Inter-agent trust is the missing control in multi-agent AI systems

At a glance

What this is: This is an analysis of why multi-agent AI systems create a trust boundary problem, with the key finding that downstream agents often cannot verify the legitimacy of instructions passed from orchestrators.

Why it matters: It matters because IAM, NHI, and emerging agent governance programmes must control delegation, scope, and accountability at handoff points, not just at the initial login or token issuance step.

👉 Read Noma Security's analysis of inter-agent trust in multi-agent AI systems

Context

In multi-agent AI systems, the core governance problem is not only what an agent is allowed to do, but whether another agent can prove the instruction it received is legitimate. That matters because the trust decision now moves from the human boundary into the agent-to-agent boundary, where traditional identity assumptions are much weaker.

The article is really about delegation, not just automation. Once an orchestrator hands work to sub-agents, the system needs to preserve identity, scope, and accountability across the chain. Without that, security teams are left with a workflow that looks authorised at each hop but is not verifiable end to end.

Key questions

Q: How should security teams govern AI agents that move across multiple trust boundaries?

A: They need runtime controls that follow the agent rather than staying attached to one platform. The practical test is whether enforcement, telemetry, and inventory remain consistent as the agent moves from IDEs to MCP servers to downstream SaaS actions. If the control breaks at the boundary, governance is incomplete.

Q: Why do multi agent systems create more identity risk than single AI assistants?

A: Multi agent systems create more identity risk because they combine delegation, shared context, and external communication across multiple execution steps. A compromise or injection in one step can propagate through downstream agents that treat prior outputs as trusted input. That turns identity trust into a chain problem rather than a single access decision.

Q: What do teams get wrong about least privilege for AI agents?

A: They often stop at permission scope and ignore behavioural scope. An agent can have narrow access and still be risky if it can independently select targets, chain tool calls, and trigger irreversible actions. Least privilege is necessary, but it does not describe the agent's freedom to act.

Q: Who is accountable when a compromised AI agent misuses delegated access?

A: Accountability usually spans the business owner of the workflow, the team that issued or approved the credential, and the vendor if a third-party integration was involved. The critical governance question is not who logged in, but who allowed the delegation chain to exist and remain valid. That chain must be documented before incidents occur.

Technical breakdown

Why inter-agent trust breaks in delegated workflows

In a multi-agent workflow, one agent delegates work to another through messages, not through a direct human approval step. That creates a weak trust model because the receiving agent may not be able to verify whether the sender was legitimate, compromised, or simply operating outside the human's intent. The problem is structural: the instruction can look valid even when the chain that produced it is not. In identity terms, the system has a task, but not a verifiable delegation lineage. Practical implication: treat every agent handoff as a trust boundary that needs explicit verification, not as an internal implementation detail.

Practical implication: design agent handoffs as enforceable trust boundaries, not implicit internal messages.

How delegated credentials expand blast radius in agent chains

The article highlights a common design choice: sub-agents may inherit the orchestrator's permissions, receive scoped permissions, or operate under their own service identity. If that choice is not deliberate, the result is standing privilege applied transitively across the chain. That means a compromise at one point can spread through downstream agents that are simply executing what appears to be a legitimate task. This is not the same as ordinary automation risk because each step can be locally valid while the full chain is unsafe. Practical implication: issue task-bound credentials that expire with the task, not transitive access copied from the orchestrator.

Practical implication: scope delegation separately from the orchestrator's own authority and make credentials task-bound.

Why audit trails must record the full delegation chain

If logs only show the final action, they miss the governance context that explains why the action happened. In agentic systems, that context includes the sending agent, receiving agent, scoped credential, task correlation ID, and whether the instruction was verified or merely trusted. Without that chain, forensic teams can see impact but not accountability. This is where agent governance becomes closer to privilege governance than to model monitoring. Practical implication: require audit records that capture delegation lineage, not just leaf-node activity.

Practical implication: log sender, receiver, scope, and verification state for every agent-to-agent action.

NHI Mgmt Group analysis

Inter-agent trust is the new identity control plane: Multi-agent systems do not fail only because an agent is over-permissioned. They fail when downstream agents accept upstream instructions without being able to validate their legitimacy, which turns delegation into an unverified trust channel. That is a governance problem, not just a prompt-security problem. The implication is that agent identity must be enforced at the handoff, not only at the session boundary.

Least privilege at the task level is necessary but incomplete: The article correctly separates action scope from delegation scope. A sub-agent can be narrow in function and still be overexposed if it inherits the orchestrator's broader authority. That creates transitive standing privilege, which is the wrong default for any environment that treats identity as an access control primitive. Practitioners should read this as a warning that orchestration design can silently widen privilege even when the individual agents appear constrained.

