Internet-Draft AI/Agent WG Intended status: standards-track March 2026 Expires: September 02, 2026 Agent Behavior Verification Protocol (ABVP) for Runtime Compliance Validation draft-ai-agent-behavior-verification-protocol-00 Abstract This document defines the Agent Behavior Verification Protocol (ABVP), a standardized framework for continuously validating that deployed AI agents operate according to their declared policies and specifications. As autonomous agents become increasingly prevalent in critical systems, there is a growing gap between stated agent capabilities and actual runtime behavior verification. ABVP provides mechanisms for real-time behavior monitoring, policy compliance validation, and cryptographic attestation of agent actions against predefined behavioral specifications. The protocol defines a verification architecture that includes behavior witnesses, compliance checkers, and attestation chains to ensure agents maintain fidelity to their declared operational parameters. ABVP integrates with existing agent accountability frameworks while providing specific mechanisms for runtime verification, behavioral drift detection, and compliance reporting. This specification addresses the critical need for trustworthy agent deployment by enabling operators to continuously verify agent behavior matches stated policies throughout the agent lifecycle. Status of This Memo This Internet-Draft is submitted in full conformance with the provisions of BCP 78 and BCP 79. This document is intended to have standards-track status. Distribution of this memo is unlimited. Table of Contents 1. Introduction ................................................ 3 2. Terminology ................................................. 4 3. Problem Statement ........................................... 5 4. Agent Behavior Verification Architecture .................... 6 5. Behavior Specification Format ............................... 7 6. Runtime Verification Protocol ............................... 8 7. Compliance Reporting and Attestation ........................ 9 8. Security Considerations ..................................... 10 9. IANA Considerations ......................................... 11 1. Introduction The proliferation of autonomous AI agents in critical infrastructure, financial systems, and decision-making processes has created an urgent need for continuous verification that these agents operate according to their declared policies and behavioral specifications. Traditional approaches to agent deployment rely on pre-deployment testing and static policy validation, which fail to address the dynamic nature of agent behavior in production environments. As agents adapt, learn, and respond to changing conditions, their actual runtime behavior may diverge significantly from their original specifications, creating security vulnerabilities, compliance violations, and operational risks that remain undetected until system failures occur. Existing agent accountability frameworks primarily focus on post- hoc analysis and audit trails, providing limited capability for real-time behavior verification and immediate detection of policy violations. This reactive approach is insufficient for autonomous systems that make critical decisions with limited human oversight, where behavioral drift or policy violations can have immediate and severe consequences. Current verification methodologies also lack standardized protocols for expressing behavioral constraints in machine-verifiable formats, making it difficult to establish consistent compliance validation across diverse agent implementations and deployment environments. The gap between declared agent capabilities and actual runtime behavior verification represents a fundamental trust problem in autonomous systems deployment. Organizations deploying AI agents face significant challenges in ensuring that agents continue to operate within specified parameters throughout their operational lifecycle, particularly as agents encounter novel situations not covered in initial testing scenarios. This verification gap undermines confidence in agent reliability and limits the adoption of autonomous systems in high-stakes environments where behavioral compliance is critical for safety, security, and regulatory compliance. The Agent Behavior Verification Protocol (ABVP) addresses these challenges by providing a standardized framework for continuous runtime verification of agent behavior against declared specifications. ABVP enables real-time monitoring of agent actions, automated compliance checking against behavioral policies, and cryptographic attestation of verification results to establish trust chains for agent operation validation. The protocol is designed to integrate with existing agent architectures while providing mechanisms for detecting behavioral drift, validating policy adherence, and generating verifiable evidence of agent compliance throughout the operational lifecycle. This specification defines the core protocol mechanisms, message formats, and verification procedures necessary to implement trustworthy agent behavior validation in production deployments. 2. Terminology 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 [RFC2119]. Agent: An autonomous software entity that performs actions or makes decisions according to defined policies and specifications. In the context of ABVP, an agent is a system whose runtime behavior requires continuous verification against its declared operational parameters and behavioral constraints. Behavior Specification: A formally defined set of policies, constraints, and operational parameters that describe the expected and permitted actions of an agent. A behavior specification MUST be machine-readable and verifiable, containing sufficient detail to enable automated compliance checking during agent runtime operation. Behavior Witness: A system component or external entity that observes and records agent actions for verification purposes. A behavior witness MUST provide cryptographically signed attestations of observed agent behavior and MAY operate independently of the agent being monitored to ensure verification integrity. Compliance Validation: The process of evaluating agent runtime behavior against its declared behavior specification to determine conformance. Compliance validation encompasses real-time monitoring, policy checking, and the generation of verification results that attest to agent adherence to specified behavioral constraints. Verification Attestation: A cryptographically signed statement that asserts the compliance status of an agent's behavior relative to its specification during a defined time period. Verification attestations MUST include sufficient detail to enable third-party validation and SHOULD reference the specific behavior specification version and verification criteria used in the assessment. Behavioral Drift: The phenomenon where an agent's actual runtime behavior gradually diverges from its declared specification over time, either due to learning adaptations, environmental changes, or system degradation. ABVP mechanisms MUST be capable of detecting behavioral drift and reporting deviations from established behavioral baselines. 