Attackers inject malicious code into AI models hosted on the public repositories. These models allow attackers to manipulate ...

The research underscores that as data becomes increasingly integrated into all aspects of life, from industry to governance, ...

The new guidance actually focuses on three main areas of AI data security: data drift and potentially poisoned data, and also ...

How I wrapped large-language-model power in a safety blanket of secrets-detection, chunking, and serverless scale.

AI security is one of the most pressing challenges facing the world today. Artificial intelligence is extraordinarily powerful, and, especially considering the advent of Agentic AI, growing more so by ...

A recent Varonis data security report notes that excessive permissions and AI-driven risks are leaving cloud environments ...

Google DeepMind has developed an ongoing process to counter the continuously evolving threat from Agentic AI’s bete noir: ...

Data security and protection teams can use this knowledge to tailor defenses to each dataset’s sensitivity and use case. For example ... is not exposed to an AI model. This provides a critical ...

Keeping hardware onsite, meanwhile, gives teams complete control of data storage and usage practices. But cost is an issue.