Data Security Guide to Securing AI Models

Securing the AI Core: A Guide to Protecting Models and Data
From fine-tuning risks to RAG-backed pipeline vulnerabilities, enterprise AI requires specialised protection. This technical guide explores the security framework needed to responsibly scale AI models while hardening your infrastructure against modern attack paths.

Key Takeaways: 

Comprehensive Model Discovery: Build a complete inventory of every AI model and service running in your environment.
Hardening AI Pipelines: Secure the training data and Retrieval-Augmented Generation (RAG) processes that power your AI.
Risk-Based Assessment: Use AI-SPM to identify misconfigurations and hidden attack paths before they are exploited.
Optimised Access Governance: Enforce strict permissions to ensure internal AI deployments don’t overshare sensitive data.

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