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toolweb-zero-trust-for-ai-maturity-assessmenttoolweb AI 成熟度评估的零信任

Agent Skill

toolweb-zero-trust-for-ai-maturity-assessment 用于补充运维相关能力,适合在 OpenClaw 中需要让 Agent 承接运维相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

3,143

周安装

135

GitHub Stars

公开资料未说明

下载量

1,102
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:toolweb-zero-trust-for-ai-maturity-assessment(toolweb AI 成熟度评估的零信任)
来源仓库:https://github.com/krishnakumarmahadevan-cmd/toolweb-zero-trust-for-ai-maturity-assessment
安装命令:
openclaw skills install toolweb-zero-trust-for-ai-maturity-assessment
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install toolweb-zero-trust-for-ai-maturity-assessment

简介

评估传统基础设施与 AI 时代下零信任架构的成熟度水平。

  • 适用于企业安全转型、AI 数据保护和模型访问控制场景。
  • 覆盖六个核心原则的多维度评分和改进建议生成。toolweb-zero-trust-for-ai-maturity-assessment 属于运维类 Skill,可作为该场景下的辅助能力补充。
  • 需结合组织实际架构和数据流分析,不能孤立看待评分结果。
  • 建议分阶段实施改进项,并建立持续监测机制跟踪演进效果。

SKILL.md

name
Zero Trust for AI Maturity Assessment
description
Evaluates Zero Trust maturity across 6 principles for both Conventional (Infrastructure) and AI Era (Data & Model) dimensions.

Overview

The Zero Trust for AI Maturity Assessment tool provides organizations with a comprehensive evaluation framework for implementing Zero Trust security principles in both traditional infrastructure and AI/ML environments. This tool assesses maturity across six critical Zero Trust principles: Verification, Least Privilege, Assume Breach, Microsegmentation, Continuous Monitoring, and Supply Chain Security.

The assessment is uniquely designed to evaluate two distinct dimensions: Conventional (Infrastructure) and AI Era (Data & Model). This dual-dimension approach recognizes that AI systems introduce novel security challenges requiring tailored Zero Trust strategies beyond traditional network and access controls. Organizations can benchmark their security posture, identify gaps, and prioritize remediation efforts with data-driven insights.

Ideal users include security architects, CISOs, AI/ML team leaders, and enterprise security teams seeking to implement Zero Trust frameworks that account for both legacy infrastructure and emerging AI workloads. The tool supports compliance initiatives, risk assessments, and strategic security planning.

Usage

Example Request:

{
  "sessionId": "sess-abc123def456",
  "userId": 1001,
  "timestamp": "2024-01-15T10:30:00Z",
  "assessmentData": {
    "sessionId": "sess-abc123def456",
    "timestamp": "2024-01-15T10:30:00Z",
    "verification_conventional": {
      "mfa_enabled": true,
      "mfa_coverage_percent": 95,
      "device_verification": "enabled"
    },
    "verification_ai": {
      "model_provenance_tracking": true,
      "data_lineage_implemented": true
    },
    "least_privilege_conventional": {
      "rbac_implemented": true,
      "principle_of_least_privilege_score": 78
    },
    "least_privilege_ai": {
      "model_access_controls": true,
      "training_data_access_restricted": true
    },
    "assume_breach_conventional": {
      "segmentation_level": "advanced",
      "incident_response_plan": "documented"
    },
    "assume_breach_ai": {
      "model_poisoning_detection": true,
      "adversarial_testing_frequency": "quarterly"
    },
    "microsegmentation_conventional": {
      "network_segments": 12,
      "segment_isolation_score": 85
    },
    "microsegmentation_ai": {
      "model_isolation": true,
      "inference_sandbox": "enabled"
    },
    "continuous_monitoring_conventional": {
      "siem_deployed": true,
      "log_retention_days": 365
    },
    "continuous_monitoring_ai": {
      "model_drift_monitoring": true,
      "inference_anomaly_detection": "enabled"
    },
    "supply_chain_conventional": {
      "vendor_assessment_process": "defined",
      "sbom_requirement": true
    },
    "supply_chain_ai": {
      "model_source_verification": true,
      "training_data_provenance_verified": true
    }
  }
}

Example Response:

