Agentic Control Plane Blueprint

What this is. The blueprint is the executive and architecture layer above the generated packs. It explains how SecurityRecipes becomes a credible secure context layer for agentic AI, not just a documentation site or recipe catalog.

SecurityRecipes already has the hard parts of an enterprise agentic program: secure context trust, MCP gateway policy, authorization conformance, connector trust, non-human identity, entitlement review, memory boundaries, skill supply-chain checks, agent handoff boundaries, egress decisions, run receipts, red-team drills, readiness scoring, catastrophic-risk gates, measurement probes, and an enterprise trust-center export.

The Agentic Control Plane Blueprint turns those individual artifacts into one product story a reviewer, AI platform owner, security architect, GRC reviewer, or reviewer can evaluate quickly:

  • What is the reference architecture?
  • Which generated packs prove each layer?
  • Which MCP tools expose the evidence to agents and review portals?
  • Which current industry references does the architecture track?
  • Which standards controls map to generated evidence instead of prose?
  • What is the path from open knowledge to production MCP adoption proof?

Generated artifact

  • Source model: data/assurance/agentic-control-plane-blueprint.json
  • Generator:
  • Evidence pack: data/evidence/agentic-control-plane-blueprint.json
  • MCP tool: recipes_agentic_control_plane_blueprint

Regenerate and validate the pack:

Why this matters

Agentic security is moving from “can we prompt the model safely?” to “can we govern the action layer?” NIST’s 2026 AI Agent Standards Initiative emphasizes interoperable standards, community protocols, agent authentication and identity, and security evaluations. OWASP’s Agentic Top 10 frames the new risk surface around goal hijack, tool misuse, identity abuse, agentic supply chain, memory and context poisoning, cascading failures, and rogue-agent behavior. The current MCP authorization specification adds concrete requirements around resource indicators, token audience validation, PKCE, HTTPS, client metadata, and forbidden token passthrough.

That is exactly where SecurityRecipes should sit: between agents and the systems they want to use, making context and authority understandable, queryable, and enforceable.

Blueprint layers

Layer What it proves Core evidence
Workflow scope and default-deny control Agents only run declared workflows and undeclared tool calls fail closed. Workflow manifest, MCP gateway policy, assurance pack, readiness scorecard
Secure context provenance Returned context has owner, trust tier, source hash, citation rule, poisoning scan, workflow package hash, and source-to-run lineage. Secure Context Trust Pack, Secure Context Lineage Ledger, Context Poisoning Guard, Agentic System BOM, Measurement Probes
MCP authorization and connector trust Remote MCP servers are reviewed for token audience, resource binding, PKCE, scope drift, and connector trust. Connector Trust Pack, Connector Intake Pack, Authorization Conformance, Gateway Policy
Agent handoff and protocol boundaries A2A Agent Cards, MCP, provider-native, and approval-bridge handoffs carry only approved metadata, cited evidence, and explicit authority state. A2A Agent Card Trust Profile, Agent Handoff Boundary Pack, Secure Context Trust Pack, Context Egress Boundary, Agent Identity Ledger
Agent identity, delegation, and entitlements Every agent run has owner, delegated scope, explicit denies, expiring permission lease, review linkage, and revocation expectations. Agent Identity Ledger, Agentic Entitlement Review Pack, Gateway Policy, Run Receipt Pack, Capability Risk Register
Memory, skill, and runtime boundaries Skills, rules files, hooks, vector memory, and persistent memory cannot silently inherit authority. Memory Boundary Pack, Skill Supply-Chain Pack, Poisoning Guard, Red-Team Drills
Context egress and data boundaries Context does not leave tenant, model, telemetry, MCP, or public-corpus boundaries without policy. Context Egress Boundary, Secure Context Trust Pack, Run Receipts, Assurance Pack
Evidence receipts and Agentic System BOM Runs can be reconstructed from context, tools, policy decisions, approvals, verifiers, closure, and revocation. Run Receipt Pack, Agentic System BOM, Assurance Pack, Measurement Probes
Measurement, red-team replay, and threat alignment Current threat signals become probes, drills, readiness decisions, and roadmap actions. Threat Radar, Measurement Probe Pack, Red-Team Drill Pack, Readiness Scorecard
Standards crosswalk and diligence OWASP, NIST, MCP, and frontier-lab guidance map to generated evidence and MCP tools. Agentic Standards Crosswalk, Threat Radar, Control Plane Blueprint
Catastrophic risk and high-impact autonomy High-impact agent actions are held, denied, or killed when approval, identity, policy, risk acceptance, or receipt evidence is missing. Catastrophic Risk Annex, Capability Risk Register, Run Receipts, Readiness Scorecard
Enterprise trust-center export reviewer and trust review diligence can start from one compact packet with evidence paths, hashes, MCP tools, runtime fields, and diligence answers. Enterprise Trust Center Export, Threat Radar, Control Plane Blueprint

reviewer diligence questions

Use the generated buyer_due_diligence_matrix when a customer or reviewer asks for evidence:

Question Evidence path
Which context sources are allowed into an agent run, and how is source drift detected? recipes_secure_context_trust_pack, recipes_context_poisoning_guard_pack
How does the product prevent token passthrough, wrong-audience tokens, scope creep, and unreviewed MCP tools? recipes_mcp_authorization_conformance_pack, recipes_mcp_connector_trust_pack
Can the team reconstruct the exact policy, context, tool, approval, verifier, and egress path after an incident? recipes_agentic_run_receipt_pack, recipes_agentic_system_bom
Which workflows are ready to scale, which stay in a guarded pilot, and which are blocked? recipes_agentic_readiness_scorecard, recipes_agentic_measurement_probe_pack
Which current agentic AI, MCP, NIST, and prompt-injection references map to generated evidence? recipes_agentic_standards_crosswalk
What should a reviewer inspect first during procurement, platform review, or trust review diligence? recipes_enterprise_trust_center_export, recipes_agentic_control_plane_blueprint

Product strategy

The open project should stay useful and forkable. That is the adoption engine. The vendor value sits above it:

Stage Product surface
Open foundation MIT-licensed recipes, generated evidence packs, read-only MCP server, deterministic policy evaluators.
Production MCP server Hosted secure-context retrieval, context signing, MCP authorization conformance, connector trust monitoring, and run receipt storage.
Enterprise expansion Tenant evidence ingestion, identity-provider adapters, hosted red-team replay, measurement probes, and trust-center exports.
Strategic trust review fit Frontier labs, AI coding platforms, cloud platforms, and security vendors need a credible control layer for agentic tool use and context.

MCP examples

Get the full architecture summary:

{}

Get one blueprint layer:

{
  "layer_id": "mcp_authorization_and_connector_trust"
}

Get reviewer evidence for a diligence question:

{
  "question_id": "runtime-evidence"
}

Get only layers that need evidence attention:

{
  "status": "needs_attention"
}

Source anchors

The source model should be reviewed when these references change:

See also