Agentic Trust Framework Specification

April 4, 2026 ยท View on GitHub

Version: 0.9.1 Status: Public Review Draft Last Updated: April 2026

Abstract

This document specifies the Agentic Trust Framework (ATF), a security framework for AI agents based on Zero Trust principles. ATF defines requirements for identity management, behavioral monitoring, data governance, segmentation, and incident response in AI agent systems.

Table of Contents

  1. Introduction
  2. Terminology
  3. Conformance Requirements
  4. Core Elements
  5. Security Considerations
  6. References

1. Introduction

AI agents with access to enterprise systems require security boundaries. This specification defines a framework for implementing Zero Trust security principles in AI agent deployments.

The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in RFC 2119.

2. Terminology

Agent: An autonomous AI system capable of perceiving its environment and taking actions to achieve specific goals.

Agent Identity: A unique, cryptographically verifiable identifier assigned to each agent instance.

Behavioral Baseline: The established pattern of normal operations for a specific agent.

Data Governance: The process of validating inputs and filtering outputs of an agent.

Segmentation: Access control mechanisms that limit agent permissions based on the principle of least privilege.

Kill Switch: A mechanism to immediately halt agent operations.

3. Conformance Requirements

ATF defines 25 core requirements (5 per element), enumerated with formal requirement IDs in CONFORMANCE.md. The requirement IDs (I-1 through I-5, B-1 through B-5, D-1 through D-5, S-1 through S-5, R-1 through R-5) are the canonical identifiers used for conformance assessment.

An implementation is considered ATF-compliant if it:

  1. Addresses the 25 core requirements defined in CONFORMANCE.md at the level appropriate to the target maturity level (Intern, Junior, Senior, or Principal)
  2. Follows the security considerations in Section 5

Implementations MAY extend ATF with additional features but MUST NOT violate core requirements.

The detailed guidance in Section 4 below provides implementation context for each core element. Section 4 expands on the 25 core requirements with specific MUST, SHOULD, and MAY statements that describe how conforming implementations typically address each element. These statements are normative but allow flexibility in implementation approach.

See CONFORMANCE.md for:

  • The complete list of 25 core requirements with formal IDs
  • Two conformance tiers (ATF Compatible and ATF Certified)
  • A maturity level requirements matrix showing MUST/SHOULD/MAY by agent level
  • A conformance statement template

4. Core Elements

4.1 Identity Management

Requirement: Every agent MUST have a unique, verifiable identity.

Core requirements: I-1 (Unique Identifier), I-2 (Credential Binding), I-3 (Ownership Chain), I-4 (Purpose Declaration), I-5 (Capability Manifest). See CONFORMANCE.md for formal definitions and maturity level applicability.

4.1.1 Identity Creation

Implementations MUST:

  • Generate cryptographically unique identifiers for each agent instance
  • Bind identities to specific agent versions and configurations
  • Support identity rotation without service disruption

Implementations SHOULD:

  • Use industry-standard identity formats (UUID, JWT, x.509)
  • Support federated identity providers
  • Log all identity lifecycle events

4.1.2 Identity Verification

Each agent request MUST include:

  • Agent identifier
  • Timestamp
  • Cryptographic proof of identity (signature, token, or certificate)

Example interface (non-normative):

class IdentityManager(Protocol):
    def create_identity(self, agent_config: Dict) -> AgentIdentity:
        """Create new agent identity"""
        
    def verify_identity(self, credentials: Credentials) -> bool:
        """Verify agent credentials"""
        
    def rotate_identity(self, old_id: AgentIdentity) -> AgentIdentity:
        """Rotate credentials maintaining continuity"""

4.2 Behavioral Monitoring

Requirement: Agent behavior MUST be continuously monitored for anomalies.

Core requirements: B-1 (Structured Logging), B-2 (Action Attribution), B-3 (Behavioral Baseline), B-4 (Anomaly Detection), B-5 (Explainability). See CONFORMANCE.md for formal definitions and maturity level applicability.

4.2.1 Baseline Establishment

Implementations MUST:

  • Collect behavioral metrics for at least 7 days or 1000 operations
  • Define normal ranges for key metrics (latency, token usage, API calls)
  • Update baselines periodically (at least monthly)

Metrics to monitor MUST include:

  • Request frequency and patterns
  • Resource consumption (tokens, API calls, compute)
  • Input/output characteristics
  • Error rates and types

4.2.2 Anomaly Detection

Implementations MUST:

  • Detect deviations from baseline exceeding configured thresholds
  • Generate alerts within 60 seconds of anomaly detection
  • Support both statistical and rule-based detection

Implementations SHOULD:

  • Use ML-based anomaly detection where appropriate
  • Correlate anomalies across multiple agents
  • Provide anomaly severity scoring

4.3 Data Governance

Requirement: All agent inputs and outputs MUST be validated.