{
  "status": "success",
  "assessment_id": "ztai-2024-001",
  "sessionId": "sess-abc123def456",
  "timestamp": "2024-01-15T10:30:45Z",
  "overall_maturity_score": 82,
  "conventional_maturity_score": 84,
  "ai_maturity_score": 80,
  "principle_scores": {
    "verification": {
      "conventional": 95,
      "ai": 88
    },
    "least_privilege": {
      "conventional": 78,
      "ai": 82
    },
    "assume_breach": {
      "conventional": 80,
      "ai": 75
    },
    "microsegmentation": {
      "conventional": 85,
      "ai": 78
    },
    "continuous_monitoring": {
      "conventional": 88,
      "ai": 85
    },
    "supply_chain": {
      "conventional": 72,
      "ai": 68
    }
  },
  "recommendations": [
    {
      "principle": "supply_chain_ai",
      "priority": "high",
      "action": "Implement model source verification and training data provenance tracking"
    },
    {
      "principle": "assume_breach_ai",
      "priority": "medium",
      "action": "Increase adversarial testing frequency and enhance model poisoning detection"
    }
  ]
}

Endpoints

GET /

Health Check Endpoint

Performs a basic health check to verify the API is operational.

Parameters: None

Response:

  • Status: 200 OK
  • Content-Type: application/json
  • Body: Health status confirmation

POST /api/zt-ai/assess

Assess Zero Trust for AI Maturity

Generates a comprehensive Zero Trust for AI maturity assessment based on provided assessment data across both conventional and AI dimensions.

Parameters:

NameTypeRequiredLocationDescription
assessmentDataAssessmentData objectYesBodyAssessment data containing maturity indicators for all 6 principles across conventional and AI dimensions
sessionIdstringYesBodyUnique identifier for the assessment session
userIdinteger or nullNoBodyOptional user identifier associated with the assessment
timestampstringYesBodyISO 8601 formatted timestamp of assessment submission

AssessmentData Fields:

FieldTypeRequiredDescription
verification_conventionalobjectNoConventional infrastructure verification controls (MFA, device verification, etc.)
verification_aiobjectNoAI-era verification controls (model provenance, data lineage, etc.)
least_privilege_conventionalobjectNoConventional least privilege implementation (RBAC, permission scoping)
least_privilege_aiobjectNoAI-era least privilege (model access, training data access)
assume_breach_conventionalobjectNoConventional breach assumption controls (segmentation, incident response)
assume_breach_aiobjectNoAI-era breach assumption (model poisoning detection, adversarial testing)
microsegmentation_conventionalobjectNoConventional network microsegmentation details
microsegmentation_aiobjectNoAI-era microsegmentation (model isolation, inference sandbox)
continuous_monitoring_conventionalobjectNoConventional monitoring capabilities (SIEM, log retention)
continuous_monitoring_aiobjectNoAI-era monitoring (model drift, inference anomaly detection)
supply_chain_conventionalobjectNoConventional supply chain security (vendor assessment, SBOM)
supply_chain_aiobjectNoAI-era supply chain security (model verification, data provenance)
sessionIdstringYesUnique identifier for the assessment session
timestampstringYesISO 8601 formatted timestamp

Response:

  • Status: 200 OK
  • Content-Type: application/json
  • Body: Detailed maturity assessment with overall scores, principle-specific scores, and recommendations

Error Responses:

  • Status: 422 Unprocessable Entity (validation error)

GET /api/zt-ai/principles

Get All Zero Trust Principle Definitions

Retrieves detailed definitions and guidelines for all six Zero Trust principles as they apply to both conventional and AI dimensions.

Parameters: None

Response:

  • Status: 200 OK
  • Content-Type: application/json
  • Body: Array of principle definitions with descriptions, assessment criteria, and best practices for conventional and AI contexts

GET /api/zt-ai/domain/{domain_key}

Get Domain Details

Retrieves detailed information, assessment guidance, and benchmark data for a specific Zero Trust domain.

Parameters:

NameTypeRequiredLocationDescription
domain_keystringYesPathThe key identifier for a Zero Trust principle or domain (e.g., "verification_conventional", "assume_breach_ai")

Response:

  • Status: 200 OK
  • Content-Type: application/json
  • Body: Detailed domain information including assessment criteria, maturity levels, implementation guidelines, and reference controls

Error Responses:

  • Status: 422 Unprocessable Entity (validation error)

Pricing

PlanCalls/DayCalls/MonthPrice
Free550Free
Developer20500$39/mo
Professional2005,000$99/mo
Enterprise100,0001,000,000$299/mo

About

ToolWeb.in - 200+ security APIs, CISSP & CISM, platforms: Pay-per-run, API Gateway, MCP Server, OpenClaw, RapidAPI, YouTube.

References

  • Kong Route: https://api.toolweb.in/security/zertruforaimatass
  • API Docs: https://api.toolweb.in:8161/docs

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

96.19%
按下载量换算1,060

安全审计

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通过

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通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

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来源信息

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