@bibryam: AI Agent Governance Toolkit - by Microsoft Runtime governance for AI agents through deterministic policy enforcement, z…

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Summary

Microsoft released the Agent Governance Toolkit, an open-source runtime enforcement tool for AI agents that provides deterministic policy enforcement, zero-trust identity, and sandboxing, covering all 10 OWASP Agentic risks with over 13,000 tests.

AI Agent Governance Toolkit - by Microsoft Runtime governance for AI agents through deterministic policy enforcement, zero-trust identity, execution sandboxing, and SRE for autonomous agents. Covers all 10 OWASP Agentic risks with 13,000+ tests. https://github.com/microsoft/agent-governance-toolkit…
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AI Agent Governance Toolkit - by Microsoft Runtime governance for AI agents through deterministic policy enforcement, zero-trust identity, execution sandboxing, and SRE for autonomous agents. Covers all 10 OWASP Agentic risks with 13,000+ tests. https://github.com/microsoft/agent-governance-toolkit…


microsoft/agent-governance-toolkit

Source: https://github.com/microsoft/agent-governance-toolkit

🌍 English | 日本語 | 简体中文 | 한국어

Agent Governance Toolkit

Agent Governance Toolkit

📖 Docs · 🚀 Quick Start · 📋 Specifications · 📦 PyPI · 📝 Changelog

CI License: MIT PyPI version npm NuGet OpenSSF Scorecard OpenSSF Best Practices OWASP Agentic Top 10

Public Preview – production-quality, Microsoft-signed releases. May have breaking changes before GA.

Runtime governance for AI agents. Every tool call, resource access, and inter-agent message is evaluated against policy before execution – deterministic, sub-millisecond, and auditable.

Agent Action ──► Policy Check ──► Allow / Deny ──► Audit Log    (< 0.1 ms)

Prompt-based safety (“please follow the rules”) has a 26.67% policy violation rate in red-team testing. AGT’s application-layer enforcement: 0.00%.

Python · TypeScript · .NET · Rust · Go. Works with LangChain, CrewAI, AutoGen, OpenAI Agents, Google ADK, Semantic Kernel, AWS Bedrock, and 20+ more.


Quick Start

pip install agent-governance-toolkit[full]
from agent_os.policies import (
    PolicyEvaluator, PolicyDocument, PolicyRule,
    PolicyCondition, PolicyAction, PolicyOperator, PolicyDefaults
)

evaluator = PolicyEvaluator(policies=[PolicyDocument(
    name="my-policy", version="1.0",
    defaults=PolicyDefaults(action=PolicyAction.ALLOW),
    rules=[PolicyRule(
        name="block-dangerous-tools",
        condition=PolicyCondition(
            field="tool_name",
            operator=PolicyOperator.IN,
            value=["execute_code", "delete_file"]
        ),
        action=PolicyAction.DENY, priority=100,
    )],
)])

result = evaluator.evaluate({"tool_name": "web_search"})    # ✅ Allowed
result = evaluator.evaluate({"tool_name": "delete_file"})   # ❌ Blocked
TypeScript / .NET / Rust / Go examples

TypeScript

import { PolicyEngine } from "@microsoft/agent-governance-sdk";

const engine = new PolicyEngine([
  { action: "web_search", effect: "allow" },
  { action: "shell_exec", effect: "deny" },
]);
engine.evaluate("web_search"); // "allow"
engine.evaluate("shell_exec"); // "deny"

.NET

using AgentGovernance;
using AgentGovernance.Extensions.ModelContextProtocol;
using AgentGovernance.Policy;

var kernel = new GovernanceKernel(new GovernanceOptions
{
    PolicyPaths = new() { "policies/default.yaml" },
});
var result = kernel.EvaluateToolCall("did:mesh:agent-1", "web_search",
    new() { ["query"] = "latest AI news" });

// MCP server integration
builder.Services.AddMcpServer()
    .WithGovernance(options => options.PolicyPaths.Add("policies/mcp.yaml"));

Rust

use agent_governance::{AgentMeshClient, ClientOptions};

let client = AgentMeshClient::new("my-agent").unwrap();
let result = client.execute_with_governance("data.read", None);
assert!(result.allowed);

Go

import agentmesh "github.com/microsoft/agent-governance-toolkit/agent-governance-golang"

client, _ := agentmesh.NewClient("my-agent",
    agentmesh.WithPolicyRules([]agentmesh.PolicyRule{
        {Action: "data.read", Effect: agentmesh.Allow},
        {Action: "*", Effect: agentmesh.Deny},
    }),
)
result := client.ExecuteWithGovernance("data.read", nil)

