The Agentic Security Graph: Get Visibility into your AI Security Risks
As enterprises shift from conversational to agentic AI, the real risk moves from model outputs to the action layer; the MCP servers and APIs through which agents execute real-world tasks.
The Agentic Security Graph frames this risk across three interconnected layers (LLM, MCP servers, APIs), showing how compromises at any layer can propagate and why existing LLM-focused controls leave the most consequential surface unmonitored.
To secure agentic AI you must discover every agent and MCP server, govern posture across all three layers, and detect & respond to cross-layer attacks in real time.
Salt Security’s operational approach combines continuous discovery (AG‑SPM) with AI-driven detection and response (AG‑DR), enabling inventory, policy-based governance, behavioral analytics, and fast containment.
The result is a full-stack defense that turns invisible action-layer risk into manageable, auditable posture.
This webinar covers how to:
- Understand the Agentic Security Graph: LLM (brain), MCP servers (hands), APIs (action layer).
- Recognize why MCP servers and API activity are the highest-risk, least-monitored surfaces.
- Learn a three-step operational approach: Discover, Govern (AG-SPM), Detect & Respond (AG-DR).
- Identify practical controls, telemetry sources, and workflows to reduce agentic risk and meet compliance.
Secure the AI action layer before it becomes the breach your organization is reacting to.