Securing AI Agents with AppGate ZTNA: Zero Trust for Every Runtime
AI agents are rapidly integrating into daily workflows—automating tasks, assisting in code editors, and even interacting with internal systems. But with that power comes risk. Whether agents run locally, in virtual machines, or inside Kubernetes pods, they introduce new attack surfaces and data exposure pathways.
AppGate ZTNA, built on a best-of-breed Zero Trust Network Access (ZTNA) architecture, delivers a flexible and scalable way to secure AI agents. It mitigates AI-driven risk through dynamic, identity-centric controls that protect agents consistently across endpoints, virtualized workloads, and containerized environments.
The Risks of AI Agents in the Enterprise
AI agents often inherit the same access rights as the user, making them powerful—and potentially dangerous. Significant risks associated with this model include:
- Over-permissioned agents: Agents can access everything the user can, including sensitive systems.
- Shadow AI: Users install their own agents, creating unmanaged and unmonitored access paths.
- Traffic ambiguity: Agent-initiated traffic is hard to distinguish from user activity, especially when embedded in apps like integrated development environments (IDEs).
- Audit gaps: It’s difficult to track what agents did and why.
- Data leakage: Agents may send sensitive data to third-party large language models (LLMs), where it can become part of future training data—or be stored and resold to other parties for marketing or espionage.
- Automated phishing: Agents with access to internal communications can craft convincing attacks.
- Reconnaissance and vulnerability scanning: Agents can be used to map infrastructure and find weaknesses.
While these risks vary across environments, they share one root cause: a lack of fine-grained, identity-based control. Without Zero Trust enforcement, AI agents can move freely, accessing more data than intended and creating invisible exposure points. AppGate ZTNA addresses these risks with identity-centric controls, infrastructure cloaking, and dynamic policy enforcement.
Local Machine Agents: Control the Cloud Connection
Most AI agents are thin clients that connect to cloud-hosted LLMs (like OpenAI). The local agent acts as a bridge between the user’s device and the cloud. This bridge is where visibility often breaks down, making it critical to verify device posture and traffic paths before an agent can connect outward.
AppGate ZTNA can control this bridge by enabling organizations to:
- Enforce proxy usage: Use device posture checks to ensure the machine routes traffic through a corporate proxy.
- Filter AI domains: Block unauthorized LLM endpoints.
- Bypass selectively: Allow approved users or apps to connect directly for sanctioned AI use.
- Dual profiles: Create one profile for “human eyes only” and another for AI-enabled workflows, made possible only when connected via the AppGate Client.
Block third-party cloud services: Prevent agents from reaching unsanctioned destinations.
By controlling how traffic flows between local agents and external models, AppGate ZTNA ensures sanctioned AI use while preventing unauthorized tools from leaking data or connecting to unvetted services. This setup ensures that only approved agents on compliant devices can reach cloud-hosted LLMs—reducing the risk of data exfiltration and unauthorized access.
Virtual Machines: Sandboxed and Segmented
Running agents in VMs—on-prem, cloud, or locally—is a secure way to isolate them. AppGate ZTNA enhances this model:
- Headless Client deployment: Install AppGate’s Linux Headless Client in the VM to enforce identity-based access controls.
- Entitlement-based access: Allow only users with specific entitlements to reach the agent service.
- Web filtering firewall: AppGate ZTNA can integrate with third-party tools to filter VM traffic and ensure agents only reach approved destinations.
This layered approach transforms each virtual machine into its own secure environment. Access is governed by identity and context rather than network placement, establishing a micro-perimeter around the VM that prevents lateral movement and limits agent access to only what it needs.
Kubernetes: Granular Control with Pod-Level Identity
AI agents deployed in Kubernetes can be ephemeral and dynamic. AppGate ZTNA’s Kubernetes Injector makes it possible to secure them with precision, as follows:
- Sidecar injection: Dynamically provision headless AppGate ZTNA clients.
- Per-pod identity: Assign each pod a unique identity.
- Label-based policy: Use Kubernetes labels to assign entitlements and access controls.
- Audit visibility: Track agent activity via centralized logs and session metadata.
With these controls, AppGate ZTNA brings Zero Trust down to the container layer, delivering the same precision and accountability for dynamic AI workloads that it provides for traditional infrastructure. This model supports dynamic, scalable AI workloads while maintaining strict access governance.
Cloud-Hosted Agents and SaaS Integrations
Even with network controls in place, SaaS apps may allow agents to connect via APIs. AppGate ZTNA complements SaaS-level controls by enabling agents to:
- Restrict egress: Prevent agents from reaching SaaS endpoints unless explicitly allowed.
- Use app-native controls: Configure SaaS platforms to block unauthorized agent integrations.
- Combine with AppGate ZTNA: Ensure only approved identities can reach SaaS APIs, and only under compliant conditions.
Together, these measures extend Zero Trust protection into SaaS ecosystems where most organizations face blind spots from API-driven AI integrations. This layered approach protects sensitive data from being accessed or exfiltrated by cloud-hosted agents.
Auditability and Compliance: Built-In
AppGate ZTNA simplifies audit and compliance by making all activity visible and controllable:
- Single Packet Authorization (SPA): Makes resources invisible until trust is verified1.
- Segment-of-one access: Ensures each session is isolated and encrypted.
- Centralized logging: Captures all access events, ensuring they are exportable to SIEMs.
- Policy-as-code: Automates provisioning and revocation based on identity, device posture and context.
This unified view makes every AI interaction fully traceable and compliant, ensuring that agent activity remains observable, explainable, and provable, which is critical for regulated environments.
Why AppGate ZTNA Is Future-Proof
AppGate ZTNA’s flexible architecture supports modern and emerging workloads through:
- Direct-routed connectivity: No vendor cloud brokers—traffic goes straight to the resource.
- Distributed enforcement: Policies are enforced locally at each gateway, improving performance and resilience.
- Programmable APIs: Integrate with DevOps, IAM, and SIEM tools for dynamic access control.
- Scalable design: Supports millions of sessions across hybrid and multi-cloud environments.
These architectural advantages make AppGate ZTNA inherently adaptable. Whether securing legacy systems or next-generation AI workloads, it provides a consistent, high-performance foundation for enforcing Zero Trust anywhere. Whether you’re securing legacy systems, modern AI agents, or future workloads, AppGate ZTNA adapts to your environment and scales with your needs.
Zero Trust for the AI-Driven Enterprise
AI agents are powerful, but without proper controls, they’re risky. AppGate ZTNA provides the visibility, segmentation, and adaptive enforcement needed to secure agents across all environments. From local machines to Kubernetes clusters, it delivers Zero Trust access that’s fast, flexible and future-ready.
Ready to secure your AI agents? Learn more about AppGate ZTNA or schedule a demo to see it in action.