The power of artificial intelligence (AI) and machine learning (ML) is a double-edged sword — empowering cybercriminals and cybersecurity professionals alike. AI, particularly generative AI’s ability to automate tasks, extract information from vast amounts of data, and generate communications and media indistinguishable from the real thing, can all be used to enhance cyberattacks and campaigns.

Generative AI is an exciting technology that is now easily available through cloud APIs provided by companies such as Google and OpenAI. While it’s a powerful tool, the use of generative AI within code opens up additional security considerations that developers must take into account to ensure that their applications remain secure. In this article, we look at the potential security implications of large language models (LLMs), a text-producing form of generative AI.

The NIST Artificial Intelligence Risk Management Framework (AI RMF) is a recent framework developed by The National Institute of Standards and Technology (NIST) to guide organizations across all sectors in the use of artificial intelligence (AI) and its systems. As AI continues to become implemented in nearly every sector — from healthcare to finance to national defense — it also brings new risks and concerns with it.

As large language models (LLMs) continue to push the boundaries of natural language processing, their widespread adoption across various industries has highlighted the critical need for robust security measures. These powerful AI systems, while immensely beneficial, are not immune to potential risks and vulnerabilities. In 2024, the landscape of LLM security tools has evolved to address the unique challenges posed by these advanced models, ensuring their safe and responsible deployment.

AI has long since been an intriguing topic for every tech-savvy person, and the concept of AI chatbots is not entirely new. In 2023, AI chatbots will be all the world can talk about, especially after the release of ChatGPT by OpenAI. Still, there was a past when AI chatbots, specifically Bing’s AI chatbot, Sydney, managed to wreak havoc over the internet and had to be forcefully shut down.

Published in 2023, the OWASP Top 10 for LLM Applications is a monumental effort made possible by a large number of experts in the fields of AI, cybersecurity, cloud technology, and beyond. OWASP contributors came up with over 40 distinct threats and then voted and refined their list down to the ten most important vulnerabilities.

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The cybersecurity domain mirrors the physical space, with the security operations center (SOC) acting as your digital police department. Cybersecurity analysts are like the police, working to deter cybercriminals from attempting attacks on their organization or stopping them in their tracks if they try it. When an attack occurs, incident responders, akin to digital detectives, piece together clues from many different sources to determine the order and details of events before building a remediation plan.

CrowdStrike’s mission is to stop breaches. We continuously research and develop technologies to outpace new and sophisticated threats and stop adversaries from pursuing attacks. We also recognize that security is best when it’s a team sport. In today’s threat landscape, technology collaboration is essential to deploy novel methods of analysis and defense.