Security teams should treat networking and governance as separate control planes. Networking decides whether an AI agent can reach a private tool through segmentation, allowlists, private connectivity, and egress controls. Governance decides whether that agent should be allowed to use the tool at all, using identity, policy, approvals, least privilege, and auditability. NHI Mgmt Group recommends binding each agent to a unique NHI and enforcing both checks independently.
Separate transport access from tool authority
Connecting an AI agent to a private tool should start with a blunt distinction: network reachability is not the same as permission to act. Segmentation, private endpoints, allowlists, and egress filtering only answer whether traffic can get to the tool. They do not answer whether that agent should be able to query, read, modify, or trigger side effects once it arrives.
That separation matters because teams often collapse two decisions into one control. If network policy becomes the proxy for authorization, the result is either overexposure or brittle exceptions. A private path can reduce exposure, but it still needs an explicit governance decision about who the agent is, what it may do, and under what approval or policy conditions.
Use identity and policy to decide what the agent may do
Governance should sit above the connection layer and evaluate the agent as a distinct principal. The practical pattern is to bind each agent to its own identity, then assign permissions narrowly to the specific tool, action, and environment it needs. That lets you apply least privilege, approval gates, and revocation without changing the underlying network topology.
For AI agents, the strongest design is usually per-agent, per-action control rather than coarse shared access. A shared credential or a broad service identity makes it difficult to tell which agent invoked the tool, why it did so, or whether one compromised workflow can reuse another workflow’s access. Unique identity also makes audit trails and incident response far more usable.
For a deeper treatment of delegation, task-scoped access, and approval gates, AI Agent Authorisation Guide is the best companion piece.
Design the control stack so networking cannot substitute for governance
The cleanest operating model is two independent checks. First, the network path must be explicitly permitted to the private tool. Second, the agent must be authorised to use that tool for that specific purpose. If either check fails, the request stops. That gives you defence in depth without pretending that network controls can enforce business intent.
This is also where observability matters. Teams should be able to see which agent reached which tool, which policy allowed it, and whether the action was read-only, state-changing, or exceptional. If you cannot answer those questions quickly, the environment is not yet separating connectivity from authority in a meaningful way.
A useful mental model is to treat networking as the boundary of possible access and governance as the boundary of allowed action. When those boundaries drift together, private connectivity can hide excessive privilege, and privilege reviews can miss the real blast radius. The better pattern is to make each layer independently inspectable, revocable, and auditable.
Risk and Threat Considerations
When transport access and governance are blended, the most common failure is silent overreach: an agent can reach a tool because the path exists, then use broader permissions than the business intended. That creates unnecessary exposure if the agent is compromised, misrouted, or simply behaves in an unexpected way.
Failure mechanism: A network rule or private connector is mistaken for an authorisation decision, so the agent inherits more effective power than the intended task scope. In a compromise scenario, that can turn a narrowly connected tool into a high-value pivot point.
Impact: Excess reach can lead to unauthorised reads, writes, destructive actions, or lateral movement through downstream systems. It also weakens attribution, because the organisation may know a connection was allowed but not whether the agent was truly meant to use the tool in that way.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Non-Human Identity Top 10 and OWASP Agentic AI Top 10 address the attack and risk surface, while NIST SP 800-53 Rev 5 sets the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-05 — Overprivileged NHI | Separating reachability from authority prevents agents from getting excessive tool privileges. |
| NHI-04 — Insecure Authentication | Unique agent identity is needed so governance can verify who is using the tool. | |
| Recommendation — Scope each agent's tool permissions to the minimum action set and remove broad shared access. Authenticate each agent with its own identity instead of reusing shared credentials. | ||
| OWASP Agentic AI Top 10 | ASI03 — Identity & Privilege Abuse | The question is about controlling an agent's authority separately from its network path. |
| Recommendation — Enforce per-agent, per-action authorisation before any tool invocation is allowed. | ||
| NIST SP 800-53 Rev 5 | AC-3 — Access Enforcement | Access enforcement is the governance layer that decides whether the agent may use the tool. |
| IA-5 — Authenticator Management | Unique identities and credentials are needed to bind actions to a specific agent. | |
| AU-2 — Audit Events | The answer depends on auditable separation of connection and action decisions. | |
| Recommendation — Enforce authorisation on each tool request, not just at the network boundary. Issue and manage distinct authenticators for each agent so access remains attributable. Log agent identity, tool use, and decision outcome for each authorised action. | ||
Practitioner Guidance
What to prioritise: Model the agent, the tool, and the action separately. A private connection is only the first gate; the second gate is whether the agent has the right to invoke that operation at all.
What to verify: Confirm that each agent has a unique identity, that permissions are scoped to the minimum viable tool actions, and that approval or policy checks happen independently of network allowlisting. If you cannot revoke access without changing routing, the controls are too entangled.
Common mistake: Treating a trusted network path as evidence of trusted behaviour. That shortcut often survives early testing but fails as soon as agents are reused, delegated, or connected to higher-value tools.
Practitioner takeaway: Private connectivity should reduce exposure, not confer authority; the safest pattern is to let networking answer “can it reach?” and governance answer “should it act?”
Related resources from NHI Mgmt Group
- How should security teams reduce data exposure before connecting enterprise data to AI tools and agents?
- How should security teams use MCP safely when connecting AI agents to vulnerability management tools?
- How should security teams protect private LLMs and internal tools from rogue AI agents in CI/CD pipelines?
- How should security teams govern AI portfolios when use cases, models and agents are tracked in separate tools?