To prevent prompt injection attacks when working with untrusted sources, Google DeepMind researchers have proposed CaMeL, a defense layer around LLMs that blocks malicious inputs by extracting the ...

Your LLM-based systems are at risk of being attacked to access business data, gain personal advantage, or exploit tools to the same ends. Everything you put in the system prompt is public data.

Businesses should be very cautious when integrating large language models into their services, the U.K.'s National Cyber Security Centre is warning, thanks to potential security risks. Through prompt ...

Prompt injections, the malicious commands attackers embed into content to entice LLMs to follow them, have been attackers’ go ...

Security leaders must adapt large language model controls such as input validation, output filtering and least-privilege access for artificial intelligence systems to prevent prompt injection attacks.

Emily Long is a freelance writer based in Salt Lake City. After graduating from Duke University, she spent several years reporting on the federal workforce for Government Executive, a publication of ...

Prompt injection, prompt extraction, new phishing schemes, and poisoned models are the most likely risks organizations face when using large language models. As CISO for the Vancouver Clinic, Michael ...

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“AI” tools are all the rage at the moment, even among users who aren’t all that savvy when it comes to conventional software or security—and that’s opening up all sorts of new opportunities for ...

With the ability to take control of distributed devices at scale, HalluSquatting has the potential to achieve various ...