They should govern the workflow as a delegation chain, not as two separate technical choices. MCP controls what tools an agent can reach, while A2A controls which peers it can delegate to. Security teams need identity registration, explicit scope, consent boundaries, and revocation for both layers so that collaboration cannot outrun access control.
Why This Matters for Security Teams
When AI systems combine MCP and A2A, the risk is not just tool use or peer messaging. The real issue is delegated authority moving across boundaries faster than human review can keep up. MCP can expose powerful tools, while A2A can let one agent enlist another to continue the same workflow. That makes the system behave less like a single application and more like a delegation chain with compounding trust.
Security teams often miss the difference between “connected” and “controlled.” If MCP is governed only as tool access and A2A only as inter-service communication, the system can still amplify privilege through chained actions, shared context, and overbroad consent. Current guidance from the OWASP Agentic AI Top 10 and NIST’s broader AI governance approach points toward runtime controls, explicit scopes, and revocation-aware authorization rather than static trust assumptions.
NHIMG’s OWASP Agentic Applications Top 10 and Top 10 NHI Issues both reinforce that identity, scope, and lifecycle control matter more when non-human actors can delegate. In practice, many security teams encounter runaway access only after an agent has already chained a benign request into a sensitive action path.
How It Works in Practice
The practical control model should treat MCP and A2A as two linked authorization layers inside one workflow. MCP governs what the agent can directly touch: files, APIs, databases, admin endpoints, and other tools. A2A governs which peer agents it may invoke, what it may ask them to do, and whether the peer is allowed to accept that delegation. Both layers need identity registration, bounded scope, and revocation so that consent is not implied by proximity.
For implementation, teams should register each agent as a workload identity, then bind that identity to a narrow policy set at runtime. That usually means short-lived credentials, per-task authorization, and policy evaluation at request time rather than pre-approved standing access. This aligns with the direction of the NIST Cybersecurity Framework 2.0, which emphasizes governance, access control, and continuous risk management, even though it is not agent-specific.
- Give each agent a unique workload identity, not a shared service account.
- Set separate scopes for tool execution, peer delegation, and data access.
- Require explicit consent boundaries before one agent can hand work to another.
- Issue short-lived tokens or other ephemeral credentials per task, then revoke on completion.
- Log the full delegation chain so audit teams can reconstruct who acted, through which agent, and under what scope.
Where possible, use policy-as-code so runtime decisions can reflect context such as task type, data sensitivity, environment, and recent behavior. NHIMG’s Ultimate Guide to NHIs — Lifecycle Processes for Managing NHIs is especially relevant here because delegation only stays safe when onboarding, rotation, and decommissioning are enforced as a lifecycle, not as one-time configuration.
These controls tend to break down when A2A is used across loosely governed teams with incompatible identity standards, because delegation becomes harder to trace and revoke consistently.
Common Variations and Edge Cases
Tighter delegation control often increases operational overhead, so organisations have to balance agent autonomy against the cost of policy maintenance and review. That tradeoff becomes sharper in environments where agents collaborate across domains, such as support triage, code generation, or incident response.
There is no universal standard for this yet. Best practice is evolving, but the direction is clear: keep MCP scopes narrow, keep A2A consent explicit, and avoid assuming that peer-to-peer trust can substitute for authorization. If an agent can recruit another agent, the receiving agent should validate the request independently rather than inherit trust from the sender.
Edge cases include delegated approvals, fallback routing, and multi-agent chains that mix human-in-the-loop checkpoints with automated hops. In those patterns, the most common failure is scope creep, where one approved task gradually becomes a broader action set. The AI Agents: The New Attack Surface report is a useful reminder that agent behaviour frequently exceeds intended scope, which makes revocation and auditability non-negotiable. For policy detail, the OWASP Top 10 for Agentic Applications 2026 remains one of the clearest external references.
In practice, the hardest failures appear when legacy IAM, shared secrets, and unclear delegation semantics are bolted onto agentic workflows after deployment rather than designed in from the start.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Agentic AI Top 10 and CSA MAESTRO address the attack and risk surface, while NIST AI RMF set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Agentic AI Top 10 | A2A-01 | Covers unsafe agent-to-agent delegation and trust chaining. |
| CSA MAESTRO | M1 | Applies to identity, orchestration, and control of autonomous agent workflows. |
| NIST AI RMF | Supports governance, accountability, and risk controls for AI systems. |
Use AI RMF governance processes to assign ownership, monitor behavior, and document escalation paths.
Related resources from NHI Mgmt Group
Deepen Your Knowledge
Reviewed and updated by the NHIMG editorial team on June 8, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
