{ "file_id": "09_vertical_government_public_sector", "version": "2026.03.16", "schema_version": "2.2", "status": "Production Authority", "last_authoritative_sync": "2026-03-16", "description": "Government and public-sector fields cover service delivery, procurement, records, security controls, and AI-use inventories. Use them to document a specific agency workflow.", "vertical_metadata": { "vertical_key": "government_public_sector", "industry": "Government & Public Sector", "primary_standards": [ "NIST SP 800-53 Rev 5, Security and Privacy Controls for Information Systems and Organizations (2020)", "NIST SP 800-53B, Control Baselines for Information Systems (2020)", "NIST SP 800-37 Rev 2, Risk Management Framework (RMF) for Information Systems (2018)", "NIST SP 800-171 Rev 3, Protecting CUI in Nonfederal Systems (2024)", "NIST AI RMF 1.0, AI Risk Management Framework (2023)", "NIST AI 600-1, Generative AI Profile (2024)", "FedRAMP Rev 5, Federal Risk and Authorization Management Program (GSA/OMB, 2023)", "FedRAMP Consolidated Rules for 2026, Cloud-service assessment and agency use", "FIPS 140-3, Security Requirements for Cryptographic Modules (2019)", "FIPS 199, Standards for Security Categorization of Federal Information and Information Systems", "FIPS 200, Minimum Security Requirements for Federal Information and Information Systems", "OMB M-25-21, Accelerating Federal Use of AI through Innovation, Governance, and Public Trust", "OMB M-23-22, Delivering a Digital-First Public Experience (September 2023)", "OMB M-22-09, Moving the US Government Toward Zero Trust Cybersecurity Principles", "OMB M-21-31, Improving the Federal Government's Investigative and Remediation Capabilities (log retention)", "EO 14028, Improving the Nation's Cybersecurity (May 2021)", "CISA JCDC AI Cybersecurity Collaboration Playbook (2024)", "FAR Part 12/39, Federal Acquisition Regulation for IT and AI procurement", "DFARS 252.204-7012, Safeguarding Covered Defense Information", "EU AI Act (2024/1689) Annex III point 5, Essential private and public services and benefits", "EU AI Act (2024/1689) Annex III para 6, High-risk AI in law enforcement", "EU AI Act (2024/1689) Annex III para 7, High-risk AI in migration, asylum, border control", "EU GDPR Article 22, Automated individual decision-making including profiling", "EU NIS2 Directive (2022/2555), Essential and important entities in public administration", "Council of Europe Framework Convention on AI (CETS 225), Opened for signature September 2024", "G7 Hiroshima AI Process, Guiding principles for advanced AI systems (2023)", "OECD Principles on AI (2019, updated 2024)", "UN General Assembly Resolution A/RES/78/311, International AI Governance (March 2024)" ], "primary_source_urls": [ "https://csrc.nist.gov/publications/detail/sp/800-53/rev-5/final", "https://www.fedramp.gov/", "https://www.whitehouse.gov/wp-content/uploads/2025/02/M-25-21-Accelerating-Federal-Use-of-AI-through-Innovation-Governance-and-Public-Trust.pdf", "https://www.fedramp.gov/2026/scope/", "https://www.fbi.gov/file-repository/cjis", "https://csrc.nist.gov/publications/detail/ai/100-1/final", "https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32024R1689" ], "otel_namespace": "government", "opa_namespace": "data.government", "agentic_ai_deployment_context": "Connect each agency workflow to its purpose, affected service, decision owner, and review outcome.", "key_regulatory_risk_note": "OMB M-25-21 replaced M-24-10. Its high-impact AI category depends on the use case, with scope and exceptions defined in the memorandum." }, "subdomains": [ { "subdomain": "FedRAMP & Cloud Security Authorisation", "description": "Record cloud-service authorization, system impact, and risk management progress. Keep the service assessment separate from the agency's authorization to operate its system.", "relevant_standards": [ "FedRAMP Rev 5, Federal Risk and Authorization Management Program (2023)", "NIST SP 800-37 Rev 2, Risk Management Framework", "NIST SP 800-53 Rev 5, Security and Privacy Controls", "FIPS 199, Security Categorization", "FIPS 200, Minimum Security Requirements" ], "categories": [ { "enum_name": "FedRAMPAuthorizationStatus", "label": "FedRAMP authorization status", "otel_attribute": "government.fedramp.authorization_status", "opa_policy_path": "data.government.fedramp.authorization_status", "rego_input_key": "government_fedramp_authorization_status", "stability": "stable", "description": "Recorded authorization status for the cloud service used by the workflow. Check the service boundary and agency authorization before using this status in a routing rule.", "permitted_values": [ "in_process", "fedramp_ready", "authorized_agency", "authorized_with_conditions", "revoked", "not_applicable_on_premise" ], "value_labels": { "in_process": "In Process", "fedramp_ready": "Fedramp Ready", "authorized_agency": "Authorized Agency", "authorized_with_conditions": "Authorized with Conditions", "revoked": "Revoked", "not_applicable_on_premise": "Not Applicable on Premise" }, "code_definitions": { "in_process": "Cloud service is actively pursuing FedRAMP authorisation; Readiness Assessment Report (RAR) or full security package in development; not yet authorised for production federal data", "fedramp_ready": "Readiness Assessment Report accepted by FedRAMP PMO; demonstrates high likelihood of achieving full authorisation; not yet authorised", "authorized_agency": "Full FedRAMP authorisation granted by a sponsoring federal agency (ATO); listed on FedRAMP Marketplace", "authorized_with_conditions": "FedRAMP ATO granted with specific conditions or Plan of Action and Milestones (POA&M) items that must be remediated within defined timeframes", "revoked": "The recorded authorization has been revoked. Apply the agency's routing restrictions and response procedures.", "not_applicable_on_premise": "System is deployed on-premise within the federal boundary; FedRAMP does not apply; FISMA authorisation required instead" }, "regulatory_mappings": { "fedramp": "Assess whether the cloud service and its use fall within FedRAMP scope. Reuse the applicable assessment package for the agency's authorization process.", "fisma": "The agency authorizing official accepts risk for the agency system. A provider assessment does not replace that decision." }, "use_case": "An agency rule stops a connected data transfer when the destination lacks the required authorization record. Reviewers inspect the service boundary and recorded conditions.", "source": "FedRAMP Rev 5 Authorisation Process documentation; FedRAMP Marketplace status definitions", "source_url": "https://www.fedramp.gov/documents-templates/" }, { "enum_name": "FIPSSecurityLevel", "label": "FIPS Security Level", "otel_attribute": "government.fips.security_level", "opa_policy_path": "data.government.fips.security_level", "rego_input_key": "government_fips_security_level", "stability": "stable", "description": "Security level recorded for a cryptographic module under FIPS 140-3. Keep the validation certificate and approved configuration with the module record.", "permitted_values": [ "level_1", "level_2", "level_3", "level_4" ], "value_labels": { "level_1": "Level 1", "level_2": "Level 2", "level_3": "Level 3", "level_4": "Level 4" }, "ordered": true, "value_ordinals": { "level_1": 1, "level_2": 2, "level_3": 3, "level_4": 4 }, "regulatory_mappings": { "fips_140_3": "FIPS 140-3 defines four security levels for cryptographic modules. Select the required level from the system's applicable security requirements." }, "use_case": "A configured rule stops an action when the reported module level falls below the system's requirement. Reviewers check the certificate and configuration before changing the record.", "source": "FIPS 140-3, Security Requirements for Cryptographic Modules (NIST, 