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Government AI Governance

Government Networks Demand
Government-Grade AI Controls.

Federal employees used over 1,200 distinct AI tools in 2024 — most without ATO, FedRAMP authorization, or CUI handling agreements. Our 16,024+ classified AI-tool domains give government IT teams the enforcement layer that executive orders, FISMA, and NIST frameworks require.

16,024+AI Domains Classified
18Tool Categories
DailyFeed Updates
5+Gov Frameworks Mapped
Download Free Sample Government Pricing
Federal AI Mandates

Executive Orders, OMB Mandates, and the Federal AI Governance Imperative

Federal AI governance is now directive, time-bound, and enforceable. Two landmark directives created the most comprehensive AI governance requirements ever issued.

EO 14110 (October 2023)

Every agency must appoint a Chief AI Officer
Complete inventory of all AI use cases
Implement NIST AI RMF risk management

OMB M-24-10 (March 2024)

Concrete safeguards for rights-impacting AI
Monitoring capabilities and human oversight
Discontinue non-compliant AI systems

The Shadow AI Compliance Gap

What Agencies See

Procured AI systems like contract management tools and ML-powered cybersecurity platforms. These appear in procurement records.

What They Miss

AI chatbots, coding assistants, and summarization tools accessed via standard web browsers on government networks.

OMB M-24-10 explicitly requires agencies to maintain inventories of AI use, including AI accessed through third-party services. Browser-based AI tools are third-party services — if they are not inventoried, the agency is out of compliance.

The AI Tools Blocklist closes this gap. Deploy 16,024+ classified AI-tool domains against agency DNS and proxy infrastructure to discover, block, and audit every AI tool.

Agency Chief AI Officer Responsibilities

Chief AI Officer Mandate

Every CFO Act agency must designate a CAIO
Responsible for AI inventory and risk management
Annual certification requires visibility into actual usage

Annual AI Use Case Inventory

Agencies must publicly report AI use case inventories
Shadow AI tools create inventory gaps
DNS-level domain intelligence closes gaps systematically

Cybersecurity + AI governance convergence: For agencies where the CAIO sits within the CIO's office, the same infrastructure enforcing cybersecurity policy can enforce AI governance policy. This is the operational model OMB expects.

FedRAMP & Cloud Authorization

FedRAMP Authorization: The Gatekeeping Requirement for Government AI Tools

Any cloud service processing federal information must hold a FedRAMP ATO. Most AI tools are cloud-based, meaning browser access equals unauthorized cloud service usage.

~380 FedRAMP Authorized CSOs
vs.
16,024+ AI Tool Domains Tracked

The arithmetic is clear: the overwhelming majority of AI tools lack FedRAMP authorization. Without technical enforcement, agencies rely entirely on employee compliance — every CISO knows that is inadequate.

FedRAMP Impact Levels and AI Tool Governance

Authorization level determines what data the tool may process. Category-level controls require the granular domain classification the AI Tools Blocklist provides.

FedRAMP Low

Publicly available federal information only
Insufficient for most government AI use cases

FedRAMP Moderate

Baseline for CUI, PII, and operational data
Covers 80% of gov cloud use cases (NIST SP 800-60)

FedRAMP High

Law enforcement, critical infrastructure, national security
Block all AI categories by default on High networks

StateRAMP and the State-Level Authorization Gap

The Challenge

StateRAMP provides a standardized framework modeled on FedRAMP. Adoption is voluntary and varies significantly by state.

The Solution

Block the domains first, then work backwards to authorize tools through whatever governance process the state employs.

NIST AI Risk Management

NIST AI Risk Management Framework: From Theory to Operational Controls

The NIST AI RMF 1.0 is effectively mandatory for federal agencies through OMB M-24-10. It organizes AI risk management into four core functions.

1. Govern

Establish policies and accountability structures for AI.

Define which AI tools are authorized
Set approval workflows for new tools
Use domain intelligence to define boundaries

2. Map

Contextualize AI risks across your organization.

Identify where AI is used, by whom, for what
18-category taxonomy for immediate mapping
Different categories = different risk profiles

3. Measure

Quantitative and qualitative AI risk assessment.

Track unauthorized tools detected
Monitor data volume submitted to AI tools
Trend data showing risk posture changes

4. Manage

Implement controls that mitigate identified risks.

