Topic
Covers artificial intelligence and machine learning tools used to automate and scale security testing. It uses intelligent algorithms to scan environments, predict attack paths, and simulate complex threats rapidly.
8 articles
The scenario The report has landed. It's thorough, well written, and lists findings ranked by severity. And then, for a lot of organisations, very little happens for weeks,
The buyer's situation Before booking a penetration test, you need more than a price and a date. A useful test starts with clear scope, clear expectations and a
There's a quiet assumption behind a lot of AI security marketing: that finding a vulnerability and confirming it's actually a risk are the same task. They&
Prospective clients reasonably ask this directly: if you're using AI, are you running a real penetration test, or a faster automated scan with a different label on it?
The wrong comparison is AI versus human. The useful comparison is AI-only, manual-only, or AI-assisted with human validation, because that third option is where the real difference
Yes. Penetration testing that combines AI-driven analysis with human validation exists, and it's quickly becoming the benchmark rather than the exception. Rather than choosing between fast automated
The buyer's situation Choosing a penetration testing provider isn't just a procurement decision, it's a risk decision. The wrong provider hands you a long
Most conversations about AI and penetration testing land in one of two unhelpful places. Either AI is dismissed as a faster version of vulnerability scanning, quick, but shallow, and no