3. Problem Statement The proliferation of autonomous AI agents in critical infrastructure, financial systems, and safety-critical applications has created an urgent need for continuous verification that deployed agents operate within their declared behavioral boundaries. Current agent deployment practices rely primarily on pre-deployment testing and static policy declarations, creating a significant verification gap between an agent's stated capabilities and constraints and its actual runtime behavior. This gap becomes particularly problematic as agents adapt their behavior through learning mechanisms, interact with dynamic environments, or experience gradual behavioral drift due to model degradation or adversarial influences. Traditional software verification approaches are insufficient for autonomous agents because agent behavior is often non- deterministic, context-dependent, and may evolve over time through machine learning processes. Unlike conventional software systems where behavior can be predicted from code analysis, agent systems exhibit emergent behaviors that arise from complex interactions between training data, environmental inputs, and decision-making algorithms. The absence of standardized mechanisms for expressing machine-verifiable behavioral specifications further complicates runtime verification, as operators lack a common framework for defining what constitutes compliant agent behavior and how compliance can be automatically validated. The security and trust implications of unverified agent behavior are substantial, particularly in scenarios where agents operate with elevated privileges or make decisions affecting human safety or economic systems. Behavioral drift, where an agent's actions gradually deviate from intended policies, may go undetected for extended periods without continuous verification mechanisms. Similarly, adversarial attacks that subtly modify agent behavior to achieve malicious objectives could remain unnoticed in systems that lack real-time compliance monitoring. The inability to provide cryptographic attestations of agent behavior compliance also prevents the establishment of trust chains necessary for multi-agent systems or cross-organizational agent interactions. Current accountability frameworks for AI systems focus primarily on explainability and audit trails but do not provide mechanisms for real-time verification of behavioral compliance against formally specified policies. This creates operational risks where agents may violate their declared constraints without immediate detection, potentially causing system failures, security breaches, or regulatory violations. The lack of standardized verification protocols also prevents interoperability between different agent verification systems and limits the ability to establish industry- wide trust frameworks for autonomous agent deployment. 4. Agent Behavior Verification Architecture The ABVP architecture consists of four primary components that work together to provide continuous runtime verification of agent behavior: Agent Runtime Environments (AREs), Behavior Verification Nodes (BVNs), Attestation Authorities (AAs), and Verification Clients (VCs). Agent Runtime Environments host the deployed agents and MUST implement behavior monitoring capabilities that capture relevant behavioral data and forward it to designated Behavior Verification Nodes. These environments MUST provide secure isolation between the agent execution context and the monitoring subsystem to prevent agents from interfering with their own verification processes. The ARE MUST also implement a trusted communication channel to BVNs using protocols such as TLS 1.3 [RFC8446] or QUIC [RFC9000] to ensure behavior data integrity during transmission. Behavior Verification Nodes serve as the core verification engines within the ABVP architecture and MUST implement the runtime verification protocol defined in Section 6. Each BVN maintains a repository of behavior specifications for agents under its verification authority and continuously processes behavioral evidence received from AREs. BVNs MUST validate incoming behavior data against the appropriate specifications and generate compliance assessments in real-time. Multiple BVNs MAY collaborate in a distributed verification network to provide redundancy and prevent single points of failure. When operating in a distributed configuration, BVNs MUST implement consensus mechanisms to ensure consistent verification results across the network. BVNs MUST also implement rate limiting and resource management to handle high- volume verification requests without compromising verification quality. Attestation Authorities provide cryptographic attestation services for verified behavior compliance and MUST maintain secure key management infrastructure capable of generating unforgeable attestations. AAs receive compliance reports from BVNs and MUST verify the authenticity and integrity of these reports before issuing attestations. The AA MUST implement a hierarchical trust model where attestations can be validated through a chain of trust extending to a root certificate authority. AAs SHOULD implement hardware security modules (HSMs) or equivalent trusted execution environments to protect attestation signing keys from compromise. Multiple AAs MAY participate in cross-attestation relationships