Core requirements: D-1 (Schema Validation), D-2 (Injection Prevention), D-3 (PII/PHI Protection), D-4 (Output Validation), D-5 (Data Lineage). See CONFORMANCE.md for formal definitions and maturity level applicability.

4.3.1 Input Validation

Implementations MUST:

  • Validate data schema and types
  • Detect potential injection attacks
  • Check for data poisoning patterns

Validation types REQUIRED:

  • Schema validation
  • Content filtering for malicious patterns
  • Statistical anomaly detection for data drift

4.3.2 Output Filtering

Implementations MUST:

  • Scan outputs for sensitive data (PII, secrets, credentials)
  • Apply configurable content filtering
  • Log all filtering actions

Implementations SHOULD:

  • Support custom filtering rules
  • Provide redaction capabilities
  • Enable output sampling for audit

4.4 Segmentation

Requirement: Agent access MUST be limited by least-privilege policies.

Core requirements: S-1 (Resource Allowlist), S-2 (Action Boundaries), S-3 (Rate Limiting), S-4 (Transaction Limits), S-5 (Blast Radius Containment). See CONFORMANCE.md for formal definitions and maturity level applicability.

4.4.1 Access Control

Implementations MUST:

  • Define granular permissions per agent
  • Support time-based access restrictions
  • Enable dynamic permission adjustment based on context

Policy elements REQUIRED:

  • Resource access lists (APIs, databases, services)
  • Operation permissions (read, write, execute)
  • Rate limits and quotas

4.4.2 Network Isolation

Implementations SHOULD:

  • Support network-level segmentation
  • Enable API gateway integration
  • Provide service mesh compatibility

4.5 Incident Response

Requirement: Systems MUST support rapid agent containment and recovery.

Core requirements: R-1 (Circuit Breaker), R-2 (Kill Switch), R-3 (Session Revocation), R-4 (State Rollback), R-5 (Graceful Degradation). See CONFORMANCE.md for formal definitions and maturity level applicability.

4.5.1 Kill Switch

Implementations MUST:

  • Provide immediate agent termination capability (<1 second)
  • Support graceful and forced shutdown modes
  • Maintain audit log of all kill switch activations

4.5.2 Recovery

Implementations MUST:

  • Support rollback to last known good configuration
  • Provide incident investigation capabilities
  • Enable selective agent restart with restrictions

Implementations SHOULD:

  • Automate common incident response procedures
  • Integrate with enterprise incident management
  • Support forensic data collection

5. Security Considerations

5.1 Cryptographic Requirements

All cryptographic operations SHOULD use:

  • AES-256 for symmetric encryption
  • RSA-2048 or ECC P-256 for asymmetric operations
  • SHA-256 or stronger for hashing

5.2 Key Management

Implementations MUST:

  • Never store keys in plain text
  • Support key rotation
  • Use hardware security modules where available

5.3 Audit Logging

All security-relevant events MUST be logged including:

  • Identity operations
  • Policy changes
  • Anomaly detections
  • Kill switch activations

6. References

  • [RFC 2119] Key words for use in RFCs to Indicate Requirement Levels
  • [NIST 800-207] Zero Trust Architecture
  • [NIST AI RMF] AI Risk Management Framework
  • [CSA AICM] AI Controls Matrix (243 controls, 18 domains)
  • [CSA MAESTRO] Multi-Agent Environment Security Threat and Risk Operations
  • [OWASP Top 10 for Agentic Applications] Security risks for agentic AI
  • [ISO/IEC 42001:2023] AI Management System Standard
  • [ISO/IEC 27001:2022] Information Security Management Systems
  • [AWS Agentic AI Security Scoping Matrix] Agent scope classification (Scopes 1-4)
  • "Agentic AI + Zero Trust: A Guide for Business Leaders" by Josh Woodruff

Appendix A: Example Implementation Checklist

  • Identity Management
    • Unique ID generation
    • Credential verification
    • Identity rotation
  • Behavioral Monitoring
    • Metric collection
    • Baseline establishment
    • Anomaly detection
  • Data Governance
    • Input validation
    • Output filtering
    • Audit logging
  • Segmentation
    • Permission policies
    • Access control
    • Rate limiting
  • Incident Response
    • Kill switch
    • Recovery procedures
    • Forensics capability