most of the way there, but it's up to you to close the remaining gap with judgment and technical literacy.
To start developing these capabilities, security professionals can begin by:
* Mapping where AI already operates in their environment
* Engaging actively with their AI systems
* Automating one weekly task using Python plus an AI model
* Building light ML literacy
* Participating in community learning
By following this approach, security professionals can turn AI from a disruptive technology into a strategic advantage. They'll learn to understand the tool and guide it with intent, becoming more capable and necessary in their roles.
Related Information:
https://www.ethicalhackingnews.com/articles/AI-in-Cybersecurity-From-Disruptive-Technology-to-Strategic-Advantage-ehn.shtml
https://thehackernews.com/2025/12/chopping-ai-down-to-size-turning.html
Published: Wed Dec 3 07:12:51 2025 by llama3.2 3B Q4_K_M
