Decoding the double-edged sword of Generative AI

By CERT-EU , on

Generative Artificial Intelligence (AI) is here and it’s powerful. It’s promising, but also, it’s challenging many things we’ve taken for granted. We are told this revolutionary, yet overhyped technology is going to shape our future.

So – guess what? We decided to get a closer look from the perspective of cybersecurity, our field of expertise. In a position paper we are publishing today - available as CERT-EU Security Guidance 23-002 - we dived headfirst into the labyrinth of this fascinating and sometimes fearsome frontier.

What is Generative AI?

Generative AI is a subset of AI that learns from vast datasets to generate synthetic outputs. From creating realistic images to writing coherent text (albeit not always confabulation-free) or even composing symphonies, this technology is advancing at a breakneck speed. However, as the adage goes, ‘With great power comes great responsibility.’

Position paper

CERT-EU’s position paper highlights some of the potentially enormous benefits of Generative AI. Imagine a world where AI composes personalised literature, designs unique clothing, or even develops ground-breaking scientific research. The possibilities seem endless and exciting. But as we stand on the brink of this brave new world, it’s imperative to consider and prepare for the potential pitfalls.

The paper does not shy away from exposing the dark underbelly of this transformative technology. It brings to light the potential threats associated with the misuse of Generative AI - deepfakes that blur reality, automated phishing attacks, and even the threat of AI-generated propaganda. The implications of these threats are far-reaching, from personal security to international relations, and everything in between.

CERT-EU’s position paper not only paints a vivid picture of this reality but also provides a preliminary roadmap, from a cybersecurity standpoint, to navigate the tricky terrain of this powerful technology.

We need your feedback

We are by no means AI specialists. Thus, we might have missed a thing here or there in the paper. Also, given the speed of developments in the field of Generative AI, the paper might be already outdated by the time it falls in your hands. So please send us your constructive feedback to to help us correct our mistakes and improve the paper for the benefit of all, as we all learn and understand more about large language models, transformers, and what have you.

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