CLI tools:

agt doctor                                        # check installation
agt verify                                        # OWASP compliance check
agt verify --evidence ./agt-evidence.json --strict # fail CI on weak evidence
agt red-team scan ./prompts/ --min-grade B         # prompt injection audit
agt lint-policy policies/                          # validate policy files

Full walkthrough: quickstart.md – zero to governed agents in 10 minutes with YAML, OPA/Rego, and Cedar policies. 🌍 Also in: 日本語 | 简体中文 | 한국어


Core Capabilities

Policy Engine

Deterministic allow/deny evaluation for every agent action. Sub-millisecond latency (0.012ms p50 for single rule, 35K ops/sec concurrent). Supports YAML, OPA/Rego, and Cedar policy languages. Fail-closed by default – if the engine errors, the action is denied.

Agent OS · Benchmarks · Spec

Zero-Trust Identity

Ed25519 + quantum-safe ML-DSA-65 agent credentials. Behavioral trust scoring (0–1000) that decays when agents act outside expected patterns. SPIFFE/SVID compatible. Trust ceilings propagate through delegation chains – a delegated agent can never exceed its parent’s trust level.

AgentMesh · Spec

Execution Sandboxing

Four privilege rings (kernel, supervisor, user, untrusted) with hardware-style isolation semantics. Saga orchestration for multi-step workflows with automatic compensation on failure. Kill switch for immediate agent termination.

Runtime · Hypervisor · Spec

Agent SRE

SLOs, error budgets, replay debugging, chaos engineering, and circuit breakers for agent fleets. OTel-native observability with structured governance events.

Agent SRE · Spec

Audit and Compliance

Tamper-evident Merkle-chained audit logs. Reconstructible Decision BOMs from observability signals. Automated compliance mapping for EU AI Act, SOC 2, HIPAA, and GDPR. CloudEvents export for SIEM integration.

Compliance · Spec

MCP Security Gateway

Tool poisoning detection, description drift monitoring, typosquatting checks, and hidden instruction scanning for MCP tool definitions.

MCP Scanner · Spec

Additional Capabilities

CapabilityDescription
Inter-Agent TrustMesh-wide trust negotiation, peer signature verification, coordinated policy enforcement (Spec)
RL Training GovernanceViolation penalties in reward signals, episode termination on critical violations (Spec)
Framework Adapters10 adapters with unified governance interceptor chain (Spec)
Shadow AI DiscoveryFind unregistered agents across processes, configs, and repos (Discovery)
Agent LifecycleProvisioning, credential rotation, orphan detection, decommissioning (Lifecycle)
Governance DashboardReal-time fleet visibility for health, trust, and compliance (Dashboard)
PromptDefense Evaluator12-vector prompt injection audit (Evaluator)
Contributor ReputationPR/issue author screening for social engineering. Reusable GitHub Action (Action)

Specifications

Every major component has a formal RFC 2119 specification with conformance tests. These specs define the behavioral contract – what implementations MUST, SHOULD, and MAY do.

SpecificationScopeTests
Agent OS Policy EnginePolicy evaluation, rule merging, fail-closed semantics68
AgentMesh Identity and TrustCredentials, trust scoring, delegation chains135
Agent Hypervisor Execution ControlPrivilege rings, saga orchestration, kill switch80
AgentMesh Trust and CoordinationPeer trust negotiation, mesh-wide policy62
Agent SRE GovernanceSLOs, error budgets, chaos, circuit breakers111
MCP Security GatewayTool poisoning, drift detection, hidden instructions127
Agent Lightning Fast-PathRL training governance, violation penalties100
Framework Adapter Contract10 adapter integrations, interceptor chain152
Audit and ComplianceMerkle audit, compliance mapping, Decision BOM157
AgentMesh Wire ProtocolMessage format, routing, serialization

992 conformance tests ensure code stays aligned to specs. 25 Architecture Decision Records document why.


