Securing Generative AI Applications Built on Amazon Bedrock with Cyera
Generative AI is transforming how organizations build, scale, and automate applications, but it also introduces new risks. As teams adopt Amazon Bedrock to power RAG workflows, customize models, and deploy autonomous agents, they face a critical challenge: how to ensure sensitive data stays protected while AI accelerates innovation.This whitepaper breaks down how Cyera’s data-first approach delivers the security foundation modern AI initiatives require. Cyera unifies Data Security Posture Management (DSPM), AI Security Posture Management (AI-SPM), and real-time AI runtime protection to give enterprises complete visibility, governance, and control over how Bedrock models, knowledge bases, and agents interact with sensitive data.Readers will learn how Cyera:
- Discovers and inventories all AI assets: including models, knowledge bases, and agents, while surfacing Shadow AI and mapping each resource to the data it touches.
- Classifies and analyzes sensitive data: feeding models, RAG pipelines, and training sets to prevent leakage, overexposure, or unauthorized use.
- Protects AI in real time: with AI Protect guardrails that classify and filter prompts, completions, knowledge-base retrievals, tool calls, and agent actions to stop sensitive information from escaping or being misused.
- Mitigates OWASP Top 10 for LLM risks: such as prompt injection, training data poisoning, and sensitive data disclosure without slowing innovation.
Through real architectural examples, screenshots, and best-practice guidance, the whitepaper shows how organizations can safely deploy high-value Bedrock use cases, including RAG, model fine-tuning, and agentic automation, while maintaining security, compliance, and least-privilege access.If your organization is adopting Amazon Bedrock, this guide explains exactly how to secure AI workloads end-to-end and eliminate Shadow AI so your teams can innovate faster, with confidence.
