PRISM AI Discovery: Complete Guide to AI Attack Surface Visibility
PRISM AI Discovery Introduction Artificial intelligence is rapidly becoming part of everyday business operations. Organizations are deploying large language models (LLMs), AI agents, machine learning systems, APIs, model endpoints, and connected tools across cloud, on-premises, and hybrid environments. But as AI adoption grows, a new cybersecurity problem is emerging: organizations often do not know exactly how many AI systems are operating inside their environment. An approved AI application may be documented by the security team, while an employee uses an external AI service, a development team deploys a model, or an autonomous agent connects to an MCP server without appearing in traditional IT asset inventories. This creates AI attack surface visibility gaps . SISA PRISM addresses this challenge through its PRISM AI Attack Surface Visibility , also referred to as PrismDiscover . The solution is designed to discover and catalogue AI models, autonomous agents, MCP servers, API e...