AgenticDome Research

Research on the future of agentic AI security

Begin with the security question you need to answer, then move to the platform, governance, or market analysis relevant to your role. The newest papers connect discovery, runtime attachment, exact-action authorization, safe policy release and verified outcomes while separating current AgenticDome controls from the customer’s responsibilities.

AgenticDome Research Team·Updated September 4, 2026·RSS feed
Choose your path

What are you trying to do?

Use these four collections as a reading path. You do not need to scan a wall of unrelated articles.

Start here

Understand the runtime security problem

For security leaders, architects, and reviewers who need the core threat model: where conventional controls stop, how a Verified Action Chain works, and how identity, runtime coverage and outcome evidence fit together.

Runtime Intelligence

Beyond the SDK: A Runtime Intelligence Grid for the Agentic Enterprise

AgenticDome Research Team · Published September 7, 2026 · Updated September 7, 2026

How AgenticDome unifies application, workload and network evidence to reveal emerging AI activity, distinguish protected execution and guide enterprise response.

  • Application, workload and network evidence in one operating picture
  • Protected execution distinguished from suspected bypass
  • One investigation workflow across Monitor & Respond
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Category Thesis

The State of Play in Agentic AI Security

AgenticDome Research Team · Published July 24, 2026 · Updated August 25, 2026

Why the market is moving beyond prompt filtering and toward an Agentic Interaction Control Plane.

  • Market shift from copilots to autonomous agents
  • Predicted growth in enterprise agent volumes
  • How AgenticDome frames the new category
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Runtime Architecture

The Five Protection Points

AgenticDome Research Team · Published July 24, 2026 · Updated August 25, 2026

A practical reference architecture for securing manager-worker agent flows and tool execution.

  • Inbound prompt screening
  • A2A delegation authorization
  • Tool authorization, output sanitization, and decision verification
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Verified Action Architecture

The Verified Action Protocol: Proof from Intent to Impact

AgenticDome Research Team · Published September 4, 2026 · Updated September 4, 2026

How exact-action passports, receiving-boundary admission, delegation verification and tiered outcome receipts create a machine-verifiable action chain.

  • Single-use authority bound to action and destination
  • Policy version, trust epoch and delegation lineage
  • Machine-verifiable evidence without raw secrets
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Runtime Assurance

Runtime Coverage Verification: Is Protection Still Attached?

AgenticDome Research Team · Published September 4, 2026 · Updated September 4, 2026

Why a passing integration test is not continuous assurance—and how signed manifests, fresh hook heartbeats and exact gaps expose runtime drift.

  • Production readiness and live coverage are separate
  • Expected-versus-observed protection points
  • Scoped evidence that never infers invisible paths
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Outcome Assurance

An Allow Decision Is Not an Outcome

AgenticDome Research Team · Published September 4, 2026 · Updated September 4, 2026

Close the loop with tiered receipts that bind observed execution, destination and a non-sensitive side-effect reference to the authorised action.

  • SDK, gateway and destination assurance stay distinct
  • Authorised-versus-observed deviation detection
  • Privacy-bounded verification bundles
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Identity & Runtime Trust

An Agent Principal Proves Who. It Does Not Prove Why.

AgenticDome Research Team · Published July 24, 2026 · Updated August 25, 2026

Why distinct non-human identity is essential—and why a valid principal still needs action-level authorization before an agent changes production state.

  • Keep IAM authoritative for identity and entitlement
  • Join actor, agent, purpose, tool, and final arguments
  • Preserve delegated authority and runtime evidence
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MCP Defence in Depth

MCP Security Is Necessary. It Is Not the Final Action Decision.

AgenticDome Research Team · Published July 24, 2026 · Updated August 25, 2026

Keep OAuth, consent, token, session, scope, sandbox, and server controls—then add policy for the exact business action travelling through the protocol.

  • Protocol authorization and action policy solve different problems
  • Stateless scaling does not prove safe intent
  • No customer Redis required for normal SDK decisions
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Build and integrate

Find your platform or execution boundary

For developers and platform teams. Choose the framework, cloud, MCP, Microsoft or data-protection article matching the service that owns the execution or knowledge boundary.

MCP Security

MCP Connects Agents to Tools. AgenticDome Governs the Action.

AgenticDome Research Team · Published July 24, 2026 · Updated August 25, 2026

Move beyond connection security: authorize the exact actor, agent, server, tool, and arguments before forwarding, then review what comes back.

  • Business authorization beyond OAuth and server access
  • One governed boundary across internal and external MCP servers
  • Request control, returned-content review, lineage, and evidence
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Python Frameworks

One Action Policy Across Python Agent Frameworks

AgenticDome Research Team · Published July 24, 2026 · Updated August 25, 2026

Let developers choose CrewAI, LangGraph, Microsoft, OpenAI, Claude, Agno, or custom Python without creating a different security posture for every team.

  • Framework-shaped adapters with one tenant policy vocabulary
  • Tool and handoff authorization before real execution
  • Network-free evaluation followed by live regional or Sovereign enforcement
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Graph & RAG

Protect the Whole Graph and RAG Journey

AgenticDome Research Team · Published July 24, 2026 · Updated August 25, 2026

Make routing, retrieval, privileged transitions, tools, delegation, streaming, and output answer to policy—not only the first prompt.

  • Stop poisoned retrieval before it becomes trusted context
  • Gate sensitive edges and tools before state changes
  • Carry actor, agent, purpose, and lineage across the workflow
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Cloud Runtimes

Put Policy Between Cloud Agents and Production Impact

AgenticDome Research Team · Published July 24, 2026 · Updated August 25, 2026

Use trusted cloud identity plus action context to decide whether Microsoft Foundry, Google ADK, and Amazon Bedrock application paths should act now.