2019)", "source_url": "https://csrc.nist.gov/publications/detail/fips/140/3/final" }, { "enum_name": "FISMAImpactLevel", "label": "FISMA Impact Level", "otel_attribute": "government.fisma.impact_level", "opa_policy_path": "data.government.fisma.impact_level", "rego_input_key": "government_fisma_impact_level", "stability": "stable", "description": "The system's assessed security impact level under FIPS 199. It reflects potential harm from a loss of confidentiality, integrity, or availability.", "permitted_values": [ "low", "moderate", "high" ], "value_labels": { "low": "Low", "moderate": "Moderate", "high": "High" }, "code_definitions": { "low": "A loss could have a limited adverse effect on operations, assets, or individuals.", "moderate": "A loss could have a serious adverse effect on operations, assets, or individuals.", "high": "A loss could have a severe or catastrophic adverse effect on operations, assets, or individuals." }, "ordered": true, "value_ordinals": { "low": 1, "moderate": 2, "high": 3 }, "regulatory_mappings": { "fips_199": "FIPS 199, Standards for Security Categorisation: all federal information and systems must be categorised", "nist_sp_800_53b": "NIST SP 800-53B, Control baselines: Low, Moderate, and High impact levels map to increasing control sets", "fedramp": "Use the assessed impact and applicable FedRAMP requirements when selecting a cloud service. The AI use case name does not determine the impact level." }, "source": "FIPS 199; FIPS 200; NIST SP 800-53B", "source_url": "https://csrc.nist.gov/publications/detail/fips/199/final" }, { "enum_name": "RMFLifecyclePhase", "label": "RMF Lifecycle Phase", "otel_attribute": "government.rmf.lifecycle_phase", "opa_policy_path": "data.government.rmf.lifecycle_phase", "rego_input_key": "government_rmf_lifecycle_phase", "stability": "stable", "description": "Current activity in the NIST Risk Management Framework. Monitoring continues during operation and supports ongoing authorization; this field is not an approval record.", "permitted_values": [ "prepare", "categorize", "select", "implement", "assess", "authorize", "monitor" ], "value_labels": { "prepare": "Prepare", "categorize": "Categorize", "select": "Select", "implement": "Implement", "assess": "Assess", "authorize": "Authorize", "monitor": "Monitor" }, "code_definitions": { "prepare": "Organisation- and system-level preparation activities; establish risk management strategy, assign roles (AO, ISSO, ISSM), register system in CSAM or equivalent", "categorize": "FIPS 199 categorisation of the system and information processed; document in System Security Plan (SSP)", "select": "Select, tailor, and document applicable NIST SP 800-53 Rev 5 security controls based on impact level and risk", "implement": "Implement selected security controls; document implementation in SSP; configure AI system and environment per controls", "assess": "Assess control implementation effectiveness; Security Assessment Report (SAR) produced by independent assessor (3PAO for FedRAMP)", "authorize": "Authorising Official (AO) reviews SAR and POA&M; issues Authority to Operate (ATO), Denial of ATO (DATO), or ATO with conditions", "monitor": "Ongoing monitoring of controls; continuous monitoring programme; annual assessments; significant change review" }, "ordered": true, "value_ordinals": { "prepare": 1, "categorize": 2, "select": 3, "implement": 4, "assess": 5, "authorize": 6, "monitor": 7 }, "regulatory_mappings": { "nist_sp_800_37": "NIST SP 800-37 Rev 2, Full RMF lifecycle required for all federal information systems", "fedramp": "FedRAMP maps directly to RMF; cloud services must complete all phases; 3PAO performs independent assessment in the 'assess' phase", "omb_m_25_21": "OMB M-25-21 Section 4 adds risk-management practices for covered high-impact AI. Applicable system authorization requirements continue separately." }, "source": "NIST SP 800-37 Rev 2, Risk Management Framework Steps", "source_url": "https://csrc.nist.gov/publications/detail/sp/800-37/rev-2/final" } ] }, { "subdomain": "NIST SP 800-53 Control Compliance Monitoring", "description": "Covers NIST SP 800-53 Rev 5 control family taxonomy and control assessment status enumerations for AI-driven continuous compliance monitoring. Federal AI compliance agents generating automated control evidence must tag each evidence record with the applicable control family and assessment status.", "relevant_standards": [ "NIST SP 800-53 Rev 5, 20 control families, 1000+ individual controls", "NIST SP 800-53A Rev 5, Assessing Security and Privacy Controls", "NIST SP 800-137A, Assessing Information Security Continuous Monitoring Programmes" ], "categories": [ { "enum_name": "NISTSPControlFamily", "label": "Nistsp Control Family", "otel_attribute": "government.nist_sp800_53.control_family", "opa_policy_path": "data.government.nist_sp800_53.control_family", "rego_input_key": "government_nist_sp800_53_control_family", "stability": "stable", "description": "NIST SP 800-53 Rev 5 control family identifier. All 20 control families are represented. AI compliance agents tag automated evidence generation and control assessment actions with the applicable family for CSAM/eMASS integration and audit trail.", "permitted_values": [ "AC_access_control", "AT_awareness_training", "AU_audit_accountability", "CA_assessment_authorisation_monitoring", "CM_configuration_management", "CP_contingency_planning", "IA_identification_authentication", "IR_incident_response", "MA_maintenance", "MP_media_protection", "PE_physical_environmental_protection", "PL_planning", "PM_program_management", "PS_personnel_security", "PT_pii_processing_transparency", "RA_risk_assessment", "SA_system_services_acquisition", "SC_system_communications_protection", "SI_system_information_integrity", "SR_supply_chain_risk_management" ], "value_labels": { "AC_access_control": "AC Access Control", "AT_awareness_training": "AT Awareness and Training", "AU_audit_accountability": "AU Audit and Accountability", "CA_assessment_authorisation_monitoring": "CA Assessment, Authorization, and Monitoring", "CM_configuration_management": "CM Configuration Management", "CP_contingency_planning": "CP Contingency Planning", "IA_identification_authentication": "IA Identification and Authentication", "IR_incident_response": "IR Incident Response", "MA_maintenance": "MA Maintenance", "MP_media_protection": "MP Media Protection", "PE_physical_environmental_protection": "PE Physical and Environmental Protection", "PL_planning": "PL Planning", "PM_program_management": "PM Program Management", "PS_personnel_security": "PS Personnel Security", "PT_pii_processing_transparency": "PT PII Processing and Transparency", "RA_risk_assessment": "RA Risk Assessment", "SA_system_services_acquisition": "SA System and Services Acquisition", "SC_system_communications_protection": "SC System and Communications Protection", "SI_system_information_integrity": "SI System and Information Integrity", "SR_supply_chain_risk_management": "SR Supply Chain Risk Management" }, "use_case": "AI continuous monitoring agent generates automated evidence for each NIST SP 800-53 control it can assess. Evidence records are tagged with control family and specific control ID (e.g. AC-2, AU-6) for ingestion into eMASS or equivalent agency GRC platform.", "source": "NIST SP 800-53 Rev 5, Security and Privacy Controls for Information Systems and Organisations (all 20 control families)", "source_url": "https://csrc.nist.gov/publications/detail/sp/800-53/rev-5/final", "notes": "Rev 5 added PT (PII Processing and Transparency) as the 20th control family. Prior versions had 18 families. AI compliance agents must use Rev 5 family codes, Rev 4 codes (e.g. AR for Accountability, IP for Individual Participation) are no longer current." }, { "enum_name": "ControlAssessmentStatus", "label": "Control Assessment