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:

json

{
  "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:

json

{
  "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:

NameTypeRequiredLocationDescriptionassessmentDataAssessmentData objectYesBodyAssessment data containing maturity indicators for all 6 principles across conventional and AI dimensionssessionIdstringYesBodyUnique identifier for the assessment sessionuserIdinteger or nullNoBodyOptional user identifier associated with the assessmenttimestampstringYesBodyISO 8601 formatted timestamp of assessment submission

AssessmentData Fields:

FieldTypeRequiredDescriptionverification_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 detailsmicrosegmentation_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 sessiontimestampstringYesISO 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:

NameTypeRequiredLocationDescriptiondomain_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/MonthPriceFree550FreeDeveloper20500$39/moProfessional2005,000$99/moEnterprise100,0001,000,000$299/mo

About#

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

• toolweb.in
• portal.toolweb.in
• hub.toolweb.in
• toolweb.in/openclaw/
• rapidapi.com/user/mkrishna477
• youtube.com/@toolweb-009

References#

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