Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

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.

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.

Healthcare data security protects patient records from cyber threats and unauthorized access. The increasing use of electronic health records raises concerns about data breaches. Organizations must follow strict security protocols to ensure patient safety and regulatory compliance. Healthcare data security is more critical than ever as healthcare systems integrate more digital tools. As risks grow, security measures become increasingly essential.

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.

We are over the moon to share that BlueVoyant has been awarded the Microsoft Worldwide Security Partner of the Year, demonstrating our leading-edge cyber defense capabilities and our strong partnership with Microsoft. We have also been recognized as the Microsoft United States Security Partner of the Year for the third time, and the Microsoft Canada Security Partner of the Year for the first time.

Cybersecurity moves fast, and the latest threats to reach organizations worldwide are being built on the back of artificial intelligence (AI) models that spit out accurate code, realistic messages, and lifelike audio and video designed to fool people. But as headline-grabbing as AI-based attacks appear to be, they aren’t driving the most breaches globally. That would be BEC attacks, in which attackers leverage stolen access to a business email account to create a scam that results in financial gain.