Status", "otel_attribute": "government.nist_sp800_53.control_assessment_status", "opa_policy_path": "data.government.nist_sp800_53.control_assessment_status", "rego_input_key": "government_nist_sp800_53_control_assessment_status", "stability": "stable", "description": "NIST SP 800-53A Rev 5 control assessment outcome status. AI compliance agents report the assessment result for each tested control in the Security Assessment Report (SAR) and continuous monitoring programme.", "permitted_values": [ "satisfied", "other_than_satisfied", "not_applicable", "not_assessed", "assessment_in_progress", "inherited_from_common_control_provider" ], "value_labels": { "satisfied": "Satisfied", "other_than_satisfied": "Other Than Satisfied", "not_applicable": "Not Applicable", "not_assessed": "Not Assessed", "assessment_in_progress": "Assessment in Progress", "inherited_from_common_control_provider": "Inherited From Common Control Provider" }, "code_definitions": { "satisfied": "Control is fully implemented and operating as intended; all assessment objectives met; no weaknesses identified", "other_than_satisfied": "One or more assessment objectives not met; weakness documented in POA&M; risk accepted by Authorising Official or remediation in progress", "not_applicable": "Control does not apply to this system based on its characteristics, operating environment, or applicable tailoring guidance", "inherited_from_common_control_provider": "Control is fully or partially provided by a common control (e.g. FedRAMP-authorised CSP, agency-level common control); responsibility documented in SSP" }, "regulatory_mappings": { "nist_sp_800_53a": "NIST SP 800-53A Rev 5, Assessment procedures produce satisfied/other-than-satisfied determinations for each control objective", "fedramp": "FedRAMP 3PAO assessment: 'other_than_satisfied' findings must appear in SAR and POA&M; High findings may result in DATO" }, "source": "NIST SP 800-53A Rev 5, Assessing Security and Privacy Controls", "source_url": "https://csrc.nist.gov/publications/detail/sp/800-53a/rev-5/final" }, { "enum_name": "ContinuousMonitoringFrequency", "label": "Continuous Monitoring Frequency", "otel_attribute": "government.continuous_monitoring.frequency", "opa_policy_path": "data.government.continuous_monitoring.frequency", "rego_input_key": "government_continuous_monitoring_frequency", "stability": "stable", "description": "NIST SP 800-137A / FedRAMP continuous monitoring assessment frequency classification. AI compliance agents schedule automated control assessments according to these frequencies as required by FedRAMP ConMon obligations.", "permitted_values": [ "continuously", "daily", "weekly", "monthly", "quarterly", "semi_annually", "annually", "on_demand", "event_driven" ], "value_labels": { "continuously": "Continuously", "daily": "Daily", "weekly": "Weekly", "monthly": "Monthly", "quarterly": "Quarterly", "semi_annually": "Semi Annually", "annually": "Annually", "on_demand": "On Demand", "event_driven": "Event Driven" }, "use_case": "FedRAMP ConMon requires monthly vulnerability scanning, annual penetration testing, and continuous log monitoring. AI compliance agents schedule and execute control assessments at the required frequency and generate evidence with timestamp and frequency classification for the FedRAMP PMO.", "source": "NIST SP 800-137A; FedRAMP Continuous Monitoring Strategy Guide", "source_url": "https://www.fedramp.gov/documents-templates/" } ] }, { "subdomain": "AI Accountability & Agency Use Cases", "description": "Describe the agency workflow, record its assessment, and track required reviews. These fields support agency policy; they are not an official government taxonomy.", "relevant_standards": [ "OMB M-25-21, Accelerating Federal Use of AI through Innovation, Governance, and Public Trust (April 2025)", "EU AI Act (2024/1689) Annex III paras 5, 6, 7, High-risk AI in public services, law enforcement, migration", "NIST AI RMF 1.0, AI Risk Management Framework (2023)", "NIST AI 600-1, Generative AI Profile (2024)", "Blueprint for an AI Bill of Rights (OSTP, October 2022)" ], "categories": [ { "enum_name": "AIAccountabilityUseCase", "label": "AI Accountability Use Case", "otel_attribute": "government.ai_accountability.use_case", "opa_policy_path": "data.government.ai_accountability.use_case", "rego_input_key": "government_ai_accountability_use_case", "stability": "stable", "description": "The purpose of the agency's AI workflow. Select a value that describes its use, then record the agency's separate high-impact determination. M-25-21 considers the role of the output in the decision, not the workflow name alone.", "permitted_values": [ "benefits_eligibility_determination", "law_enforcement_predictive_policing", "law_enforcement_facial_recognition", "child_welfare_risk_scoring", "hiring_and_employment_screening", "parole_sentencing_risk_scoring", "immigration_adjudication", "immigration_border_risk_screening", "credit_and_housing_determination", "healthcare_diagnosis_or_treatment", "educational_outcome_assessment", "tax_fraud_detection", "public_procurement_evaluation", "national_security_threat_assessment", "emergency_resource_allocation", "regulatory_enforcement_targeting", "administrative_process_automation", "citizen_service_chatbot_non_binding" ], "value_labels": { "benefits_eligibility_determination": "Benefits Eligibility Determination", "law_enforcement_predictive_policing": "Law Enforcement Predictive Policing", "law_enforcement_facial_recognition": "Law Enforcement Facial Recognition", "child_welfare_risk_scoring": "Child Welfare Risk Scoring", "hiring_and_employment_screening": "Hiring and Employment Screening", "parole_sentencing_risk_scoring": "Parole Sentencing Risk Scoring", "immigration_adjudication": "Immigration Adjudication", "immigration_border_risk_screening": "Immigration Border Risk Screening", "credit_and_housing_determination": "Credit and Housing Determination", "healthcare_diagnosis_or_treatment": "Healthcare Diagnosis or Treatment", "educational_outcome_assessment": "Educational Outcome Assessment", "tax_fraud_detection": "Tax Fraud Detection", "public_procurement_evaluation": "Public Procurement Evaluation", "national_security_threat_assessment": "National Security Threat Assessment", "emergency_resource_allocation": "Emergency Resource Allocation", "regulatory_enforcement_targeting": "Regulatory Enforcement Targeting", "administrative_process_automation": "Administrative Process Automation", "citizen_service_chatbot_non_binding": "Citizen Service Chatbot Non Binding" }, "code_definitions": { "benefits_eligibility_determination": "AI used to assess eligibility for government benefits, such as Medicaid, SNAP, unemployment insurance, or veterans benefits.", "law_enforcement_facial_recognition": "AI using facial recognition or biometric identification in law enforcement contexts. EU AI Act Article 5 prohibits real-time remote biometric identification in public spaces except in narrow exceptions.", "parole_sentencing_risk_scoring": "AI producing risk scores for parole, bail, or sentencing decisions.", "citizen_service_chatbot_non_binding": "AI providing information or routing assistance without deciding access to services. Assess the actual workflow before assigning its risk level." }, "regulatory_mappings": { "omb_m_25_21": "OMB M-25-21 Sections 4-6: agency high-impact determinations, minimum risk management practices, and presumed high-impact uses. Applicability depends on the specific use and memorandum scope.", "eu_ai_act_annex3": "EU AI Act Annex III paras 5, 6, 7, Explicit high-risk classifications for government AI use cases", "eu_ai_act_art5": "EU AI Act Article 5, Prohibited AI practices: real-time remote biometric identification, social scoring, exploitation of vulnerabilities", "blueprint_ai_bill_rights": "OSTP Blueprint for an AI Bill of Rights, Safe and effective systems, algorithmic