Securing Generative AI: Understanding Prompt Attacks and How to Stop Them

Generative AI promises productivity and innovation—but it also introduces unfamiliar security challenges. As models ingest sensitive data and agents act autonomously, organizations risk exposure through hallucinations, insecure outputs, and misuse of trusted systems.

This report explores how AI-specific threats differ from traditional cyber risks and why visibility into models, agents, and runtime behavior is now essential. It highlights where security gaps commonly emerge and what organizations must do to prevent AI systems from becoming attack vectors.

Key topics include:

AI-specific threats security teams can’t ignore
Why visibility across inputs, outputs, and behavior matters
How continuous monitoring strengthens trust in AI systems

Download the report to better understand where AI security breaks down—and how to close the gap before threats escalate.

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