Why agent-to-agent delegation changes the threat model
When one agent invokes another, identity and authorization can drift. A workflow that began under a narrowly scoped user session may, after several handoffs, execute tools with broader ambient privilege, opaque service identities, or credentials that outlive the original task. Attackers and accidental misconfigurations exploit the same gaps: over-broad delegation, missing channel authentication, weak isolation between agent runtimes, and audit trails that cannot reconstruct who authorized what.
Security engineering for multi-agent systems therefore centers on continuity of principal, least-privilege authority at every hop, mutual authentication between agents, and forensic reconstructability. The controls below are evaluation and implementation criteria, not product claims.
Treat each agent handoff as a policy boundary. Prefer short-lived, purpose-bound delegation over forwarding standing high-privilege credentials.
Operational practices that preserve accountability
- Define chain-of-action ownership: Assign clear accountability for outcomes produced through multi-agent chains, including who may authorize standing delegation versus single-task handoffs.
- Require reconstructable audit evidence: Retain records that link the initiating principal, each intermediate agent, tools invoked, authorization decisions, and final results under shared correlation IDs.
- Align with existing IAM and data standards: Map agent delegation policies to enterprise identity, access-management, retention, and data-handling standards rather than inventing parallel exception paths.
- Treat cross-org agents as vendor risk: When agents span teams, tenants, or third parties, apply vendor risk and data-sharing review before enabling privileged tools or durable delegation.
- Re-check protocol security features: Emerging agent interoperability protocols differ in native authn, authz, and audit support. Validate capabilities per implementation before production trust.
- Plan for non-deterministic control messages: Where model outputs influence control-plane decisions, require deterministic policy evaluation on structured claims, not free-form text alone.