Penetration Testing

Security analyst reviewing an attack path validation dashboard beside critical vulnerability findings
Cybersecurity

When a “Critical” Vulnerability Isn’t Your Real Problem

A vulnerability scanner is very good at one thing: telling you that something is broken. It is much less good at telling you whether that broken thing actually matters — whether an attacker sitting outside your network could ever reach it, use it, and turn it into a foothold worth having. That gap between “this exists” and “this is dangerous” is where a growing number of security teams are now focusing their attention, and it’s reshaping how penetration testing itself gets done.

Security analyst reviewing autonomous AI pentesting results on a laptop dashboard
Artificial Intelligence

Why Security Teams Are Pulling Back from Autonomous AI Pentesting

A year ago, nearly one in three security professionals believed that fully autonomous AI systems could handle their organization’s penetration testing needs. Today, that number has collapsed to just 9%. The speed of that reversal is telling — not because AI-powered security tools have stopped improving, but because the gap between what they were marketed to do and what they actually deliver in practice has become impossible to ignore.

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