discrimination protections, data privacy, notice and explanation, human alternatives" }, "use_case": "A benefits workflow checks its recorded assessment and required review before a decision proceeds. The agency's published policy defines which evidence permits the action.", "source": "OMB M-25-21 Sections 4-6; use-case values are VeriProof vocabulary, not an official classification list", "source_url": "https://www.whitehouse.gov/wp-content/uploads/2025/02/M-25-21-Accelerating-Federal-Use-of-AI-through-Innovation-Governance-and-Public-Trust.pdf" }, { "enum_name": "AIMinimumRiskPracticeStatus", "label": "AI Minimum Risk Practice Status", "otel_attribute": "government.ai_accountability.min_risk_practice_status", "opa_policy_path": "data.government.ai_accountability.min_risk_practice_status", "rego_input_key": "government_ai_accountability_min_risk_practice_status", "stability": "stable", "description": "Progress on a required risk management practice for an agency AI use case. Record completion evidence or the applicable waiver separately from this status.", "permitted_values": [ "not_started", "in_progress", "completed", "completed_with_exceptions", "waiver_requested", "waiver_granted", "not_applicable", "overdue_paused" ], "value_labels": { "not_started": "Not Started", "in_progress": "In Progress", "completed": "Completed", "completed_with_exceptions": "Completed with Exceptions", "waiver_requested": "Waiver Requested", "waiver_granted": "Waiver Granted", "not_applicable": "Not Applicable", "overdue_paused": "Overdue Paused" }, "code_definitions": { "completed": "Minimum risk practice fully completed and documented; evidence available for OMB review", "overdue_paused": "A required practice is overdue and the affected AI use has been paused.", "waiver_granted": "The agency CAIO has authorized a waiver for a specific practice. Retain its scope, justification, and current certification with the assessment." }, "regulatory_mappings": { "omb_m_25_21_section4": "OMB M-25-21 Section 4 covers minimum risk management practices for high-impact AI, qualifying pilots, and CAIO-authorized waivers. Assess the applicable requirements for the specific use." }, "use_case": "An agency rule stops a connected action when a required practice remains incomplete and no applicable authorization permits it. Reviewers can inspect the supporting assessment.", "source": "OMB M-25-21 Section 4, minimum risk management practices for high-impact AI", "source_url": "https://www.whitehouse.gov/wp-content/uploads/2025/02/M-25-21-Accelerating-Federal-Use-of-AI-through-Innovation-Governance-and-Public-Trust.pdf" }, { "enum_name": "AIUseCaseInventoryStage", "label": "AI Use Case Inventory Stage", "otel_attribute": "government.ai_accountability.inventory_stage", "opa_policy_path": "data.government.ai_accountability.inventory_stage", "rego_input_key": "government_ai_accountability_inventory_stage", "stability": "stable", "description": "Progress through the agency's AI use case inventory. Record the current assessment and reporting status; inventory entry alone does not authorize an action.", "permitted_values": [ "identified_not_yet_assessed", "under_assessment", "inventoried_not_high_impact", "inventoried_high_impact", "inventoried_national_security_excepted", "decommissioned", "not_covered_narrow_exception" ], "value_labels": { "identified_not_yet_assessed": "Identified; assessment pending", "under_assessment": "Under assessment", "inventoried_not_high_impact": "Inventoried: not high-impact", "inventoried_high_impact": "Inventoried: high-impact", "inventoried_national_security_excepted": "National security exception recorded", "decommissioned": "Decommissioned", "not_covered_narrow_exception": "Outside scope: exception recorded" }, "regulatory_mappings": { "omb_m_25_21_section3": "M-25-21 Section 3(b)(v) requires covered agencies to update inventories at least annually, submit them to OMB, and publish a public version. Defense and Intelligence Community exceptions apply." }, "source": "OMB M-25-21 Section 3(b)(v); catalog status values are not official OMB inventory classifications", "source_url": "https://www.whitehouse.gov/wp-content/uploads/2025/02/M-25-21-Accelerating-Federal-Use-of-AI-through-Innovation-Governance-and-Public-Trust.pdf" } ] }, { "subdomain": "Law Enforcement & Criminal Justice AI", "description": "Identify the tool used in a law enforcement, criminal justice, or corrections workflow. Link its recorded use to the agency's impact assessment and review process.", "relevant_standards": [ "EU AI Act (2024/1689) Annex III para 6, High-risk AI in law enforcement", "EU AI Act Article 5, Prohibited AI: real-time remote biometric ID, social scoring", "OMB M-25-21, Minimum risk-management practices for covered high-impact agency AI", "DOJ AI Use Policy (2024)", "FBI CJIS Security Policy, Criminal Justice Information security requirements", "Algorithmic Accountability Act (proposed), Congressional proposals for bias auditing" ], "categories": [ { "enum_name": "LawEnforcementAIToolType", "label": "Law Enforcement AI Tool Type", "otel_attribute": "government.law_enforcement.ai_tool_type", "opa_policy_path": "data.government.law_enforcement.ai_tool_type", "rego_input_key": "government_law_enforcement_ai_tool_type", "stability": "stable", "description": "Record the type of AI tool used in law enforcement. Its intended use helps reviewers assess bias, individual rights, and applicable requirements.", "permitted_values": [ "facial_recognition_identification", "predictive_policing_hotspot", "recidivism_risk_scoring", "bail_risk_assessment", "gang_membership_identification", "social_media_monitoring", "license_plate_reader_analytics", "gunshot_detection_ai", "body_camera_analytics", "forensic_dna_probabilistic_genotyping", "document_fraud_detection", "crime_pattern_analysis", "investigative_lead_generation" ], "value_labels": { "facial_recognition_identification": "Facial Recognition Identification", "predictive_policing_hotspot": "Predictive Policing Hotspot", "recidivism_risk_scoring": "Recidivism Risk Scoring", "bail_risk_assessment": "Bail Risk Assessment", "gang_membership_identification": "Gang Membership Identification", "social_media_monitoring": "Social Media Monitoring", "license_plate_reader_analytics": "License Plate Reader Analytics", "gunshot_detection_ai": "Gunshot Detection AI", "body_camera_analytics": "Body Camera Analytics", "forensic_dna_probabilistic_genotyping": "Forensic Dna Probabilistic Genotyping", "document_fraud_detection": "Document Fraud Detection", "crime_pattern_analysis": "Crime Pattern Analysis", "investigative_lead_generation": "Investigative Lead Generation" }, "regulatory_mappings": { "eu_ai_act_annex3_6": "Annex III point 6 lists specific law-enforcement uses. Match the intended use to that list and Article 6; a tool label alone does not establish high-risk status.", "eu_ai_act_art5_1d": "Article 5(1)(d) prohibits individual criminal-offence risk predictions based solely on profiling or personality traits. It distinguishes assessments supported by objective facts linked to criminal activity.", "eu_ai_act_art5_1h": "Article 5(1)(h) restricts real-time remote biometric identification in publicly accessible spaces for law enforcement. Exceptions require the specified purposes, safeguards and authorization conditions.", "omb_m_25_21": "OMB M-25-21 Sections 4-6: assess the specific use against the high-impact definition and presumptions; tool type alone does not settle the classification.", "cjis_security_policy": "The FBI CJIS Security Policy provides security requirements for Criminal Justice Information. Record the policy version applicable to the agency's system." }, "use_case": "An agency records each tool's intended use. Its own rule can stop deployment until the required assessment and human-review arrangements are