Control means setting clear rules for AI usage and enforcing them in a way that does not break the business. This is the point where many companies get stuck. Some teams over-block and kill adoption. Other teams do nothing and accept silent risk. The goal is neither. The goal is safe adoption by default.
AI is showing up everywhere in the enterprise sometimes through approved tools and sometimes through “shadow AI.” The first step to securing it is simple: if you cannot see AI usage, you cannot secure it. This post explains what to discover, why it is hard, and what to do in the first 30 days.
Introduction Prompt injection is increasingly recognized as a rising class of risk in AI systems. This is a critical threat vector in which attackers craft natural language inputs to subvert model instructions, bypass guardrails, or leak sensitive data. But before focusing on prompt injection threats let’s quickly review how AI tools present risks for a company’s unstructured data. In our blog discussing how Versa secures unstructured data against AI driven risk, we explain how unstructured data—spanning emails, documents, collaboration tools, and code repositories—creates surface area of risk with generative AI platforms and solutions. We also examine how Versa’s Unified SASE…
The proliferation of AI and machine learning workloads has accelerated the generation and utilization of unstructured data—including emails, source code, collaboration files, logs, recordings, and internal documentation. Unlike structured data, which resides in databases, unstructured data spreads across cloud drives, SaaS applications, endpoints, and unmanaged collaboration tools.
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