Securing Your AI Agents: Native AI Detection and Response Across the Full Agentic Path

Enterprises are deploying AI agents at scale, and those agents are taking real business actions. Through LLMs, MCP servers, and APIs, they move money, access patient records, modify code, and send emails. The attack surface has fundamentally shifted, but most security programs are still focused on what an AI says rather than what it does.

The blind spot is dangerous. Existing LLM security tools address prompt injection and model-level threats, but leave the full agentic path unprotected. A compromised or manipulated agent can cause irreversible damage at machine speed, and no single-layer solution can stop it.

In this on-demand webinar, speakers Nick Rago and Michael Callahan talk about the following:
· Why LLM security alone leaves critical gaps across the full agentic attack surface
· How AI agents use MCP servers and APIs to take real business actions, and what that means for your risk posture
· What the Agentic Security Graph is and why protecting LLMs, MCP servers, tools, and downstream APIs together is the only complete approach
· How Salt's native AI Detection and Response connects prompt injection attacks, the top-ranked risk in the OWASP Top 10 for LLM Applications 2025, to downstream MCP and API attacks, giving teams unified visibility across existing guardrails and native protection where gaps exist