Framework Support

FrameworkIntegration
Microsoft Agent FrameworkNative Middleware
Semantic KernelNative (.NET + Python)
AutoGenAdapter
LangGraph / LangChainAdapter
CrewAIAdapter
OpenAI Agents SDKMiddleware
Google ADKAdapter
LlamaIndexMiddleware
HaystackPipeline
DifyPlugin
Azure AI FoundryDeployment Guide
GitHub Copilot CLIGovernance installer

Full list: Framework Integrations · Quickstart Examples


OWASP Agentic Top 10

AGT covers all 10 risks identified in the OWASP Agentic Security Top 10:

RiskAGT Control
ASI-01 Agent Goal HijackingPolicy engine blocks unauthorized goal changes
ASI-02 Excessive CapabilitiesCapability model enforces least-privilege
ASI-03 Identity & Privilege AbuseZero-trust identity with Ed25519 + ML-DSA-65
ASI-04 Uncontrolled Code ExecutionExecution rings + sandboxing
ASI-05 Insecure Output HandlingContent policies validate all outputs
ASI-06 Memory PoisoningEpisodic memory with integrity checks
ASI-07 Unsafe Inter-Agent CommsEncrypted channels + trust gates
ASI-08 Cascading FailuresCircuit breakers + SLO enforcement
ASI-09 Human-Agent Trust DeficitFull audit trails + flight recorder
ASI-10 Rogue AgentsKill switch + ring isolation + anomaly detection

Regulatory alignment: EU AI Act · NIST AI RMF · SOC 2


Install

LanguageCommand
Pythonpip install agent-governance-toolkit[full]
TypeScriptnpm install @microsoft/agent-governance-sdk
Copilot CLInpx @microsoft/agent-governance-copilot-cli install
.NETdotnet add package Microsoft.AgentGovernance
Rustcargo add agent-governance
Gogo get github.com/microsoft/agent-governance-toolkit/agent-governance-golang

All five languages implement core governance (policy, identity, trust, audit). Python has the full stack. See Language Package Matrix for per-language coverage.

Individual Python packages
PackagePyPIDescription
Agent OSagent-os-kernelPolicy engine, capability model, audit logging, MCP gateway
AgentMeshagentmesh-platformZero-trust identity, trust scoring, A2A/MCP/IATP bridges
Agent Runtimeagentmesh-runtimePrivilege rings, saga orchestration, termination control
Agent SREagent-sreSLOs, error budgets, chaos engineering, circuit breakers
Agent Complianceagent-governance-toolkitOWASP verification, integrity checks, policy linting
Agent Discoveryagent-discoveryShadow AI discovery, inventory, risk scoring
Agent Hypervisoragent-hypervisorExecution plan validation, reversibility verification
Agent Marketplaceagentmesh-marketplacePlugin lifecycle management
Agent Lightningagentmesh-lightningRL training governance

Security

AGT enforces governance at the Python middleware layer, not at the OS kernel level. The policy engine and agents share the same process boundary.

Production recommendation: Run each agent in a separate container for OS-level isolation. See Architecture – Security Boundaries.

ToolCoverage
CodeQLPython + TypeScript SAST
GitleaksSecret scanning on PR/push/weekly
ClusterFuzzLite7 fuzz targets (policy, injection, MCP, sandbox, trust)
Dependabot13 ecosystems
OpenSSF ScorecardWeekly scoring + SARIF upload

See Known Limitations for honest design boundaries and recommended layered defense.


Documentation

CategoryLinks
Getting StartedQuick Start · Tutorials (40+) · FAQ
ArchitectureSystem Design · Threat Model · ADRs (25)
SpecificationsAll Specs (10 formal specs, 992 conformance tests)
API ReferenceAgent OS · AgentMesh · Agent SRE
ComplianceOWASP · EU AI Act · NIST AI RMF · SOC 2
DeploymentAzure · AWS · GCP · Docker Compose
ExtensionsVS Code · Framework Integrations

Contributing

Contributing Guide · Community · Security Policy · Changelog

Using AGT? Add your organization to ADOPTERS.md.

Governance

DocumentPurpose
GOVERNANCE.mdDecision-making, roles, contributor ladder
CHARTER.mdTechnical charter (LF Projects format)
MAINTAINERS.mdMaintainers and organizations
SECURITY.mdVulnerability reporting and response SLAs
CODE_OF_CONDUCT.mdMicrosoft Open Source Code of Conduct

Important Notes

If you use the Agent Governance Toolkit to build applications that operate with third-party agent frameworks or services, you do so at your own risk. We recommend reviewing all data being shared with third-party services and being cognizant of third-party practices for retention and location of data.

License

This project is licensed under the MIT License.

Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft’s Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party’s policies.

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