data-governance
Safeguard articles tagged "data-governance" — guides, analysis, and best practices for software supply chain and application security.
5 articles
AI Information Security: How to Protect Data in AI Systems
AI information security is the practice of protecting the data that flows through AI systems, training sets, prompts, outputs, and the models themselves, from disclosure, poisoning, and misuse. Here is a working model of the risks and controls.
DSPM for AI: navigating data and AI compliance regulations
DSPM for AI closes the gap traditional tools miss: tracking sensitive data through embeddings, fine-tuning, and vector stores to meet EU AI Act and Colorado AI Act requirements.
MCP Server Telemetry Data Governance
MCP server telemetry captures sensitive prompts, arguments, and outputs. A governance framework for retention, redaction, and tenant-scoped access is essential.
AI Data Security Solutions: What Actually Protects Your Data?
AI data security solutions cover the tools and controls that protect the data flowing into, through, and out of AI systems. Here is what the category really includes and how to evaluate it.
Choosing an Agile Data Security Solution That Keeps Up
An agile data security solution protects data at the speed teams actually ship, embedding controls into pipelines and adapting as data moves rather than gating everything through slow manual review.
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