to provide attestation redundancy and prevent single points of trust failure. Verification Clients represent entities that consume ABVP attestations to make trust decisions about agent behavior and MAY include system operators, regulatory bodies, or other automated systems. VCs MUST implement attestation verification capabilities including certificate chain validation and revocation checking as specified in Section 7. The architecture MUST support both real- time verification queries and batch verification processes to accommodate different operational requirements. VCs SHOULD implement local attestation caching with appropriate cache invalidation mechanisms to reduce verification latency while maintaining attestation freshness. The ABVP architecture MUST provide clear separation of duties between verification components to prevent conflicts of interest and ensure independent verification processes. The communication between architectural components MUST follow the protocol specifications defined in Section 6, with all inter- component communications authenticated and encrypted. The architecture MUST support both synchronous and asynchronous verification modes to accommodate different agent deployment scenarios and performance requirements. Components MUST implement appropriate logging and audit trail capabilities to support forensic analysis and compliance reporting. The overall architecture SHOULD be designed for horizontal scalability to support large-scale agent deployments while maintaining verification performance and reliability. 5. Behavior Specification Format This section defines the standardized format for expressing agent behavioral policies and constraints within the ABVP framework. The behavior specification format enables machine-readable policy declarations that can be automatically verified during agent runtime. All behavior specifications MUST be expressed in a structured format that supports both human readability and automated processing by verification systems. The core behavior specification is structured as a JSON document conforming to the ABVP Behavior Schema. Each specification MUST contain a policy declaration section, verification parameters, and compliance thresholds. The policy declaration section includes behavioral constraints expressed as logical predicates, allowed action sets, and resource utilization bounds. Verification parameters specify the monitoring frequency, sampling rates, and attestation requirements for each declared behavior. Compliance thresholds define the acceptable deviation ranges and tolerance levels for measured behaviors compared to declared specifications. Behavioral constraints within the specification are expressed using a formal constraint language based on temporal logic predicates. Each constraint MUST specify a behavioral property (such as "response_time_bound" or "resource_utilization_limit"), an operator (such as "less_than", "equals", or "within_range"), and target values or ranges. Complex behavioral policies MAY be constructed using logical operators (AND, OR, NOT) to combine multiple constraints. The specification format supports hierarchical constraint groupings to represent different operational modes or contextual behavior variations. The behavior specification includes a verification requirements section that defines how each behavioral constraint should be monitored and validated. This section MUST specify the required verification frequency, acceptable measurement methods, and cryptographic attestation parameters for each constraint. Verification requirements MAY include sampling strategies for performance-sensitive constraints and continuous monitoring directives for safety-critical behaviors. The specification format also supports conditional verification rules that adjust monitoring parameters based on agent operational context or detected behavioral patterns. Each behavior specification MUST include metadata sections containing versioning information, validity periods, and specification dependencies. The metadata enables proper specification lifecycle management and ensures compatibility between agent deployments and verification infrastructure. Specifications SHOULD include digital signatures from authorized policy authors to ensure specification integrity and authenticity. The format supports specification inheritance and composition, allowing complex agent policies to be built from validated behavioral specification components while maintaining verification traceability throughout the composition hierarchy. 6. Runtime Verification Protocol The Runtime Verification Protocol defines the message exchange patterns and procedures that enable continuous monitoring and validation of agent behavior against declared specifications. The protocol operates on a request-response model where Verification Requesters initiate compliance checks, Behavior Monitors observe agent actions, and Compliance Checkers evaluate adherence to behavioral specifications. All protocol participants MUST implement the core verification message set defined in this section, and MAY implement optional extensions for specialized verification scenarios. The protocol is designed to operate over existing transport mechanisms including HTTP/2 [RFC7540], WebSocket [RFC6455], or dedicated secure channels established through TLS 1.3 [RFC8446]. Verification sessions are initiated through a VERIFICATION_REQUEST message that specifies the agent identifier, behavioral specification reference, verification scope, and temporal parameters for the compliance check. The requesting entity MUST include a cryptographically secure session identifier, timestamp bounds for the verification window, and references to the specific behavioral constraints to be validated. Behavior Monitors respond with MONITORING_DATA messages containing timestamped observations of agent actions, decision traces, and relevant contextual information captured during the specified verification window. These messages MUST include integrity protection through digital signatures and SHOULD include privacy-preserving mechanisms when agent actions contain sensitive information. Compliance evaluation proceeds through COMPLIANCE_CHECK messages exchanged between Verification Requesters and designated