Inter-Agent Context

Expanded Definition

Inter-agent context is the information one AI agent passes to another so work can continue without restarting from zero. That context can include prompts, summaries, retrieved facts, memory snippets, task instructions, tool output, or intermediate decisions. In practice, the value is continuity, but the security boundary is the transfer itself: once context crosses from one agent to another, it may also cross a different application, cloud, permission set, or trust domain.

The main boundary issue is that useful context is not always safe context. A handoff that is perfect for task continuity can still expose secrets, private data, or sensitive reasoning that the next agent does not need. Guidance across the agentic AI community increasingly treats context minimisation as a control goal, not just a performance choice. For a current industry view, see OWASP Top 10 for Agentic Applications 2026.

Inter-agent context is narrower than general prompt engineering and broader than a single message payload. It also differs from model memory because the core issue is transfer between autonomous actors, not storage alone. When organisations blur that distinction, they tend to over-share state in the name of delegation and under-estimate how quickly context can replicate sensitive material across a multi-agent workflow.

Examples and Use Cases

• A support triage agent forwards a shortened case summary to a resolution agent so the second agent can continue the workflow without re-reading the full conversation.
• A coding agent passes a task plan and repository findings to a review agent, but excludes secrets, tokens, and environment-specific credentials from the handoff.
• A research agent transfers retrieved evidence and citations to a drafting agent so the output can be written from the same source set.
• An orchestration layer sends tool results from one agent to another, but the intermediate context is filtered so only task-relevant fields survive the transfer.
• A finance workflow moves approval state between agents, where the tradeoff is speed versus the risk of propagating unnecessary customer or transaction detail.

These examples show why inter-agent context is often designed as a selective summary rather than a full transcript. That design choice can reduce leakage, but it can also remove nuance if the receiving agent needs more than a coarse state snapshot to act safely.

Security Implications

Mismanaged inter-agent context can create silent data spread. If an upstream agent forwards more than the next agent needs, sensitive information may be replicated into logs, queues, caches, memory stores, or downstream tools that were never intended to hold it. In a multi-agent system, that can multiply exposure across separate permissions and trust boundaries instead of containing it in one place.

The practical failure mode is over-sharing, not just interception. Agents often inherit context automatically, so a weak boundary can look like normal workflow continuity while actually bypassing least-privilege assumptions. That becomes especially important when context includes API keys, customer identifiers, internal instructions, or data pulled from privileged tools. The observable symptom is usually not a single dramatic breach signal but growing inconsistency in what different agents can see and reuse.

For NHIMG, the key practitioner observation is that context size is not the same as context quality. A smaller handoff can be safer and more governable, but only if it preserves the decision-critical facts needed by the next agent.

Domain and Governance Relevance

Inter-agent context sits at the intersection of agentic AI governance and identity-adjacent security because it determines what one autonomous actor is allowed to know about another actor’s work. When agents operate with different scopes, the handoff becomes an authorization question as much as a data-handling question. That makes context design relevant to ownership, retention, and boundary setting, especially where one agent works across systems with different confidentiality levels.

In NHI-heavy environments, the same issue affects workload identities, service tokens, and delegated tool access. If an agent receives context that embeds credentials or privileged operational detail, the transfer can outlive the original task and expand the blast radius of a compromise. Good governance therefore treats context forwarding as part of access design, not as a harmless implementation detail.

Where agent-to-agent delegation is used, the organisation should be able to explain why each field is present, who can inspect it, and what should never move between agents at all.

Risk and Threat Considerations

Inter-agent context creates a material confidentiality and trust-boundary risk because the same state that improves delegation can also propagate secrets, sensitive instructions, or private data into places that were not meant to receive them. In agentic workflows, the risk is often cumulative: each handoff can widen exposure even when no single transfer looks obviously dangerous.

Failure mechanism: An upstream agent includes more context than the downstream agent needs, and that data is then reused, logged, cached, or forwarded again through another tool or agent. Attackers can also exploit poisoned or misleading context if they can influence what one agent passes to another.

Impact: Sensitive data can spread across multiple permissions and systems, privileged actions may be taken on the basis of untrusted context, and containment becomes harder because the same material exists in several agent memories or execution paths.

Practitioner Guidance

Why practitioners should care: Treat inter-agent context as a security boundary, not just a convenience layer. The main design question is not whether agents can share state, but which parts of that state are genuinely needed for the next agent to do its job.

Common misunderstanding: Teams often assume a summarized handoff is automatically safe because it is shorter than the original prompt. In practice, a compact summary can still carry secrets, privileged instructions, or misleading state if it is not filtered against the receiving agent’s role and scope.

Practitioner takeaway: Keep the handoff minimal, role-specific, and reviewable so delegation works without turning every agent exchange into a data propagation event.

Related resources from NHI Mgmt Group

• How can SOC teams use identity context to improve response to agent activity?
• What breaks when audit logs do not capture agent delegation and decision context?
• What breaks when inter-agent responses are not validated?
• How should security teams govern AI agent context windows?