The Problem: Static Controls Won't Meet the 2026 Deadline
You're racing toward the Department of Defense's zero trust implementation deadline with a security stack built for perimeter defense. The Pentagon is shifting technical priorities from foundational zero trust capabilities to advanced behavioral analytics tools that use machine learning to detect anomalous user activity and assign dynamic risk scores. If you're still enforcing static allow/deny controls, you're not implementing zero trust; you're just adding more gates to the same perimeter.
The department's zero trust strategy explicitly requires analysis of events, activities, and behaviors to derive context and apply AI and machine learning. This isn't optional work. It's the difference between continuous verification and security theater.
What You Need Before Starting
Infrastructure Requirements
Your environment must support real-time telemetry collection and policy enforcement. You need:
- Centralized identity provider supporting SAML 2.0 or OpenID Connect with attribute-based access control
- Security Information and Event Management (SIEM) or data lake capable of ingesting behavioral telemetry at scale
- API access to all systems generating authentication, authorization, and data access events
- Network visibility into east-west traffic, not just north-south perimeter flows
Data Foundations
User and Entity Behavior Analytics (UEBA) requires baseline activity data. Before you deploy behavioral analytics:
- Collect at least 30 days of authentication logs, data access patterns, and application usage telemetry
- Document your current access policies in machine-readable format (JSON, YAML)
- Identify Controlled Unclassified Information flows and data repositories subject to NIST SP 800-171 requirements
- Map Non-Person Entity accounts and their authorized behaviors
Team Capabilities
You'll need security engineers who can translate risk thresholds into policy logic and program managers who understand the Risk Management Framework assessment process. If you're planning to integrate this into Enterprise Mission Assurance Support Service workflows, designate someone who knows how to document compensating controls and continuous monitoring strategies.
Step-by-Step Implementation
Phase 1: Deploy Behavioral Baselining (Weeks 1-4)
Start with read-only monitoring. Don't enforce anything yet.
Configure your UEBA platform to ingest:
- Authentication events (success, failure, MFA challenges)
- Data access requests and file operations
- Application usage patterns and API calls
- Network connection metadata
Set detection rules for deviation from baseline:
- Geographic anomalies (authentication from unexpected locations)
- Time-of-day violations (access outside normal working hours)
- Privilege escalation attempts
- Unusual data volume transfers
Tag each event with user identity, device posture, application context, and data sensitivity classification. This is the telemetry foundation for dynamic risk scoring.
Phase 2: Implement Dynamic Risk Scoring (Weeks 5-8)
Build a risk scoring model that assigns numerical values to behavioral signals. A simple starting framework:
Low-risk baseline activities: Score 0-30
Moderate-risk deviations: Score 31-60 (unusual time, new device)
High-risk anomalies: Score 61-100 (geographic jump, privilege escalation, CUI access from unmanaged device)
Configure your policy engine to calculate composite risk scores in real time. When a user authenticates, the system evaluates:
- Device compliance posture
- Network location trust level
- Recent behavioral anomalies
- Sensitivity of requested resource
The score determines the Authenticator Assurance Level required and whether step-up authentication triggers.
Phase 3: Automate Adaptive Policy Controls (Weeks 9-12)
This is where you move from monitoring to enforcement. Configure your access control system to adjust authorization decisions based on calculated risk:
Risk score 0-30: Standard authentication flow
Risk score 31-60: Require step-up MFA, restrict to read-only access
Risk score 61-100: Block access, trigger Security Orchestration, Automation, and Response workflow for investigation
Implement these controls incrementally:
- Start with non-production systems
- Run in alert-only mode for two weeks
- Enable enforcement for a pilot user group
- Expand to full production after validating false positive rates below 5%
Phase 4: Integrate Data-Centric Controls (Weeks 13-16)
The Pentagon's focus on data usage context means you need to enforce policy at the data layer, not just the application perimeter.
Deploy automated data tagging for CUI and other sensitive information. Configure your Data Loss Prevention controls to:
- Inspect file operations in real time
- Apply risk-based restrictions (block download to unmanaged devices when risk score exceeds threshold)
- Log all CUI access events for audit logging requirements under NIST SP 800-171 3.3.1
Connect these controls to your risk scoring engine so that attempting to exfiltrate sensitive data automatically elevates the user's risk score and triggers additional verification steps.
Validation: How to Verify It Works
Test Anomaly Detection
Run controlled tests to confirm your behavioral analytics detect deviations:
- Authenticate from a new geographic location, system should flag the anomaly and require step-up authentication
- Attempt to access CUI outside normal working hours, risk score should increase
- Simulate privilege escalation, access should be blocked and alert generated
Measure Policy Response Time
Your adaptive controls must operate in real time. Measure the latency between:
- Risk score calculation and policy adjustment (target: under 2 seconds)
- Anomaly detection and SOAR workflow initiation (target: under 30 seconds)
If you're seeing delays beyond these thresholds, your architecture can't support continuous verification.
Audit Logging Completeness
Verify you're capturing the audit records required for continuous monitoring under the Risk Management Framework. Every access decision should generate a log entry containing:
- User identity and authentication method
- Calculated risk score and contributing factors
- Resource requested and action taken
- Timestamp and session identifier
Export a week's worth of logs and confirm you can reconstruct the decision logic for any access event.
Maintenance and Ongoing Tasks
Weekly: Review High-Risk Alerts
Investigate all blocked access attempts and risk scores above 80. Document false positives and tune your detection rules to reduce noise without compromising security.
Monthly: Retrain Behavioral Baselines
User behavior changes. Rebaseline your UEBA models monthly to account for:
- New applications deployed
- Organizational changes affecting normal access patterns
- Seasonal variations in activity
Quarterly: Update Risk Scoring Thresholds
As you collect more data, refine your risk scoring model. Analyze which signals best predict actual security incidents and adjust weighting accordingly.
Continuous: Document for Assessment
If you're pursuing Continuous Authorization, maintain evidence that your adaptive controls are functioning as designed. Your independent assessor will want to see:
- Configuration baselines for your behavioral analytics platform
- Test results demonstrating anomaly detection
- Audit Logging showing policy enforcement
- Tuning decisions and their rationale
This documentation satisfies continuous monitoring requirements and demonstrates that your zero trust implementation isn't just deployed, it's operating as your security architecture claims.