  • Turn cloud identity from access into action-aware policy context
  • Stop high-impact local handlers before production state changes
  • Unify Microsoft, Google, and AWS decision evidence
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Copilot Studio Preview

Give Copilot Studio Tools an Independent Policy Decision

AgenticDome Research Team · Published July 24, 2026 · Updated August 25, 2026

Use Microsoft’s native external-provider path to send eligible proposed tool calls to AgenticDome before execution—without rewriting each covered tool.

  • Configuration-led setup with an assigned endpoint and Entra trust
  • Business-action policy using Microsoft-provided tool context
  • One governance model across Microsoft and non-Microsoft agents
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Copilot Studio + MCP

Copilot Studio Can Choose the Tool. Who Authorizes the Action?

AgenticDome Research Team · Published July 24, 2026 · Updated August 25, 2026

How MCP-connected capabilities, generative orchestration, Microsoft’s external-provider hook, and AgenticDome fit together before an eligible tool runs.

  • Use Microsoft’s supported pre-tool decision point
  • Keep MCP and Power Platform controls intact
  • Apply one tenant policy across a mixed agent estate
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OpenClaw Security

Authorize OpenClaw Capabilities at the Point of Use

AgenticDome Research Team · Published July 24, 2026 · Updated August 25, 2026

Do not let installation become permanent trust: govern supported prompts, tools, delegated actions, and transcript persistence through native hooks.

  • Per-use tool decisions before execution
  • Delegated-action verification at the specialist boundary
  • Sensitive-result redaction before supported transcript persistence
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TypeScript Services

Put Agent Policy Where TypeScript Services Hold the Credentials

AgenticDome Research Team · Published July 24, 2026 · Updated August 25, 2026

Turn the Node.js dispatcher that can actually call a tool or business API into a tenant-governed action firewall.

  • Authorize final arguments at the last responsible moment
  • Verify downstream agent authority before execution
  • Bind brokered decisions to the actual outbound request
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Discovery & Data Protection

Privacy-Preserving Agent Discovery and Data Protection

AgenticDome Research Team · Published September 4, 2026 · Updated September 4, 2026

Connect bounded agent discovery, runtime content decisions and Microsoft knowledge-permission remediation without centralising source or document content.

  • Proprietary interception analysis remains private
  • Explicit multimodal evidence and policy boundaries
  • Approval-gated Microsoft permission removal
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Govern and assure

Translate guidance into operating evidence

For governance, risk, compliance, and audit teams connecting policy frameworks to immutable drafts, impact projection, canary release, accountable ownership, live controls and evidence.

AI Governance

From ASD Agentic AI Guidance to Runtime Control

AgenticDome Research Team · Published July 24, 2026 · Updated August 25, 2026

A factual mapping of the May 2026 joint ASD/ACSC guidance to identity, bounded execution, tool validation, oversight, monitoring, and runtime evidence.

  • Start bounded and keep agents least-privileged
  • Separate human approval from runtime enforcement
  • Use AgenticDome as one defence-in-depth layer
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Policy Operations

Safe Policy Deployment for AI Agents

AgenticDome Research Team · Published September 4, 2026 · Updated September 4, 2026

Move from global template to immutable tenant draft, bounded impact projection, deterministic canary and explicit promotion without direct live-policy editing.

  • Observe-only, source-free starting point
  • Historical metadata projection with explicit limits
  • Canary, rollback and tenant-approved promotion
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AI Risk Management

NIST AI RMF and Agentic AI

AgenticDome Research Team · Published July 24, 2026 · Updated August 25, 2026

How the NIST AI Risk Management Framework applies to agentic systems and runtime controls.

  • Govern, Map, Measure, Manage
  • Trustworthy AI characteristics
  • Runtime evidence for agentic AI risk
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AI Regulation

EU AI Act, Agentic AI, and Runtime Assurance

AgenticDome Research Team · Published July 24, 2026 · Updated August 25, 2026

A succinct guide to the EU AI Act and what it means for businesses deploying agentic systems.

  • EU AI Act risk tiers
  • High-risk AI obligations
  • How AgenticDome can support runtime assurance
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Evaluate the market

Compare adjacent platforms and control layers

For buyers and strategists assessing where AgenticDome fits alongside agent platforms, frameworks, cloud and security products. These are directional analyses, not vendor certifications.

Platform Comparison

Platform Security vs AgenticDome

AgenticDome Research Team · Published July 24, 2026 · Updated August 25, 2026

Where Microsoft, Salesforce, and ServiceNow lead — and where cross-platform agentic gaps remain.

  • Microsoft Copilot Studio
  • Salesforce Agentforce
  • ServiceNow Now Assist and AI Agent Studio
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Framework Security

Agent Frameworks Need a Runtime Security Partner

AgenticDome Research Team · Published July 24, 2026 · Updated August 25, 2026

How LangGraph, CrewAI, PydanticAI, OpenAI Agents SDK, Semantic Kernel, LlamaIndex, Haystack and others create new runtime security gaps.

  • Framework-by-framework security gaps
  • Why native hooks are not enough
  • How AgenticDome protects framework-driven agents
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Market Map

The 2026 Agentic Platform Market Map

AgenticDome Research Team · Published July 24, 2026 · Updated August 25, 2026

A directional view of where enterprise and open-source agent platforms are concentrating adoption and budget.

  • Enterprise platforms vs open-source frameworks
  • Predicted agent volumes and agent sprawl
  • The common security challenge across all platforms
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Agents are becoming enterprise actors. Their actions need a control plane.

Explore AgenticDome’s perspective on securing autonomous workflows, agent-to-agent communication, memory, tools, runtime decisions, and AI governance obligations across heterogeneous enterprise environments.

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