Large Language Models (LLMs) are advanced artificial intelligence systems that understand and generate human language. These models, such as GPT-4, are built on deep learning architectures and trained on vast datasets, enabling them to perform various tasks, including text completion, translation, summarization, and more. Their ability to generate coherent and contextually relevant text has made them invaluable in the healthcare, finance, customer service, and entertainment industries.

In today's digital landscape, Application Programming Interfaces (APIs) play an important role in driving innovation. They allow teams to integrate new applications with existing systems, reuse code and deliver software more efficiently. But, APIs are also prime targets for hackers due to their public availability and the large amounts of web data they transmit. API vulnerabilities can lead to unauthorized access, data breaches, and various other forms of attacks.

Data anonymization is transforming data to prevent the identification of individuals while conserving the data's utility. This technique is crucial for protecting sensitive information, securing compliance with privacy regulations, and upholding user trust. In the context of LLMs, anonymization is essential to protect the vast amounts of personal data these models often process, ensuring they can be utilized without compromising individual privacy.

From chatbots like ChatGPT to the large language models (LLMs) that power them, managing and mitigating potential AI vulnerabilities is an increasingly important aspect of effective cybersecurity. Kroll’s new AI insights hub explores some of the key AI security challenges informed by our expertise in helping businesses of all sizes, in a wide range of sectors. Some of the topics covered on the Kroll AI insights hub are outlined below.

OpenAI has reported launching its latest flagship model, GPT-4o, alongside a suite of advanced tools now available to free ChatGPT users. This move aligns with OpenAI's mission to advance AI technology and make it accessible and beneficial to everyone.

In the rapidly evolving fields of large language models (LLMs) and machine learning, new frameworks and applications emerge daily, pushing the boundaries of these technologies. While exploring libraries and frameworks that leverage LLMs for user-facing applications, we came across the Vanna.AI library – which offers a text-to-SQL interface for users – where we discovered CVE-2024-5565, a remote code execution vulnerability via prompt injection techniques.

Modern organizations know that protecting their data is absolutely critical. That’s where cloud security compliance comes in. Satisfying regulatory standards helps organizations protect against unauthorized access and data breaches, as well as other security incidents. Beyond protecting data, compliance also protects organizations from the legal implications and financial effects of attacks.