Trust by proximity is the current failure mode: Most multi-agent deployments still rely on the assumption that a message arriving from the right channel is safe to execute. That assumption was designed for simpler automation and trusted service boundaries, not for recursive agent delegation. It fails when an upstream agent can be poisoned, misled, or compromised before it generates the downstream task. The implication is a need to rethink how trust is assigned across agent chains, not simply add another approval step.

Inter-agent authentication will become a governance baseline, not a niche control: The article points to a future where cryptographic identity, dynamic trust scoring, and scoped delegation are expected parts of agent security. That direction is consistent with how IAM has always evolved when new classes of non-human actors become operationally important. The practical conclusion is that teams should evaluate agent platforms on whether they can prove who instructed whom, under what scope, and with what verifiable lineage.

From our research:

• 70% of organisations grant AI systems more access than they would give a human employee performing the exact same job, according to the 2026 Infrastructure Identity Survey.
• Only 44% of organisations have implemented any policies to manage their AI agents, even though 92% agree that governing AI agents is critical to enterprise security.
• That gap makes OWASP NHI Top 10 a useful next reference for teams formalising agent handoff controls.

What this signals

Multi-agent governance will increasingly resemble privilege governance plus identity verification at runtime. Teams that already map delegation chains, down-scope task access, and capture lineage in logs will be better prepared when agent frameworks start enforcing stronger inter-agent trust controls.

Delegation lineage debt: this is the gap that appears when organisations can describe what an agent did but cannot prove who authorised the action path. That debt will surface first in incident reviews and later in access governance, especially where sub-agents inherit authority implicitly.

For practitioners, the practical signal is that agent security is moving from model monitoring into identity design. The organisations that align with OWASP Agentic AI Top 10 and NIST AI Risk Management Framework will be better positioned to evaluate trust scoring, scoped delegation, and future inter-agent authentication.

For practitioners

• Map every agent delegation chain Document which orchestrators can task which sub-agents, under what identity, and with what inherited scope. You need a live inventory of handoffs before you can define trust boundaries or detect where a compromised upstream agent could influence downstream execution.
• Issue task-bound credentials for sub-agents Do not copy orchestrator permissions into downstream agents. Use just-in-time, expiring credentials that are scoped to the specific task and automatically revoked at completion, so one compromised step cannot silently inherit the full session.
• Require delegation-aware audit logging Make sure logs show the sender, receiver, scoped credential, task ID, and whether the instruction was verified or trusted. A leaf-node action without delegation context is not enough for governance, incident response, or review.
• Test for poisoned upstream instructions Simulate a compromised orchestrator or malformed peer instruction and verify whether the receiving agent can reject it. If the downstream agent executes anyway, your trust model depends on message proximity rather than authenticated delegation.

Key takeaways

• Multi-agent AI creates a governance gap at the handoff boundary, where downstream agents may not be able to verify the legitimacy of instructions they receive.
• The article's core risk is transitive privilege, because inherited authority can let a compromise in one agent cascade through the entire delegation chain.
• Practitioners should respond by mapping agent relationships, down-scoping delegated access, and logging the full identity chain for every handoff.

Key terms

• Inter-Agent Trust: Inter-agent trust is the set of assumptions one agent makes about another agent’s identity, input, and authority. If that trust is implicit or unauthenticated, attackers can exploit spoofing, replay, or poisoned messages to steer workflows and trigger broader failures across systems.
• Delegation Chain: A delegation chain is the sequence of identities, credentials, and tool calls an agent uses to complete a task across systems. It matters because each step may appear acceptable on its own while the combined path produces an outcome no reviewer would have approved directly.
• Transitive privilege: Privilege that is inherited by a downstream actor through an upstream delegating identity. In agentic environments, it becomes a governance problem when a sub-agent receives more authority than its task requires simply because the orchestrator already had it.

What's in the full article

Noma Security's full post covers the operational detail this analysis intentionally leaves for the source:

• A deeper walkthrough of multi-agent delegation patterns, including orchestrator and sub-agent roles in practice.
• The specific inter-agent trust protocol concepts and implementation examples discussed by the vendor.
• More detail on how current frameworks such as LangGraph, CrewAI, Copilot Studio, and AgentForce differ in default trust handling.
• A fuller discussion of runtime guardrails, including scoped delegation and audit trail design for agent chains.

👉 The full Noma Security post expands on delegation chains, trust assumptions, and runtime guardrails for agent handoffs.

Deepen your knowledge

NHI governance, agentic AI identity, and machine identity security are core topics in our NHI Foundation Level course, the industry's only accredited NHI security programme. If you are building or maturing an IAM or identity security programme, it is worth exploring.