Block unauthorized AI tools at DNS/proxy/firewall
Directly mitigate risks from Map and Measure
The Blocklist is the enforcement mechanism

FISMA Compliance and Continuous Monitoring

AI tools accessed on government networks are external information systems. Under NIST SP 800-53 control SA-9, agencies must establish trust relationships and monitor continuously.

Unsanctioned AI tool usage violates SA-9 — no trust relationship established, no security controls assessed, no monitoring in place. Each instance requires POA&M documentation and remediation.

FISMA continuous monitoring (NIST SP 800-137)

AI tool discovery is a continuous monitoring obligation, not a one-time audit finding.

Three Pillars of Continuous AI Monitoring

1

Automated Detection

Deploy as an automated feed. Transform monitoring from periodic manual exercise to continuous process.

2

POA&M Generation

Document unauthorized AI usage in the agency's Plan of Action and Milestones, tracked to remediation.

3

Root Cause Prevention

Daily-updated domain feed ensures newly launched AI tools are automatically captured and authorized.

#!/usr/bin/env python3
"""Government AI tool access monitor with CUI tagging and FISMA reporting."""

import csv
import json
import sys
from datetime import datetime
from collections import defaultdict
from enum import Enum

class DataSensitivity(Enum):
    PUBLIC          = "PUBLIC"
    CUI_BASIC       = "CUI_BASIC"
    CUI_SPECIFIED    = "CUI_SPECIFIED"
    CLASSIFIED       = "CLASSIFIED"

class FISMAImpact(Enum):
    LOW      = "LOW"
    MODERATE = "MODERATE"
    HIGH     = "HIGH"

class GovAIToolMonitor:
    """Monitor AI tool access on government networks with CUI awareness."""

    NETWORK_ZONE_SENSITIVITY = {
        "NIPRNET":  DataSensitivity.CUI_BASIC,
        "SIPRNET":  DataSensitivity.CLASSIFIED,
        "JWICS":    DataSensitivity.CLASSIFIED,
        "AGENCY_LAN": DataSensitivity.CUI_BASIC,
        "PUBLIC_DMZ": DataSensitivity.PUBLIC,
    }

    CUI_HIGH_RISK_CATEGORIES = [
        "Text Generation", "Code Generation",
        "Data Analytics", "AI Agents",
        "Voice & Speech", "Healthcare AI",
    ]

    def __init__(self, blocklist_csv: str, fedramp_authorized: str):
        self.ai_domains = {}
        with open(blocklist_csv) as f:
            for row in csv.DictReader(f):
                self.ai_domains[row["domain"].lower()] = {
                    "category": row.get("primary_category", "Unknown"),
                    "tool_name": row.get("tool_name", ""),
                }
        # Load FedRAMP-authorized domains
        self.authorized = set()
        with open(fedramp_authorized) as f:
            for line in f:
                self.authorized.add(line.strip().lower())

    def classify_event(self, domain: str, network_zone: str,
                       user: str, method: str, bytes_sent: int) -> dict:
        """Classify an AI tool access event for FISMA reporting."""
        info = self.ai_domains.get(domain.lower(), {})
        zone_sensitivity = self.NETWORK_ZONE_SENSITIVITY.get(
            network_zone, DataSensitivity.CUI_BASIC
        )
        is_authorized = domain.lower() in self.authorized
        is_cui_risk = info.get("category") in self.CUI_HIGH_RISK_CATEGORIES
        is_data_upload = method == "POST" and bytes_sent > 512

        # Determine FISMA impact level
        if zone_sensitivity == DataSensitivity.CLASSIFIED:
            fisma_impact = FISMAImpact.HIGH
        elif is_cui_risk and is_data_upload:
            fisma_impact = FISMAImpact.HIGH
        elif is_cui_risk or is_data_upload:
            fisma_impact = FISMAImpact.MODERATE
        else:
            fisma_impact = FISMAImpact.LOW