recorded.", "source": "EU AI Act Articles 5 and 6, Annex III point 6; OMB M-25-21 Sections 4-6; agency-defined tool vocabulary", "source_url": "https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32024R1689" }, { "enum_name": "BiasAuditOutcome", "label": "Bias Audit Outcome", "otel_attribute": "government.ai_accountability.bias_audit_outcome", "opa_policy_path": "data.government.ai_accountability.bias_audit_outcome", "rego_input_key": "government_ai_accountability_bias_audit_outcome", "stability": "proposed", "description": "Recorded outcome of a bias audit. Keep its method, assessed population, and acceptance criteria with the result so reviewers can interpret the finding.", "permitted_values": [ "no_disparate_impact_identified", "disparate_impact_identified_within_threshold", "disparate_impact_identified_exceeds_threshold", "disparate_impact_identified_remediation_complete", "audit_in_progress", "audit_not_yet_conducted", "audit_methodology_under_review" ], "value_labels": { "no_disparate_impact_identified": "No Disparate Impact Identified", "disparate_impact_identified_within_threshold": "Disparate Impact Identified Within Threshold", "disparate_impact_identified_exceeds_threshold": "Disparate Impact Identified Exceeds Threshold", "disparate_impact_identified_remediation_complete": "Disparate Impact Identified Remediation Complete", "audit_in_progress": "Audit in Progress", "audit_not_yet_conducted": "Audit not Yet Conducted", "audit_methodology_under_review": "Audit Methodology Under Review" }, "regulatory_mappings": { "omb_m_25_21": "M-25-21 provides independent-review and risk-management context for covered high-impact AI. This audit outcome records an agency assessment, not a legal determination." }, "use_case": "An agency rule stops deployment while its required audit is pending or a finding exceeds its acceptance threshold. A reviewer examines the assessment before release.", "source": "Agency-defined audit outcome vocabulary; OMB M-25-21 Sections 3 and 4 provide governance context", "source_url": "https://www.whitehouse.gov/wp-content/uploads/2025/02/M-25-21-Accelerating-Federal-Use-of-AI-through-Innovation-Governance-and-Public-Trust.pdf" } ] }, { "subdomain": "Benefits Administration & Public Services", "description": "Follow an AI-assisted benefits recommendation through eligibility review, notices, and appeals. Service-channel fields show how the person interacted with the agency.", "relevant_standards": [ "OMB M-25-21, Minimum risk-management practices for covered high-impact agency AI", "Social Security Act, Benefits eligibility statutory requirements", "EU AI Act Annex III para 5(a), AI in public benefits access decisions is high-risk", "EU GDPR Article 22, Automated individual decision-making", "5 U.S.C. 555(e) and 706, Agency denial notices and judicial review", "Section 508, Accessibility for citizen-facing digital services" ], "categories": [ { "enum_name": "BenefitsEligibilityDecisionType", "label": "Benefits Eligibility Decision Type", "otel_attribute": "government.benefits.eligibility_decision_type", "opa_policy_path": "data.government.benefits.eligibility_decision_type", "rego_input_key": "government_benefits_eligibility_decision_type", "stability": "stable", "description": "Record the benefits decision type so the workflow can apply the program's review, notice, and appeal rules.", "permitted_values": [ "initial_eligibility_approved", "initial_eligibility_denied", "recertification_approved", "recertification_denied", "benefit_amount_determination", "benefit_suspension", "benefit_termination", "overpayment_determination", "fraud_referral", "appeal_upheld", "appeal_overturned", "administrative_review_required" ], "value_labels": { "initial_eligibility_approved": "Initial Eligibility Approved", "initial_eligibility_denied": "Initial Eligibility Denied", "recertification_approved": "Recertification Approved", "recertification_denied": "Recertification Denied", "benefit_amount_determination": "Benefit Amount Determination", "benefit_suspension": "Benefit Suspension", "benefit_termination": "Benefit Termination", "overpayment_determination": "Overpayment Determination", "fraud_referral": "Fraud Referral", "appeal_upheld": "Appeal Upheld", "appeal_overturned": "Appeal Overturned", "administrative_review_required": "Administrative Review Required" }, "regulatory_mappings": { "eu_ai_act_annex3_5a": "Annex III point 5(a) covers specified essential public-assistance benefits and services decisions. Apply Article 6 to the system's intended use.", "eu_gdpr_art22": "Article 22 addresses solely automated decisions with legal or similarly significant effects on individuals. Its exceptions and safeguards depend on the legal basis for the decision.", "apa_due_process": "5 U.S.C. 555(e) addresses notice and grounds for covered denials, with stated exceptions. Section 706 governs judicial review; benefits-program rules determine additional notices and appeal procedures.", "omb_m_25_21": "OMB M-25-21 Section 4(b)(vi) addresses timely human review and appeals of negative impacts, when appropriate, for covered high-impact AI." }, "use_case": "An agency rule pauses a proposed denial, termination, or fraud referral for caseworker review. The connected workflow waits for that review before notifying the claimant.", "source": "Agency-defined decision vocabulary; OMB M-25-21 Section 4(b)(vi); EU AI Act Annex III para 5(a); applicable benefits-program rules", "source_url": "https://www.ssa.gov/policy/docs/ssb/v77n4/v77n4p1.html" }, { "enum_name": "CitizenServiceChannelType", "label": "Citizen Service Channel Type", "otel_attribute": "government.citizen_service.channel_type", "opa_policy_path": "data.government.citizen_service.channel_type", "rego_input_key": "government_citizen_service_channel_type", "stability": "proposed", "description": "Record how a person accesses an AI-assisted public service, from a web chat to an in-person office. Use the channel to route assistance.", "permitted_values": [ "ai_chatbot_web", "ai_chatbot_mobile", "ai_voice_ivr", "ai_assisted_human_agent", "human_agent_only", "in_person_office", "mail_paper", "third_party_navigator" ], "value_labels": { "ai_chatbot_web": "AI Chatbot Web", "ai_chatbot_mobile": "AI Chatbot Mobile", "ai_voice_ivr": "AI Voice Ivr", "ai_assisted_human_agent": "AI Assisted Human Agent", "human_agent_only": "Human Agent Only", "in_person_office": "In Person Office", "mail_paper": "Mail Paper", "third_party_navigator": "Third Party Navigator" }, "regulatory_mappings": { "omb_m_23_22": "OMB M-23-22 provides digital-service delivery context for the channel record.", "omb_m_25_21": "OMB M-25-21 Section 4(b)(v)-(vi) addresses human oversight and appropriate review or appeals for covered high-impact uses, rather than prescribing every service channel.", "section_508": "Section 508, All AI-delivered citizen service channels must be accessible to individuals with disabilities" }, "use_case": "An agency rule requires a human assistance option for selected benefits or immigration workflows. The policy checks the reported channel and escalation option before proceeding.", "source": "Agency-defined service-channel vocabulary; OMB M-23-22; OMB M-25-21; Section 508 accessibility requirements", "source_url": "https://www.whitehouse.gov/wp-content/uploads/2023/09/M-23-22-Delivering-a-Digital-First-Public-Experience.pdf" } ] }, { "subdomain": "Immigration & Border Management AI", "description": "Record how AI supports immigration, asylum, and border decisions. These fields help connect each recommendation to the agency's review requirements.", "relevant_standards": [ "EU AI Act (2024/1689) Annex III para 7, High-risk AI in migration, asylum, and border control", "EU AI Act Article 5(1)(h), Restrictions on real-time remote biometric identification for law enforcement", "DHS AI Strategy (2023), Department