New! A10 Networks Acquires TrojAI

Secure the AI Agents Your Teams Build

Build AI agents with confidence

Secure Custom Agentic Workflows

Custom AI agents are built to automate an organization's unique workflows, connect to internal systems, and take action using enterprise data. These agents can accelerate productivity and enable powerful automation across a wide range of development approaches. Agents built on platforms such as Vertex AI, Azure AI Foundry, and Amazon Bedrock, developed using LangGraph or LangChain with python and other proprietary architectures introduce security challenges.

Custom agent workflow dashboard with activity rows and a request progressing through a policy check

Because custom agents combine model reasoning, enterprise data access, and autonomous action, they create a rapidly expanding attack surface that traditional application security tools were never designed to protect.

Custom Agent Workflow

  1. 01

    Employee/Customer

    A user initiates a financial analysis or question

  2. 02

    Custom UI or Internal App

    User interacts through a custom interface or internal application

  3. 03

    Custom Agent Logic

    Handles context, session management, input validation, and business rules

  4. 04

    LLM (GPT, Gemini, Claude, Llama)

    Generates insights, answers, and analysis based on user intent and data

  5. 05

    Planner/Orchestrator

    Breaks down the task, plans steps, selects tools, and orchestrates execution

Enterprise Access. Enterprise Risk

Custom agents are AI systems built by internal teams or trusted partners, whether self-managed orchestration frameworks or managed agent platforms. To complete AI-driven enterprise workflows, custom agents often integrate with:

  • Orchestration Frameworks
  • LLM APIs
  • MCP Servers
  • RAG Pipelines
  • Internal Tools and Applications
  • Business Logic

These agents frequently operate with privileged access, making visibility, governance, and runtime protection across the AI lifecycle essential.

Custom agent integration hub connecting LLM APIs, orchestration, MCP servers, and RAG pipelines around a central node

The Security Risks of Custom Agents

Custom agents can connect directly to internal APIs, databases, and workflows, turning a single prompt into a potential business problem. Custom agents introduce the following risks:

Prompt injection and tool misuse that manipulate the agent into taking unintended action

Over-permissioned access to internal systems, APIs, files, and workflows

Data leakage through model outputs, tool calls, logs, or connected services

Unsafe autonomous behavior when agents make decisions without enough policy control

Shadow AI development where agents are built and deployed without security visibility

How TrojAI Secures Custom Agents

TrojAI helps enterprises secure custom agents across the full AI lifecycle. From design and configuration to runtime monitoring, policy enforcement, and continuous protection, TrojAI helps secure custom agents across the full AI lifecycle. Security and AI teams get the control layer they need to safely build and scale custom agents.

Discover and Assess Agent Risk

Identify where custom agents exist, what systems they connect to, and which tools they can access.

Test Before Deployment

Evaluate agents before and during deployment for susceptibility to prompt injection, jailbreaks, unsafe tool use, data exposure, and policy violations before they reach production.

Enforce Policy at Runtime

Apply consistent security policies that govern agent inputs, outputs, tool calls, and sensitive data handling.

Monitor Behavior Continuously

Detect abnormal action, risky interactions, and emerging threats in real time.

Secure the Full Lifecycle

From configuration to runtime, ensure custom agents operate safely, reliably, and as intended.

Secure Your AI Agents Today.