        return {
            "timestamp": datetime.utcnow().isoformat() + "Z",
            "event_type": "GOV_AI_TOOL_ACCESS",
            "domain": domain,
            "tool_name": info.get("tool_name", "Unknown"),
            "category": info.get("category", "Unknown"),
            "network_zone": network_zone,
            "data_sensitivity": zone_sensitivity.value,
            "fedramp_authorized": is_authorized,
            "authorization_status": "AUTHORIZED" if is_authorized else "UNAUTHORIZED",
            "cui_exposure_risk": is_cui_risk and not is_authorized,
            "fisma_impact": fisma_impact.value,
            "user": user,
            "method": method,
            "bytes_sent": bytes_sent,
            "data_upload_detected": is_data_upload,
            "poam_required": not is_authorized,
            "nist_controls": ["SA-9", "AC-20", "SI-4"],
        }

    def generate_fisma_report(self, events: list) -> dict:
        """Generate FISMA-aligned compliance summary."""
        unauthorized = [e for e in events if not e["fedramp_authorized"]]
        cui_risks = [e for e in events if e["cui_exposure_risk"]]
        return {
            "total_ai_access_events": len(events),
            "unauthorized_tool_events": len(unauthorized),
            "unique_unauthorized_tools": len(set(
                e["domain"] for e in unauthorized
            )),
            "cui_exposure_events": len(cui_risks),
            "poam_items_generated": len(set(
                e["domain"] for e in unauthorized
            )),
            "high_impact_events": sum(
                1 for e in events if e["fisma_impact"] == "HIGH"
            ),
        }

# Usage
monitor = GovAIToolMonitor("ai_tools_blocklist.csv", "fedramp_authorized_domains.txt")
event = monitor.classify_event(
    domain="chat.openai.com",
    network_zone="AGENCY_LAN",
    user="[email protected]",
    method="POST",
    bytes_sent=8192,
)
print(json.dumps(event, indent=2))

What This Script Does

FedRAMP Cross-Reference

Classifies every AI tool access event against the agency's FedRAMP authorization list and originating network zone

Impact Flagging

Unauthorized tools with data uploads on CUI networks flagged HIGH and tagged for POA&M generation

NIST Control Mapping

References SA-9, AC-20, and SI-4 — linking directly to control families FISMA assessors evaluate

Network Isolation & CUI

Classified Network Isolation and CUI Protection

Air-Gapped Networks

SIPRNET and JWICS are air-gapped from the internet. AI cloud tools cannot be accessed from classified systems.

Spillage Risk

Personnel use AI tools on unclassified networks to process classified data. This triggers investigation and potential clearance loss.

The real risk is spillage. Personnel with classified access use AI tools on unclassified networks to process, summarize, or analyze information from classified sources. This triggers investigation, potential clearance loss, and mandatory reporting.

Nuanced category-level policies. Block "Text & Language" and "Data Analytics" on classified-adjacent segments while permitting "Design & Creative" for public affairs.

Controlled Unclassified Information: NIST SP 800-171 and CMMC

CUI encompasses a vast range of sensitive government data. Categories span multiple domains of sensitivity.

Law Enforcement Sensitive Export-Controlled Technical Data Privacy-Protected Information Procurement-Sensitive Data

NIST 800-171 Requirements Implicated by AI Tool Usage

Requirement Description AI Tool Relevance
3.1.1 Limit system access to authorized users AI tools are unauthorized systems receiving CUI
3.1.20 Control connection of mobile devices AI tools are uncontrolled data exfiltration channels
3.1.21 Limit use of portable storage devices Browser-based AI tools function like USB drives for CUI
3.13.1 Monitor, control, and protect communications AI tool traffic crosses the external boundary uncontrolled

CMMC 2.0 makes this contractual for defense contractors. Under Level 2, organizations must implement all 110 NIST 800-171 requirements and pass third-party assessment. Unblocked AI tools on CUI networks will be flagged as a boundary protection failure.

CUI Spillage Through AI Tools

Pasting CUI into a chatbot = unauthorized transmission
Requires investigation, reporting, and remediation

CMMC Assessment Readiness

Systematic blocking satisfies multiple requirements
Strengthens overall assessment outcome
Control Mapping

Mapping AI Tool Categories to NIST 800-53 Security Controls

NIST SP 800-53 provides the control catalog for federal security programs. Six control families are directly relevant to AI tool governance.

AC — Access Control AU — Audit & Accountability CM — Configuration Mgmt SI — System Integrity SC — System Protection SA — Services Acquisition

The following configuration maps AI tool categories to specific controls that agencies must implement for each category.

