Hackers use fake ChatGPT apps to push Windows and Android malware, attackers flood NPM repository with over 15,000 spam packages containing phishing links, and New Stealc malware emerges with a wide set of stealing capabilities.

Since ChatGPT was released by OpenAI last year, large language models like it have gone viral. Cheerleaders extol these AI models as the future of work, maybe the best thing to happen since the invention of the internet, or as the invention that changes everything. Detractors point to their gaffs, failures, and “hallucinations.” Both Google and Microsoft have been embarrassed in the last several days by the outputs of their respective chatbots.

With the launch of ChatGPT, concerns have been growing around the use of AI in phishing. The concerns are founded: AI can write phishing emails. It’s not the only tool in a hacker’s toolkit either - cybercriminals can use many different technologies to build a phishing campaign and send phishing emails. Many, like chatbots, are widely available for consumer and business use.

Can OpenAI ChatGPT become a contributor for an open source project like Falco? Is this the end of GitHub Copilot? ChatGPT is SO trendy that I overheard my grandma talking about it to her friends the other day. We’re seeing more and more uses of this AI for real world applications. That made us think… Falco, the first runtime security project to join CNCF as an incubation-level project, needs contributors.

OpenAI's ChatGPT chatbot has been a phenomenon, taking the internet by storm. Whether it is composing poetry, writing essays for college students, or finding bugs in computer code, it has impressed millions of people and proven itself to be the most accessible form of artificial intelligence ever seen.

In Calligo’s latest Beyond Data podcast, co-hosts Sophie Chase Borthwick and Tessa Jones are joined by Alexander Visheratin, Artificial Intelligence Engineer at Beehive AI. Here we explore some of the episode’s highlights; the importance of Natural Learning Processing (NLP) and the pros and cons of output produced by examples like OpenAI’s ChatGPT-3.

We’ve now seen a number of different use cases for ChatGPT from marketing, sales, software development and others including from the security field. This platform continues to dominate most of the headlines and impress based on how it’s able to handle questions and topics from various backgrounds.

In recent years, the world of artificial intelligence (AI) has seen a significant increase in the use of language models. ChatGPT, a language generation model developed by OpenAI, has been making waves in the news with its ability to process large amounts of data, which can be used to train machine learning models and to test them. One feature that’s grabbed headlines is its ability to write code and provide feedback on the accuracy and efficiency of code.

With the rise of OpenAI’s GPT-3, ChatGPT and Codex products, as well as GitHub’s CoPilot and numerous competitors, today we’re seeing developers experimenting with AI to help augment their development workflows. While at first these efforts focused on more commonly used programming languages, such as Javascript and Python, the AI use cases are now expanding to Infrastructure-as-Code (IaC) configurations.

Even if you’ve been living under a super-sized rock for the last few months, you’ve probably heard of ChatGPT. It’s an AI-powered chatbot and it’s impressive. It’s performing better on exams than MBA students. It can debug code and write software. It can write social media posts and emails. Users around the globe are clearly finding it compelling. And the repercussions – good and bad – have the potential to be monumental.

Artificial Intelligence (AI) is revolutionizing the financial services industry, known as fintech. From improving customer experience to reducing operational costs and mitigating risks, AI is having a significant impact on fintech. In this blog, we will explore the top 10 ways AI is being used in fintech.

With news headlines like “A massive ransomware attack hit hundreds of businesses” becoming common, concern about malware has never been higher. High-profile examples of malware like DarkSide, REvil have been profiled so many times that not only cybersecurity professionals are on edge — every organization that has on-premises or in-the-cloud workloads is concerned.