AI Defense Matrix Catalog

Agent Governance Toolkit

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Overview

Product details compiled from public sources, each with a citation.

Vendor
Microsoft1
Description
Open-source Microsoft project enforcing runtime policy on autonomous agent actions, with zero-trust agent identity, MCP gateway checks, and tamper-evident audit logs.1
Deployment
Self-hosted1
Status
Active1

Matrix Coverage

Where this product defends, by asset class and NIST CSF function. The Coverage column shows whether each asset is Primary, Secondary, or Adjacent to what the product does. The table omits empty rows and columns.

Asset class IdentifyProtectDetectRespond Coverage
AI Orchestration Tools Primary 1
Runtime AI Data Adjacent 1
AI Agent Identities Secondary 1

Framework Relevance

These frameworks include controls relevant to the asset classes Agent Governance Toolkit defends. This is an editorial inference from the AI Defense Matrix asset-level crossmap, not a statement that Microsoft implements these controls or is certified against them.

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Framework Asset class Relevant controls
NIST IR 8596 AI Orchestration Tools Agents as deployed artifacts (orchestration view; see AI Agent Identities row for the principal view); system prompts and templates
Runtime AI Data Prompts (runtime); inference data
AI Agent Identities Agents as autonomous principals; Keys; Integrations and permissions
CSA AI Controls Matrix AI Orchestration Tools Application and Interface Security; Supply Chain Management
Runtime AI Data Data Security and Privacy Lifecycle Management; Application and Interface Security
AI Agent Identities IAM; Governance, Risk and Compliance
ISO 42001 AI Orchestration Tools A.6 AI system life cycle; A.5 Assessing impacts of AI systems
Runtime AI Data A.7 Data for AI systems; A.8 Information for interested parties
AI Agent Identities A.9 Use of AI systems; A.3 Internal organization; A.5 Assessing impacts of AI systems
Google SAIF AI Orchestration Tools Secure the AI supply chain; application and pipeline security; agent orchestration controls
Runtime AI Data Expand AI red-teaming; runtime input and output safety; prompt defense
AI Agent Identities Focus on Agents (explicit SAIF section); identity, authorization, and delegation controls
SANS Critical AI Security Guidelines AI Orchestration Tools Secure Agentic Systems and AI Autonomy Controls (defined function scope; execution isolation; API and function-call gating); Limit Model Behavior (focused functionality; access controls outside the model)
Runtime AI Data Model I/O Handling (sanitize, validate, and filter inputs and outputs; segregate user and system prompts; multilayered prompt-injection defense); Conventional Security Controls (protect augmentation and RAG data with vector-store access controls and validation); Data Minimization and Obfuscation (limit sensitive prompt content; context-window management); Limit Model Behavior (AI guardrails)
AI Agent Identities Secure Agentic Systems and AI Autonomy Controls (defined function scope; API and function-call gating; escalation and fallback); Limit Model Behavior (least-privilege focused functionality; human oversight; override capabilities)
MITRE ATLAS AI Orchestration Tools AML.T0051 LLM Prompt Injection; AML.T0054 LLM Jailbreak; AML.T0016 Obtain Capabilities (malicious plugins)
Runtime AI Data AML.T0051 LLM Prompt Injection; AML.T0054 LLM Jailbreak; AML.T0056 Extract LLM System Prompt
AI Agent Identities AML.T0053 AI Agent Tool Invocation; credential and delegation-chain abuse
OWASP AI Exchange AI Orchestration Tools Development-time threats: agent framework supply chain; runtime threats: plugin abuse, prompt injection via tools
Runtime AI Data Input threats: prompt injection, adversarial inputs, evasion; runtime threats: RAG poisoning, memory tampering
AI Agent Identities Runtime threats: unauthorized agent actions, capability abuse, delegation chain exploitation
OWASP LLM Top 10 AI Orchestration Tools LLM01 Prompt Injection; LLM05 Improper Output Handling; LLM07 System Prompt Leakage; LLM10 Unbounded Consumption
Runtime AI Data LLM01 Prompt Injection; LLM02 Sensitive Information Disclosure; LLM08 Vector and Embedding Weaknesses; LLM05 Improper Output Handling
AI Agent Identities LLM06 Excessive Agency; LLM05 Improper Output Handling; unauthorized actions by AI agents
OWASP Agentic Security Top 10 AI Orchestration Tools ASI01 Agent Goal Hijack; ASI02 Tool Misuse and Exploitation; ASI05 Unexpected Code Execution (RCE); ASI07 Insecure Inter-Agent Communication; ASI08 Cascading Failures; ASI10 Rogue Agents
Runtime AI Data ASI06 Memory & Context Poisoning; ASI01 Agent Goal Hijack (via prompt injection in runtime inputs)
AI Agent Identities ASI03 Identity and Privilege Abuse; ASI10 Rogue Agents; ASI09 Human-Agent Trust Exploitation; ASI02 Tool Misuse and Exploitation (when tied to agent permissions)

Provenance

Last sourced 2026-07-04.

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Sources

  1. Agent Governance Toolkit repository
    Vendor source accessed 2026-07-04
    • “safe_tool evaluates your YAML policy on every call, logs the decision, and raises GovernanceDenied if the action is blocked.”
    • “Shadow AI Discovery Find unregistered agents across processes, configs, and repos”
    • “PromptDefense Evaluator 12-vector prompt injection audit”

Changelog

  1. Corrected matrix_coverage (erratum): narrowed the orchestration and identity row functions and re-anchored the identity and runtime coverage quotes to the repository.

  2. Added to the catalog from the Microsoft Open Source Blog announcement and the project repository; in public preview per the repository README.

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