# gov_ai_control_mapping.yaml
# Maps AI tool categories to NIST 800-53 Rev 5 controls and government policy

government_ai_controls:

  global_policy:
    default_action: "BLOCK"
    authorization_required: "FedRAMP ATO or agency-specific ATO"
    governing_directives:
      - "EO 14110 - Safe, Secure, and Trustworthy AI"
      - "OMB M-24-10 - Advancing AI Governance"
      - "FISMA - Federal Information Security Modernization Act"
      - "NIST AI RMF 1.0"

  categories:

    text_generation:
      display_name: "Text & Language AI"
      government_risk: "CRITICAL"
      cui_risk: true
      fedramp_minimum: "Moderate"
      nist_800_53_controls:
        - "AC-2   # Account Management — track who uses AI tools"
        - "AC-20  # Use of External Systems — prohibit without ATO"
        - "AU-2   # Audit Events — log all AI tool access"
        - "AU-6   # Audit Review — review AI access logs weekly"
        - "SA-4   # Acquisition Process — include AI in procurement"
        - "SA-9   # External System Services — require FedRAMP"
        - "SC-7   # Boundary Protection — block at perimeter"
        - "SI-4   # System Monitoring — detect AI tool traffic"
      policy_notes:
        - "Block all unapproved text generation tools"
        - "Approved tools require CUI handling training"
        - "POST requests to approved tools logged for audit"
      network_zones:
        NIPRNET: "BLOCK unless FedRAMP Moderate+"
        AGENCY_LAN: "BLOCK unless agency ATO"
        PUBLIC_DMZ: "ALLOW with logging"

    code_generation:
      display_name: "Code & Development AI"
      government_risk: "HIGH"
      cui_risk: true
      fedramp_minimum: "Moderate"
      nist_800_53_controls:
        - "AC-20  # Use of External Systems"
        - "CM-7   # Least Functionality — disable unnecessary AI tools"
        - "SA-8   # Security & Privacy Engineering — review AI-generated code"
        - "SA-10  # Developer Configuration Mgmt"
        - "SA-11  # Developer Testing — validate AI code output"
        - "SC-7   # Boundary Protection"
        - "SI-10  # Information Input Validation"
      policy_notes:
        - "Never paste classified or CUI source code into AI tools"
        - "AI-generated code requires security review before deployment"
        - "Supply chain risk: AI code tools may introduce vulnerabilities"

    data_analytics:
      display_name: "Data Analytics AI"
      government_risk: "CRITICAL"
      cui_risk: true
      fedramp_minimum: "High"
      nist_800_53_controls:
        - "AC-4   # Information Flow Enforcement — prevent data exfil"
        - "AC-20  # Use of External Systems"
        - "MP-5   # Media Transport — data leaving the boundary"
        - "SA-9   # External System Services"
        - "SC-7   # Boundary Protection"
        - "SC-28  # Protection of Information at Rest"
      policy_notes:
        - "No government datasets uploaded to external AI analytics"
        - "Synthetic or anonymized data only for approved tools"
        - "FedRAMP High required for any PII/CUI analytics"

    ai_agents:
      display_name: "Autonomous AI Agents"
      government_risk: "CRITICAL"
      cui_risk: true
      fedramp_minimum: "High"
      nist_800_53_controls:
        - "AC-6   # Least Privilege — agents must not have admin access"
        - "AU-12  # Audit Record Generation — log all agent actions"
        - "CA-7   # Continuous Monitoring — monitor agent behavior"
        - "SA-9   # External System Services"
        - "SC-7   # Boundary Protection"
        - "SI-4   # System Monitoring"
      policy_notes:
        - "Autonomous AI agents prohibited without CAIO approval"
        - "Human-in-the-loop required for all government decisions"
        - "OMB M-24-10 rights-impacting AI safeguards apply"

    voice_speech:
      display_name: "Voice & Speech AI"
      government_risk: "HIGH"
      cui_risk: true
      fedramp_minimum: "Moderate"
      nist_800_53_controls:
        - "AC-20  # Use of External Systems"
        - "SC-8   # Transmission Confidentiality — encrypt voice data"
        - "SC-7   # Boundary Protection"
        - "SI-4   # System Monitoring"
      policy_notes:
        - "No dictation of CUI content to external speech tools"
        - "Voice data may contain biometric identifiers (PII)"
        - "Conference call transcription requires approved tools only"

How This Policy Engine Works

Automated Enforcement

Auto-identifies violated controls (AC-4, AC-20, SA-9, SC-7)
Determines required FedRAMP level per category
Control references tie directly to the agency's SSP

Zone-Based Policy

Text gen may be allowed on public DMZ for citizen engagement
Strictly blocked on internal CUI networks
Enforce by both tool category and network location
State & Local Government

State and Local Government AI Mandates: An Accelerating Landscape

More than 30 states have enacted or introduced AI governance legislation. Four common themes are emerging across jurisdictions.