Compliance Checkers. Each compliance check message MUST reference the behavioral specification being evaluated, include the monitoring data to be assessed, and specify the verification algorithms or rules to be applied. Compliance Checkers process the monitoring data against the behavioral constraints and generate COMPLIANCE_RESULT messages indicating whether the observed behavior satisfies the specified requirements. Results MUST include binary compliance indicators, detailed violation reports when non-compliance is detected, and confidence metrics indicating the reliability of the compliance assessment. The protocol includes mechanisms for handling streaming verification scenarios where agent behavior must be validated continuously rather than in discrete sessions. Streaming verification employs persistent connections where MONITORING_DATA messages are transmitted in near real-time as agent actions occur, enabling immediate detection of behavioral deviations. Compliance Checkers maintain running assessments of behavioral compliance and generate COMPLIANCE_ALERT messages when violations are detected or when behavioral patterns indicate potential drift from specified policies. All streaming verification sessions MUST implement flow control mechanisms to prevent resource exhaustion and SHOULD include adaptive sampling techniques to manage verification overhead in high-throughput scenarios. Attestation generation occurs through ATTESTATION_REQUEST messages that trigger the creation of cryptographic proofs of compliance assessment results. These requests MUST specify the compliance results to be attested, the cryptographic algorithms to be used for attestation generation, and any additional claims or assertions to be included in the attestation. The resulting ATTESTATION_RESPONSE messages contain digitally signed attestations that bind compliance results to specific agents, time periods, and behavioral specifications through tamper-evident cryptographic structures. Attestations MUST include sufficient information to enable independent verification of compliance claims and SHOULD reference the complete verification audit trail to support forensic analysis when behavioral violations occur. 7. Compliance Reporting and Attestation Compliance reporting in ABVP provides a standardized mechanism for documenting and cryptographically attesting to agent behavior verification results. A compliance report MUST contain the agent identifier, verification period, evaluated behavior specifications, compliance status for each specification, and supporting evidence including behavioral observations and verification computations. Reports MUST be generated at configurable intervals or upon detection of compliance violations, with emergency reports triggered immediately when critical policy violations occur. The reporting format MUST support both human- readable summaries and machine-processable structured data to enable automated compliance monitoring and audit trail generation. Cryptographic attestation ensures the integrity and non- repudiation of compliance reports through digital signatures and hash chain mechanisms. Each compliance report MUST be digitally signed by the generating Compliance Checker using keys certified within the ABVP trust framework. Attestations MUST include a timestamp from a trusted time source, the hash of the previous attestation to form a verification chain, and sufficient cryptographic binding to prevent tampering or replay attacks. The attestation format SHOULD follow established standards such as RFC 8392 (CWT) or RFC 7519 (JWT) to ensure interoperability with existing security infrastructures. Trust chain establishment requires a hierarchical certification authority structure where Compliance Checkers obtain certificates from trusted ABVP Certificate Authorities. Root certificates for ABVP trust anchors MUST be distributed through secure channels and updated using standard certificate management practices as defined in RFC 5280. Verification entities MUST validate the complete certificate chain from the signing Compliance Checker to a trusted root before accepting attestations. Certificate revocation MUST be supported through standard mechanisms such as Certificate Revocation Lists (CRLs) or Online Certificate Status Protocol (OCSP) as specified in RFC 5280 and RFC 6960 respectively. The compliance reporting protocol defines specific message formats for distributing attestations to interested parties including agent operators, regulatory authorities, and other verification systems. Compliance reports MAY be distributed through push mechanisms to subscribed entities or pulled on-demand through standardized query interfaces. Report distribution MUST preserve attestation integrity while allowing for appropriate access control based on the sensitivity of the reported agent behaviors. Long-term storage and archival of compliance reports SHOULD implement tamper-evident logging mechanisms to support forensic analysis and regulatory compliance requirements. 8. Security Considerations The ABVP verification infrastructure introduces several security considerations that must be addressed to ensure the integrity and trustworthiness of agent behavior verification. The protocol's reliance on continuous monitoring and attestation creates potential attack vectors that could compromise the verification process itself. Attackers may attempt to subvert verification mechanisms to mask non-compliant agent behavior or to falsely indicate compliance violations where none exist. The verification system MUST be designed with the assumption that both the monitored agents and the verification infrastructure may be targets of sophisticated adversaries seeking to undermine behavioral compliance validation. Attestation integrity represents a critical security requirement for ABVP implementations. Verification attestations MUST be cryptographically signed using mechanisms that provide non- repudiation and tamper detection capabilities. The attestation chain MUST be anchored in a trusted root of trust, such as hardware security modules or trusted platform modules, to prevent forgery of compliance attestations. Implementations SHOULD employ time-stamping mechanisms to prevent replay attacks where old attestations are reused