Internet of Agents

Expanded Definition

The Internet of Agents describes an environment where autonomous software entities coordinate work across multiple systems, exchange context, and hand off tasks through chains of delegation. In NHI security, the concern is not only whether one agent is authenticated, but whether every downstream action remains constrained, attributable, and revocable. This makes the term broader than a single assistant or chatbot deployment, because it includes orchestration logic, tool access, shared memory, and cross-agent trust relationships.

Definitions vary across vendors, but the security baseline is converging around identity, authorization, and control-plane governance for agents. That aligns with the framing in the OWASP Agentic AI Top 10 and the risk lens in the NIST AI Risk Management Framework, both of which treat agent behavior as a governed system rather than a single prompt-response loop. The most common misapplication is assuming one service account or API token can safely cover an entire agent mesh, which occurs when teams ignore delegation boundaries and shared-state propagation.

Examples and Use Cases

Implementing the Internet of Agents rigorously often introduces coordination overhead, requiring organisations to weigh automation gains against tighter policy enforcement, logging, and credential control.

• A support agent routes a ticket to a billing agent that verifies entitlements, then calls a payment service and updates the CRM. Each hop needs scoped authorization and traceable ownership, not inherited trust.
• A software engineering agent reads issues, opens pull requests, invokes CI/CD, and requests a code review agent to summarise findings. This is useful, but it expands the blast radius if tool permissions are overbroad. The OWASP NHI Top 10 highlights how agentic workflows can amplify secret exposure and privilege misuse.
• A procurement agent consults a policy agent, then a vendor-risk agent, before writing data into a shared repository. The chain is only trustworthy if provenance, policy versioning, and approval boundaries are enforced.
• A fraud-detection agent shares signals with a case-management agent and an investigation agent. Cross-agent messaging is efficient, but it demands strict context filtering to avoid leaking sensitive attributes into unrelated workflows.
• Research teams are already documenting real-world abuse patterns in agent ecosystems, including the AI LLM hijack breach and related agent-key exposure cases.

Why It Matters in NHI Security

The Internet of Agents matters because every additional delegation hop becomes another place where secrets, permissions, and context can be intercepted, expanded, or misused. In practice, a compromised agent can trigger downstream actions far beyond its intended scope if its identity is not tightly bound to purpose, session, and policy. NHIMG reporting shows that 80% of identity breaches involved compromised non-human identities such as service accounts and API keys, and 97% of NHIs carry excessive privileges, which makes agent-to-agent trust especially dangerous when the system is designed for speed rather than containment. That risk is reinforced by the Ultimate Guide to NHIs, which documents how common excessive privilege and weak rotation remain across enterprises.

Good governance therefore treats agents as NHI participants with lifecycle obligations: provisioning, scoped access, rotation, monitoring, and offboarding. Frameworks such as the MITRE ATLAS adversarial AI threat matrix and the CSA MAESTRO agentic AI threat modeling framework help security teams reason about attack paths across autonomous workflows, not just at the model boundary. Organisations typically encounter the operational reality of the Internet of Agents only after an agent has overstepped its scope, at which point containment across the delegation chain becomes operationally unavoidable to address.

Related resources from NHI Mgmt Group

• What governance controls should every enterprise put in place before deploying AI agents?
• What is MCP Step-Up Authorisation and how does it implement least privilege for agents?
• When is it crucial to implement least-privilege access for AI agents?
• What is the difference between managed identities and hardcoded secrets for AI agents?