AI Inventory & Disclosure

Transparency requirements for all government AI operations.

Human Review Mandates

Human oversight for AI-assisted high-stakes decisions.

Data Protection

Safeguards for AI tools processing resident information.

Procurement Standards

Formal acquisition requirements for government AI systems.

State AI Legislation Highlights

State Mandate Key Requirement
California EO N-12-23 Comprehensive AI use case inventory + deployment guidelines
New York City Local Law 144 Bias auditing for AI tools in employment decisions
Colorado SB 24-205 Impact assessments for high-risk AI systems
Texas HB 2060 AI advisory council + state agency reporting requirements

The foundational requirement is the same across all mandates: know what AI tools your employees are using. The domain feed deployed against DNS or proxy infrastructure provides that visibility.

Supply Chain Risk Management for Government AI Tools

NIST SP 800-161 provides the SCRM framework. AI tools introduce unique supply chain risks that traditional assessments miss.

Compromised Training Data

Poisoned or manipulated datasets producing unreliable outputs.

Embedded Backdoors

Model biases or hidden behaviors introduced during training.

Foreign Adversary Control

Infrastructure operated or controlled by foreign adversary entities.

Section 889 analogy: If an AI tool is developed, hosted, or controlled by a foreign adversary entity, its use on government networks creates supply chain risk. The AI Tools Blocklist provides domain inventory for cross-referencing against FASC exclusion lists, ODNI advisories, and CISA alerts.

30+ State AI Mandates

From inventory mandates to bias auditing. The Blocklist provides the discovery layer every mandate requires.

Procurement Integration

Build approved-vendor lists from the taxonomy. Unapproved tools are blocked at the network layer.

Multi-Jurisdiction Compliance

Unified domain feed with category-level controls. Consistent governance across all jurisdictions.

Implementation Guide

Deploying AI Tool Controls on Government Networks

Government IT teams face unique constraints. Strict change management, lengthy procurement, ATO requirements, and multi-stakeholder coordination.

CIO CISO CAIO Privacy Officer General Counsel
1

Phase 1: Discovery (Weeks 1-4)

Deploy in monitoring-only mode against DNS and proxy logs
Generate the initial AI tool inventory required by OMB M-24-10
Brief the CAIO on findings. No blocking -- observation only
2

Phase 2: Assessment (Weeks 5-8)

Evaluate tools against FedRAMP status and NIST 800-53 controls
Classify into authorized, under-review, and prohibited
Develop the AI acceptable use policy from assessment findings
3

Phase 3: Enforcement (Weeks 9-12)

Activate blocking with informational block pages for users
Configure alerts for high-risk access attempts
Coordinate firewall rule deployment with network security
4

Phase 4: Continuous Governance (Ongoing)

Weekly compliance metrics and quarterly CAIO reporting
Integrate into FISMA continuous monitoring program
Update controls as new executive orders and mandates are issued

Phase-to-Compliance Mapping

Phase Produces Satisfies
Phase 1 AI use case inventory OMB M-24-10 inventory requirement
Phase 2 Risk assessments NIST AI RMF mandate
Phase 3 Technical controls NIST 800-53 specifications
Phase 4 Continuous monitoring evidence Annual FISMA assessments

By completing all four phases, the agency has a comprehensive, auditable, and continuously-updated AI governance program. The CAIO can certify compliance with confidence.

Secure Your Government Network Against Unauthorized AI Tools

Our team works with federal, state, and local agencies to deploy AI tool controls aligned with FedRAMP, FISMA, NIST AI RMF, and executive order requirements. Request a government consultation to get started.

Request a Government Consultation

Tell us about your agency’s network environment, compliance requirements, and AI governance goals. We will map the AI Tools Blocklist to your specific federal or state mandates.