Organizations are adopting generative AI to boost productivity and innovation but face rising security risks like prompt injections, data leaks, and agent hijacking that traditional tools can't address. AI-specific threats demand AI-native protection for models, data, applications, and agents. Explore security strategies in this e-book.
Organizations are adopting generative AI to boost productivity and innovation, with nearly half already building GenAI applications. However, this rapid growth introduces security challenges traditional tools can't address, such as prompt injections, model tampering, data leaks, and agent hijacking, exploiting vulnerabilities in model inputs and outputs.
This e-book explores how AI security platforms mitigate these risks across the GenAI lifecycle, including:
· AI-specific threats like prompt injection and agent hijacking
· Security for models, data, and agents
· Strategies for deployment, runtime, and monitoring
Read the e-book to secure your AI investments.
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