Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Six months ago, the question, “Which is your preferred AI?” would have sounded ridiculous. Today, a day doesn’t go by without hearing about “ChatGPT” or “Bard.” LLMs (Large Language Models) have been the main topic of discussions ever since the introduction of ChatGPT. So, which is the best LLM? The answer may be found in a surprising source – the dark web. Threat actors have been debating and arguing as to which LLM best fits their specific needs.

As the world experiences the AI gold rush, organizations are increasingly turning to enterprise AI solutions to gain a competitive edge and unlock new opportunities. However, amid the excitement and potential benefits, one crucial aspect that must not be overlooked is data security — in particular, protecting against adversarial attacks and securing AI models. As businesses embrace the power of AI, they must be vigilant in safeguarding sensitive data to avoid potential disasters.

AI has become a hot topic thanks to the recent headlines around the large language model (LLM) AI with a simple interface — ChatGPT. Since then, the AI field has been vibrant, with several major actors racing to provide ever-bigger, better, and more versatile models. Players like Microsoft, NVidia, Google, Meta, and open source projects have all published a list of new models. In fact, a leaked Google document makes it seem that these models will be ubiquitous and available to everyone soon.

We recently published a blog post detailing how threat actors could leverage AI tools such as ChatGPT to assist in attacks targeting operational technology (OT) and unmanaged devices. In this blog post, we highlight why healthcare organizations should be particularly worried about this.

I’m Peter Wrenn, my friends call me Pete! I have the pleasure of being the moderator of the Tines Technical Advisory Board (TAB) which is held quarterly. In it, some of Tines’s power users engage in conversations around product innovations, industry trends, and ways we can push the Tines vision forward — automation for the whole team. Well, that’s the benefit to our customers and Tines.

Artificial Intelligence (AI) has the potential to transform our industry. At Splunk, we see it as a catalyst for driving digital resilience — a way to accelerate human decision making in service of incident detection, investigation and response.

AI-related security risk manifests itself in more than one way. It can, for example, result from the usage of an AI-powered security solution that is based on an AI model that is either lacking in some way, or was deliberately compromised by a malicious actor. It can also result from usage of AI technology by a malicious actor to facilitate creation and exploitation of vulnerabilities.