AI Security Posture Management for Your Entire AI Stack

AI security posture management, or AI-SPM, is the discipline of discovering, securing, and governing the components of an AI application. It provides one inventory and policy layer across models, prompts, plugins, datasets, and vector databases, so security teams can see and control AI risk the way they manage the rest of their stack.

AI-SPM covers the full AI application stack: foundation and fine-tuned models, prompts and prompt templates, plugins and tools, code assistants, training data, and vector databases. It tracks where each artifact came from, how it is used, and whether it meets your security and licensing policies.

Traditional AppSec inspects source code and dependencies. AI-SPM adds the artifacts unique to AI systems, such as model weights, prompts, and embeddings, and the new attack surface they create. It pairs that inventory with runtime validation, because much of an AI system's risk only appears once the model is responding to live input.

Runtime validation watches how models, agents, and plugins behave when they execute, not just how they are configured. It can flag unexpected tool calls, data access, or outputs in production, which is essential for AI systems whose behavior depends on prompts and context rather than fixed code paths.

AI applications add non-deterministic models, external plugins, and large training datasets that classic scanners cannot reason about. Risks like prompt injection, unsafe tool use, model provenance gaps, and license violations live outside source code, so they require an AI-SPM approach built specifically for the AI stack.