Best practices to evaluate LLM-based AI security tools | TechTarget
The cybersecurity industry hasn't had many calm moments in the last 25 years, but the advent of LLM-based AI has ushered in a new level of threat. LLM-based AI has enormously accelerated the slowest, hardest and most specialized parts of the cyberattack lifecycle: discovering vulnerabilities and developing exploits to take advantage of them. It is also now driving new scales and scopes of social engineering attacks.
LLM-based AI is also now being bent to the defense of enterprise IT environments, joining machine-learning-based AI in a broad range of tools. Let's take a look at the questions CISOs and other security leaders must ask potential vendors and service providers when comparing and selecting such tools.
Require an open-door policy
First and foremost, those adopting an LLM-type AI in cybersecurity should demand that AI not be a black box. It should be what is known as explainable AI, which enables...
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