Ahead of the upcoming AI Safety Summit to be held at the UK’s famous Bletchley Park in November, I wanted to outline three areas that I would like to see the summit address, to help simplify the complex AI regulatory landscape. When we start any conversation about the risks and potential use cases for an artificial intelligence (AI) or machine learning (ML) technology, we must be able to answer three key questions.
As organizations continue to believe the malicious use of artificial intelligence (AI) will outpace its defensive use, new data focused on the future of AI in cyber attacks and defenses should leave you very worried. It all started with the proposed misuse of ChatGPT to write better emails and has (currently) evolved into purpose-built generative AI tools to build malicious emails. Or worse, to create anything an attacker would need using a simple prompt.
If you are searching for ways to actualise benefits from cybersecurity AI tools or want to find out what AI tools will really make a difference in your SOC, you’re not alone. A World Economic Forum survey last year showed that almost half of all security leaders thought AI and machine learning would have the greatest influence on stopping cyber attacks and malware in the next two years. And that was before ChatGPT started an AI frenzy.
As the world embraces the power of artificial intelligence, large language models (LLMs) have become a critical tool for businesses and individuals alike. However, with great power comes great responsibility – ensuring the security and integrity of these models is of utmost importance.
In an evolving era of Artificial Intelligence (AI) and Large Language Models (LLMs), innovative tools like GitHub's Copilot are transforming the landscape of software development. In a prior article, I published about the implications of this transformation and how it extends to both the convenience offered by these intelligently automated tools and the new set of challenges it brings to maintaining robust security in our coding practices.
The intersection of privilege escalation and identity is taking on new dimensions with the advent of Artificial Intelligence (AI). As AI becomes increasingly integrated into our lives, it both challenges and reinforces existing notions of privilege and identity. In this blog, we'll explore what privilege escalation means in the context of AI and how it influences our understanding of personal and societal identities.
It is common knowledge that when it comes to cybersecurity, there is no one-size-fits all definition of risk, nor is there a place for static plans. New technologies are created, new vulnerabilities discovered, and more attackers appear on the horizon. Most recently the appearance of advanced language models such as ChatGPT have taken this concept and turned the dial up to eleven.