of Homeland Security AI governance", "CBP AI Use Policy, Customs and Border Protection", "USCIS AI Use Cases, US Citizenship and Immigration Services" ], "categories": [ { "enum_name": "ImmigrationAdjudicationAIUseType", "label": "Immigration Adjudication AI Use Type", "otel_attribute": "government.immigration.ai_use_type", "opa_policy_path": "data.government.immigration.ai_use_type", "rego_input_key": "government_immigration_ai_use_type", "stability": "stable", "description": "Record the task AI supports in an immigration or border process. Assess its intended use against the applicable rules, including Annex III point 7 for EU deployments.", "permitted_values": [ "visa_application_risk_screening", "asylum_claim_credibility_assessment", "document_authenticity_verification", "biometric_identity_matching", "travel_document_fraud_detection", "border_crossing_anomaly_detection", "refugee_status_determination_support", "immigration_enforcement_targeting", "detention_risk_assessment", "deportation_order_generation" ], "value_labels": { "visa_application_risk_screening": "Visa Application Risk Screening", "asylum_claim_credibility_assessment": "Asylum Claim Credibility Assessment", "document_authenticity_verification": "Document Authenticity Verification", "biometric_identity_matching": "Biometric Identity Matching", "travel_document_fraud_detection": "Travel Document Fraud Detection", "border_crossing_anomaly_detection": "Border Crossing Anomaly Detection", "refugee_status_determination_support": "Refugee Status Determination Support", "immigration_enforcement_targeting": "Immigration Enforcement Targeting", "detention_risk_assessment": "Detention Risk Assessment", "deportation_order_generation": "Deportation Order Generation" }, "regulatory_mappings": { "eu_ai_act_annex3_7": "Annex III point 7 covers specified migration, asylum and border uses. Point 7(d) excludes travel-document verification; apply Article 6 to the intended use.", "eu_ai_act_art14": "Article 14 requires effective human oversight of high-risk AI, proportionate to its risks and context. Assigned reviewers must be able to interpret and override outputs." }, "use_case": "An agency rule keeps asylum, detention, and removal recommendations advisory until an authorized officer records a decision. The case retains both the recommendation and review.", "source": "Agency-defined task vocabulary and review example; EU AI Act Articles 6 and 14, Annex III point 7", "source_url": "https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32024R1689" } ] }, { "subdomain": "Federal Procurement & Acquisition AI", "description": "Record how an agency acquires AI and which review path applies. Keep the acquisition vehicle separate from the system's assessed risk.", "relevant_standards": [ "FAR Part 12, Acquisition of Commercial Items", "FAR Part 39, Acquisition of Information Technology", "DFARS 252.204-7012, Safeguarding Covered Defense Information", "DFARS 252.204-7024, Notice on the Use of the Supplier Performance Risk System", "OMB M-25-22, Driving Efficient Acquisition of Artificial Intelligence in Government", "GSA Multiple Award Schedule, Information Technology category" ], "categories": [ { "enum_name": "FederalAIAcquisitionVehicleType", "label": "Federal AI Acquisition Vehicle Type", "otel_attribute": "government.procurement.ai_acquisition_vehicle", "opa_policy_path": "data.government.procurement.ai_acquisition_vehicle", "rego_input_key": "government_procurement_ai_acquisition_vehicle", "stability": "stable", "description": "Contract vehicle or procurement mechanism used to acquire AI. Record the applicable requirements separately; the vehicle alone does not determine them.", "permitted_values": [ "gsa_mas_schedule_it_category", "gsa_gwac_alliant_3", "gsa_gwac_8a_stars_iii", "doi_ecs_iii", "nasa_sewp_vi", "dod_otagreement", "dod_idiq_contract", "agency_direct_award_sar", "sbir_sttr_award", "cooperative_research_crada", "open_source_no_contract" ], "value_labels": { "gsa_mas_schedule_it_category": "GSA Multiple Award Schedule: IT", "gsa_gwac_alliant_3": "GSA Alliant 3", "gsa_gwac_8a_stars_iii": "GSA 8(a) STARS III", "doi_ecs_iii": "DOI ECS III", "nasa_sewp_vi": "NASA SEWP VI", "dod_otagreement": "DoD other transaction agreement", "dod_idiq_contract": "DoD indefinite-delivery contract", "agency_direct_award_sar": "Agency Direct Award SAR", "sbir_sttr_award": "SBIR/STTR award", "cooperative_research_crada": "Cooperative research and development agreement", "open_source_no_contract": "Open source without a contract" }, "regulatory_mappings": { "far_part_39": "FAR Part 39 provides information technology acquisition context. Assess accessibility and cloud authorization requirements for the planned acquisition.", "dfars_252_204_7012": "DFARS 252.204-7012 addresses safeguarding covered defense information and cyber incident reporting when the clause applies.", "omb_m_25_22": "OMB M-25-22: acquisition planning, performance evaluation, and contract terms for covered agency AI acquisitions. National Security Systems follow separate requirements." }, "source": "FAR/DFARS; GSA contract vehicle taxonomy; OMB M-25-22", "source_url": "https://www.acquisition.gov/" }, { "enum_name": "AIContractRiskTier", "label": "AI Contract Risk Tier", "otel_attribute": "government.procurement.ai_contract_risk_tier", "opa_policy_path": "data.government.procurement.ai_contract_risk_tier", "rego_input_key": "government_procurement_ai_contract_risk_tier", "stability": "proposed", "description": "Agency-defined procurement review tier based on intended use, data sensitivity, and potential impact. These four catalog tiers are not an OMB classification.", "permitted_values": [ "tier_1_low_risk", "tier_2_moderate_risk", "tier_3_high_risk_rights_impacting", "tier_4_critical_national_security" ], "value_labels": { "tier_1_low_risk": "Tier 1, Low Risk", "tier_2_moderate_risk": "Tier 2, Moderate Risk", "tier_3_high_risk_rights_impacting": "Tier 3, High Risk Rights Impacting", "tier_4_critical_national_security": "Tier 4, Critical National Security" }, "code_definitions": { "tier_1_low_risk": "Internal productivity or administrative use with limited expected impact. Apply the agency's baseline procurement review.", "tier_2_moderate_risk": "Use involving federal data or agency processes that needs additional review. Assess information security requirements separately.", "tier_3_high_risk_rights_impacting": "Use with potentially significant effects on people or public services. Record the agency's impact assessment and required controls.", "tier_4_critical_national_security": "Use requiring specialist national security or critical infrastructure review. Apply the requirements for the specific system and mission." }, "ordered": true, "value_ordinals": { "tier_1_low_risk": 1, "tier_2_moderate_risk": 2, "tier_3_high_risk_rights_impacting": 3, "tier_4_critical_national_security": 4 }, "regulatory_mappings": { "omb_m_25_22": "OMB M-25-22 provides acquisition guidance for covered AI, including performance and risk management. An agency selects its review tier separately." }, "source": "Agency-defined review taxonomy; OMB M-25-22 for covered federal AI acquisitions", "source_url": "https://www.whitehouse.gov/wp-content/uploads/2025/02/M-25-22-Driving-Efficient-Acquisition-of-Artificial-Intelligence-in-Government.pdf" } ] }, { "subdomain": "FOIA, Records Management & Open Government", "description": "Covers AI-assisted Freedom of Information Act (FOIA) processing, federal records management, and open data governance enumerations.", "relevant_standards": [ "Freedom of Information Act (5 USC § 552), FOIA request processing requirements", "Presidential Records Act / Federal Records Act, Records retention and management", "OMB M-23-07, Update to Transition to Electronic Records", "NARA Bulletin 2023-01, Guidance on Managing