to mask current non-compliance. The cryptographic algorithms used for attestation signing MUST conform to current best practices for digital signatures and SHOULD support algorithm agility to enable updates as cryptographic standards evolve. Key management for attestation signing MUST follow established security practices, including regular key rotation and secure key storage. The distributed nature of ABVP verification creates additional security challenges related to verification node compromise and Byzantine behavior among verification participants. Verification nodes may be compromised by attackers seeking to manipulate compliance reporting or inject false verification results. Implementations MUST employ consensus mechanisms or threshold- based verification approaches to detect and mitigate the impact of compromised verification nodes. The protocol SHOULD include mechanisms for verification node authentication and authorization to prevent unauthorized participants from joining verification networks. Network communications between verification components MUST be encrypted and authenticated to prevent eavesdropping and man-in-the-middle attacks. Implementations SHOULD implement rate limiting and anomaly detection to identify potential denial-of- service attacks against verification infrastructure. Behavioral specification tampering and specification substitution attacks pose significant threats to the ABVP framework's effectiveness. Attackers may attempt to modify behavioral specifications to make non-compliant behavior appear compliant or to introduce specifications that are impossible to verify accurately. Behavioral specifications MUST be cryptographically protected through digital signatures and integrity checking mechanisms. The protocol MUST include versioning and change tracking for behavioral specifications to detect unauthorized modifications. Verification systems SHOULD implement specification validation to detect specifications that contain logical inconsistencies or verification bypasses. Access controls for specification modification MUST follow principle of least privilege and include audit logging of all specification changes. The ABVP verification process may inadvertently expose sensitive information about agent operations, internal state, or the systems being monitored. Verification data collection MUST be designed to minimize information disclosure while maintaining verification effectiveness. Implementations SHOULD employ privacy-preserving techniques such as zero-knowledge proofs or selective disclosure mechanisms where appropriate to limit exposure of sensitive operational details. Verification logs and attestations MUST be protected against unauthorized access and SHOULD include data retention policies that balance verification auditability with privacy requirements. The protocol MUST consider the implications of cross-border data flows when verification infrastructure spans multiple jurisdictions with different privacy regulations. Side-channel attacks and covert channels represent additional security considerations for ABVP implementations. The verification process itself may create observable patterns that could be exploited by attackers to infer information about agent behavior or verification outcomes. Timing-based side channels in verification operations MAY reveal information about the complexity or results of compliance checking. Implementations SHOULD consider countermeasures such as constant-time operations and traffic analysis resistance where appropriate. The protocol design MUST consider how verification metadata and communication patterns might be used to build profiles of agent behavior that could compromise operational security or reveal sensitive system characteristics. 9. IANA Considerations This document requires the registration of several new namespaces and protocol parameters with the Internet Assigned Numbers Authority (IANA). These registrations are necessary to ensure global uniqueness and interoperability of ABVP implementations across different vendors and deployment environments. IANA SHALL establish a new registry titled "Agent Behavior Verification Protocol (ABVP) Parameters" under the "Structured Syntax Suffixes" registry group. This registry SHALL contain three sub-registries: "Behavior Specification Schema Types", "Verification Message Types", and "Attestation Format Identifiers". The registration policy for all ABVP parameter sub- registries SHALL follow the "Specification Required" policy as defined in RFC 8126, with the additional requirement that all registrations include a reference to a publicly available specification document and demonstrate interoperability with at least one existing ABVP implementation. The "Behavior Specification Schema Types" sub-registry SHALL maintain identifiers for standardized behavior specification formats as defined in Section 5. Each registration MUST include a unique identifier string, a human-readable description, a reference specification, and version information. Initial registrations SHALL include "abvp-policy-v1" for the base policy specification format and "abvp-constraints-v1" for behavioral constraint specifications. The "Verification Message Types" sub- registry SHALL contain identifiers for protocol messages defined in Section 6, including verification requests, compliance reports, and attestation messages. Registration entries MUST specify the message identifier, purpose, required parameters, and applicable verification contexts. The "Attestation Format Identifiers" sub-registry SHALL maintain identifiers for cryptographic attestation formats used in compliance reporting as specified in Section 7. Each registration MUST include the attestation format identifier, cryptographic algorithm requirements, trust model specifications, and interoperability considerations. IANA SHALL reserve the identifier prefix "abvp-" for protocol-specific attestation formats and MAY delegate sub-namespace management to recognized standards bodies for domain-specific attestation requirements. All registry entries MUST include contact information for the registrant and SHALL be subject to periodic review to ensure continued relevance and security adequacy. Author's Address Generated by IETF Draft Analyzer 2026-03-01