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

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 ...

Malicious web prompts can weaponize AI without your input. Indirect prompt injection is now a top LLM security risk. Don't treat AI chatbots as fully secure or all-knowing. Artificial intelligence (AI ...

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 ...

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.

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.

Prompt injection and supply chain vulnerabilities remain the main LLM vulnerabilities but as the technology evolves new risks come to light including system prompt leakage and misinformation.

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The UK’s National Cyber Security Centre (NCSC) has highlighted a potentially dangerous misunderstanding surrounding emergent prompt injection attacks against generative artificial intelligence (GenAI) ...

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 ...