Electronic Records", "DATA Act (2014), Federal spending data transparency", "Open, Public, Electronic and Necessary Government Data Act (OPEN Government Data Act 2018)" ], "categories": [ { "enum_name": "FOIARequestProcessingStatus", "label": "FOIA Request Processing Status", "otel_attribute": "government.foia.processing_status", "opa_policy_path": "data.government.foia.processing_status", "rego_input_key": "government_foia_processing_status", "stability": "stable", "description": "Status of a FOIA request as it is processed by an AI-assisted FOIA workflow. AI FOIA agents may triage, search, and recommend redactions but a human FOIA officer must make final disclosure and exemption determinations.", "permitted_values": [ "received", "acknowledged", "perfected", "search_in_progress", "ai_review_in_progress", "human_review_required", "redaction_in_progress", "response_draft_ready", "released_full", "released_partial", "denied_in_full", "referred_to_agency", "closed_no_records", "appealed_by_requester", "litigation_hold" ], "value_labels": { "received": "Received", "acknowledged": "Acknowledged", "perfected": "Perfected", "search_in_progress": "Search in Progress", "ai_review_in_progress": "AI Review in Progress", "human_review_required": "Human Review Required", "redaction_in_progress": "Redaction in Progress", "response_draft_ready": "Response Draft Ready", "released_full": "Released Full", "released_partial": "Released Partial", "denied_in_full": "Denied in Full", "referred_to_agency": "Referred to Agency", "closed_no_records": "Closed No Records", "appealed_by_requester": "Appealed by Requester", "litigation_hold": "Litigation Hold" }, "regulatory_mappings": { "foia_5_usc_552": "FOIA 5 USC § 552(a)(6), 20 working day response deadline; complex requests may qualify for extension", "doj_foia_guidance": "DOJ FOIA guidelines, AI-assisted redaction tools must be reviewed by a human FOIA officer before response is issued; AI cannot autonomously determine FOIA exemption applicability" }, "use_case": "AI FOIA triage agent classifies requests, conducts keyword search, and marks sensitive passages for redaction review. OPA policy enforces that 'denied_in_full' and 'released_partial' determinations always require human FOIA officer sign-off before communication to the requester.", "source": "FOIA 5 USC § 552; DOJ FOIA processing guidance; agency FOIA regulations", "source_url": "https://www.justice.gov/oip/freedom-information-act-5-usc-552" }, { "enum_name": "FOIAExemptionCategory", "label": "FOIA Exemption Category", "otel_attribute": "government.foia.exemption_category", "opa_policy_path": "data.government.foia.exemption_category", "rego_input_key": "government_foia_exemption_category", "stability": "stable", "description": "FOIA exemption category under 5 USC § 552(b). AI FOIA review agents may flag candidate exemptions but a human officer must confirm each exemption before withholding records. Each exemption requires specific legal justification.", "permitted_values": [ "exemption_1_classified_national_security", "exemption_2_internal_personnel_rules", "exemption_3_statute_prohibited", "exemption_4_trade_secrets", "exemption_5_deliberative_process_privilege", "exemption_5_attorney_client_privilege", "exemption_5_work_product", "exemption_6_personal_privacy", "exemption_7a_law_enforcement_interference", "exemption_7b_fair_trial_rights", "exemption_7c_unwarranted_privacy", "exemption_7d_confidential_source", "exemption_7e_law_enforcement_techniques", "exemption_7f_endangerment", "exemption_8_financial_institutions", "exemption_9_geological_data" ], "value_labels": { "exemption_1_classified_national_security": "Exemption 1 Classified National Security", "exemption_2_internal_personnel_rules": "Exemption 2 Internal Personnel Rules", "exemption_3_statute_prohibited": "Exemption 3 Statute Prohibited", "exemption_4_trade_secrets": "Exemption 4 Trade Secrets", "exemption_5_deliberative_process_privilege": "Exemption 5 Deliberative Process Privilege", "exemption_5_attorney_client_privilege": "Exemption 5 Attorney Client Privilege", "exemption_5_work_product": "Exemption 5 Work Product", "exemption_6_personal_privacy": "Exemption 6 Personal Privacy", "exemption_7a_law_enforcement_interference": "Exemption 7a Law Enforcement Interference", "exemption_7b_fair_trial_rights": "Exemption 7b Fair Trial Rights", "exemption_7c_unwarranted_privacy": "Exemption 7c Unwarranted Privacy", "exemption_7d_confidential_source": "Exemption 7d Confidential Source", "exemption_7e_law_enforcement_techniques": "Exemption 7e Law Enforcement Techniques", "exemption_7f_endangerment": "Exemption 7f Endangerment", "exemption_8_financial_institutions": "Exemption 8 Financial Institutions", "exemption_9_geological_data": "Exemption 9 Geological Data" }, "use_case": "AI FOIA review agent scans responsive documents and recommends applicable exemptions for human FOIA officer review. 'Exemption_1_classified_national_security' recommendations trigger mandatory ISCAP referral if the classification is disputed.", "source": "FOIA 5 USC § 552(b), Nine exemption categories (Exemption 7 has six sub-categories)", "source_url": "https://www.justice.gov/oip/freedom-information-act-5-usc-552" } ] }, { "subdomain": "Cybersecurity & Zero Trust (Federal)", "description": "Covers OMB M-22-09 Zero Trust, CISA CDM, and EO 14028 cybersecurity enumerations for AI agents deployed in federal cybersecurity monitoring, threat detection, and incident response.", "relevant_standards": [ "OMB M-22-09, Moving the US Government Toward Zero Trust Cybersecurity Principles", "CISA Zero Trust Maturity Model v2.0 (2023)", "EO 14028, Improving the Nation's Cybersecurity (2021)", "CISA CDM, Continuous Diagnostics and Mitigation programme", "OMB M-21-31, Log retention requirements for federal agencies", "NIST SP 800-207, Zero Trust Architecture" ], "categories": [ { "enum_name": "ZeroTrustMaturityLevel", "label": "Zero Trust Maturity Level", "otel_attribute": "government.zero_trust.maturity_level", "opa_policy_path": "data.government.zero_trust.maturity_level", "rego_input_key": "government_zero_trust_maturity_level", "stability": "stable", "description": "CISA Zero Trust Maturity Model v2.0 maturity level for a federal agency or system pillar (Identity, Devices, Networks, Applications, Data). AI security agents report on ZT maturity to drive CDM dashboard updates.", "permitted_values": [ "traditional", "initial", "advanced", "optimal" ], "value_labels": { "traditional": "Traditional", "initial": "Initial", "advanced": "Advanced", "optimal": "Optimal" }, "code_definitions": { "traditional": "Legacy perimeter-based security; limited integration of ZT principles; pre-EO 14028 posture", "initial": "Some ZT capabilities deployed; automated attribute assignment begun; inventory partly complete; gaps remain", "advanced": "Cross-pillar integration; automation of identity and device validation; enterprise-wide visibility approaching complete", "optimal": "Fully automated ZT operations; AI-driven continuous validation; dynamic policy enforcement across all pillars; CDM data feeds complete and current" }, "ordered": true, "value_ordinals": { "traditional": 1, "initial": 2, "advanced": 3, "optimal": 4 }, "regulatory_mappings": { "omb_m_22_09": "OMB M-22-09, Agencies must achieve specific ZT milestones by end of FY2024; annual reporting to OMB/CISA required", "eo_14028": "EO 14028 Section 3, Federal agencies required to advance toward ZT architecture; CISA ZTM is the reference framework" }, "source": "CISA Zero Trust Maturity Model v2.0 (2023), Maturity stages", "source_url": "https://www.cisa.gov/zero-trust-maturity-model" }, { "enum_name": "FederalIncidentSeverityCategory", "label": "Federal Incident Severity