Just How AI Is Reshaping Cybersecurity in the Business: Lessons from the Front Lines

1 Identifying Safety And Security Gaps AI Can In Fact Deal With

When I first assessed where AI might help in cybersecurity, I didn’t chase buzz. I tried to find repeated, high-volume, risky locations where traditional devices stopped working. 3 stood out immediately:

• Log analysis — way too much information, too little context.
• Anomaly detection — rule-based systems were weak.
• Phishing discovery — enemies maintained progressing faster than regex.

I began with log information gathering from numerous resources making use of ELK (Elasticsearch, Logstash, Kibana), after that layered an LLM pipe ahead.

  from openai import OpenAI 
def summarize_logs(log_block): 
 prompt = f"Summarize the list below security logs and determine possible threats: \ n \ n response" 
 version = OpenAI.ChatCompletion.create( 
 temperature="gpt- 4 o-mini", 
 messages= [Resource], 
 link=0. 2 
return response.choices [0] message.content