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Autonomous agents move beyond chatting by executing code and accessing APIs to complete tasks.

This shift creates a "black box" execution risk where the AI acts without a human seeing the process.

Securing these systems requires a maturity framework to measure how safely an agent acts on a user's behalf.

What it does: It moves security from a single toggle to a set of intersecting technical vectors.

The core dimensions: Authorization (verifying who is allowed to do what) and tool-use constraints (limiting what the agent can actually touch).

The maturity path: Systems evolve from "Initial" basic safeguards to "Optimized" continuous automated monitoring.

The analogy: An immature agent is like an intern with a company credit card and no manager; a mature agent is a vetted employee with strict spending limits.

The shift: Security is moving away from just stopping prompt injection—tricking the AI with clever text—toward governing the entire lifecycle of the entity.

To assess your current posture, start by inventorying every tool the agent can access and mapping the data flow.

You can then apply the OWASP Top 10 for Agentic Applications to grade your maturity level and set a target.

A customer support agent that can issue refunds requires a much higher maturity level than a research agent that only reads public documents.

The Agentic Security Vector Map in the guide helps you visualize this balance across five key dimensions.

Download the full Field Guide PDF to see the complete maturity ascent.

#LLMOps #OWASP #AgenticAI #AppSec #SoftwareGovernance