Category", "otel_attribute": "government.cybersecurity.incident_severity_category", "opa_policy_path": "data.government.cybersecurity.incident_severity_category", "rego_input_key": "government_cybersecurity_incident_severity_category", "stability": "stable", "description": "US-CERT / CISA federal incident severity schema. AI cybersecurity agents must classify all detected incidents using this schema for FISMA reporting, US-CERT notification, and OMB M-21-31 log retention determination.", "permitted_values": [ "category_0_exercise", "category_1_unauthorized_access", "category_2_denial_of_service", "category_3_malicious_code", "category_4_improper_usage", "category_5_scans_probes", "category_6_investigation" ], "value_labels": { "category_0_exercise": "Category 0 Exercise", "category_1_unauthorized_access": "Category 1 Unauthorized Access", "category_2_denial_of_service": "Category 2 Denial of Service", "category_3_malicious_code": "Category 3 Malicious Code", "category_4_improper_usage": "Category 4 Improper Usage", "category_5_scans_probes": "Category 5 Scans Probes", "category_6_investigation": "Category 6 Investigation" }, "regulatory_mappings": { "fisma": "FISMA, All Category 1–3 incidents must be reported to US-CERT within 1 hour of discovery", "omb_m_21_31": "OMB M-21-31, Log retention: Category 1 and 2 incidents require EL3 logging (12-month retention plus 18-month cold storage)", "eo_14028_sec6": "EO 14028 Section 6, Federal agencies must share cyber incident information with CISA; AI threat detection agents are key data sources" }, "source": "CISA / US-CERT Federal Incident Notification Guidelines, Incident Category Descriptions", "source_url": "https://www.cisa.gov/federal-incident-notification-guidelines" } ] } ], "opa_rego_policy_patterns": { "description": "Government & Public Sector-specific OPA Rego policy patterns referencing enum values from this file and from 00_core_sdk_and_governance.json. Illustrative patterns, not production policies.", "patterns": [ { "pattern_id": "government.block_action_without_required_risk_review", "pattern_name": "block_action_without_required_risk_review", "display_name": "Complete the required risk review before action", "enforcement_effect": "deny", "description": "Hold the connected action until the agency's required risk review is complete. Check the assessed use, required practices, and applicable authorization together.", "applicable_enums": [ "AIAccountabilityUseCase", "AIMinimumRiskPracticeStatus", "AIUseCaseInventoryStage" ], "regulatory_basis": "Agency-defined control informed by OMB M-25-21 Section 4, applied to the assessed AI use and its authorization." }, { "pattern_id": "government.block_autonomous_adverse_benefits_determination", "pattern_name": "block_autonomous_adverse_benefits_determination", "enforcement_effect": "deny", "description": "Require caseworker review before a connected benefits workflow issues a denial or termination. Keep the review and required notice with the decision record.", "applicable_enums": [ "BenefitsEligibilityDecisionType", "AIAccountabilityUseCase", "AIMinimumRiskPracticeStatus" ], "regulatory_basis": "Agency-defined benefits control. Set review and notice requirements from the applicable program rules." }, { "pattern_id": "government.enforce_fedramp_authorization_before_federal_data_routing", "pattern_name": "enforce_fedramp_authorization_before_federal_data_routing", "enforcement_effect": "deny", "description": "Stop a connected data transfer when its destination lacks the authorization required by agency policy. Route revoked or unresolved authorizations for review.", "applicable_enums": [ "FedRAMPAuthorizationStatus", "FISMAImpactLevel", "RMFLifecyclePhase" ], "regulatory_basis": "Agency-defined routing control informed by applicable FedRAMP scope and the agency system's authorization conditions." }, { "pattern_id": "government.block_law_enforcement_ai_without_bias_audit", "pattern_name": "block_law_enforcement_ai_without_bias_audit", "enforcement_effect": "deny", "description": "Hold deployment until the agency's required bias audit is complete. An outcome above the configured threshold also stops deployment for review.", "applicable_enums": [ "LawEnforcementAIToolType", "BiasAuditOutcome", "AIAccountabilityUseCase" ], "regulatory_basis": "Agency-defined audit control. Set audit scope, acceptance criteria, and review requirements for the intended use and applicable law." }, { "pattern_id": "government.enforce_foia_human_review_for_exemption_claims", "pattern_name": "enforce_foia_human_review_for_exemption_claims", "enforcement_effect": "require_hitl_approval", "description": "Hold a proposed FOIA denial for an authorized officer. The officer reviews each claimed exemption before the connected workflow sends the response.", "applicable_enums": [ "FOIARequestProcessingStatus", "FOIAExemptionCategory" ], "regulatory_basis": "Agency-defined review control for FOIA exemption decisions under 5 USC 552(b)." } ] }, "agent_registry_fields": { "description": "Recommended fields for registering a government or public sector agentic AI system in the GRC portal. Supplements the core agent identity schema from 00_core_sdk_and_governance.json.", "fields": [ { "field": "omb_m2410_use_case_classification", "type": "enum", "enum_ref": "AIAccountabilityUseCase", "description": "The agency AI use case recorded for this system. Keep the current high-impact determination and its supporting assessment separately.", "required_when": "When the agency's registry requires a use case classification" }, { "field": "fedramp_authorization_status", "type": "enum", "enum_ref": "FedRAMPAuthorizationStatus", "description": "Recorded authorization status of the cloud service. Keep its scope and the agency's permission to use it with the assessment.", "required_when": "All AI agents deployed in or connected to cloud services processing federal data" }, { "field": "fisma_impact_level", "type": "enum", "enum_ref": "FISMAImpactLevel", "description": "FIPS 199 security impact categorisation of the information system hosting this AI agent. Drives the NIST SP 800-53 Rev 5 control baseline and FedRAMP authorisation level required.", "required_when": "All federal AI systems and AI systems operated by federal contractors" }, { "field": "rmf_lifecycle_phase", "type": "enum", "enum_ref": "RMFLifecyclePhase", "description": "Current NIST SP 800-37 RMF activity for this system. Track the actual authorization decision separately.", "required_when": "All federal AI systems undergoing or maintaining FISMA authorisation" }, { "field": "chief_ai_officer_designated", "type": "boolean", "description": "Whether the agency has designated a Chief AI Officer. System registration is a separate record.", "required_when": "When recording agency governance ownership under M-25-21 Section 3(a)" }, { "field": "ato_expiration_date", "type": "string", "description": "Expiration date of the Authority to Operate (ATO) for this AI system. AI compliance agents monitor ATO expiration and trigger re-authorisation workflows 90 days before expiration.", "required_when": "All federal AI systems with a time-limited ATO" }, { "field": "cjis_compliance_required", "type": "boolean", "description": "True when the AI system accesses or processes Criminal Justice Information (CJI). Use this fact to apply the agency's CJIS security controls.", "required_when": "Law enforcement AI agents with access to NCIC, NICS, or other CJIS systems" }, { "field": "cui_category", "type": "string", "description": "Controlled Unclassified Information (CUI) category handled by this AI system per the CUI Registry. Drives NIST SP 800-171 Rev 3 compliance requirements for non-federal systems and DFARS obligations for defence contractors. Use values such as none, cui_basic, cui_specified, cui_law_enforcement_sensitive, cui_privacy, or cui_export_controlled.", "required_when": "AI agents processing CUI at federal or non-federal contractor facilities" } ] } }