Internet-Draft lake Intended status: standards-track March 2026 Expires: September 05, 2026 Agent Behavior Verification Protocol (ABVP) draft-ai-agent-behavior-verification-protocol-00 Abstract Autonomous AI agents operate with increasing independence across network environments, making it critical to verify that their actual behavior matches expected policies and constraints. Existing approaches focus primarily on identity verification or single-point attestation, leaving gaps in continuous behavior monitoring and cross-protocol verification. This document defines the Agent Behavior Verification Protocol (ABVP), which provides standardized mechanisms for capturing, validating, and attesting to agent behavior patterns in real-time. ABVP enables continuous trustworthiness assessment through cryptographic behavior proofs, supports multi-vendor attestation environments, and integrates with existing authorization frameworks. The protocol addresses the fundamental challenge of moving from 'who is this agent?' to 'is this agent behaving as expected?' across diverse operational contexts. ABVP complements existing agent authentication and authorization protocols by providing the missing behavior verification layer essential for autonomous agent deployment at scale. 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. Terminology The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in BCP 14 [RFC2119] [RFC8174] when, and only when, they appear in all capitals, as shown here. Behavior Attestation A cryptographically signed assertion about an agent's observed behavior patterns over a specified time period Verification Proof Cryptographic evidence that demonstrates an agent's compliance with specified behavioral constraints Behavior Trace A structured record of agent actions, decisions, and reasoning processes that can be cryptographically verified Trust Anchor A root source of trust for behavior verification, typically backed by hardware attestation or multi-party consensus Behavior Policy A formal specification of expected agent behavior patterns and constraints Verification Registry A distributed system for storing and validating behavior attestations and verification proofs Table of Contents 1. Introduction ................................................ 3 2. Terminology ................................................. 4 3. Problem Statement ........................................... 5 4. ABVP Architecture and Components ............................ 6 5. Behavior Capture and Attestation Mechanisms ................. 7 6. Protocol Integration and Bindings ........................... 8 7. Verification Workflows and Enforcement ...................... 9 8. Security Considerations ..................................... 10 9. IANA Considerations ......................................... 11 10. References .................................................. 12 1. Introduction The proliferation of autonomous AI agents across network environments has introduced a fundamental challenge in distributed systems: verifying that agents behave according to their intended design and declared policies throughout their operational lifecycle. Traditional authentication and authorization mechanisms, as defined in frameworks like OAuth 2.0 [RFC6749] and established in agent-specific protocols [draft-aylward-aiga-1], primarily focus on identity verification and initial access control decisions. However, these approaches are insufficient for autonomous agents that operate independently over extended periods, modify their behavior based on learning, and interact across multiple administrative domains without continuous human oversight. Current verification approaches leave critical gaps in ongoing behavioral assurance. While existing protocols can answer "who is this agent?" through identity attestation, they cannot adequately address "is this agent behaving as expected?" during operation. This limitation becomes particularly problematic when agents exhibit Dynamic Behavior Authentication requirements, where the agent's behavioral patterns change over time based on learning algorithms, environmental adaptation, or policy updates. The absence of standardized Behavioral Trustworthiness Assessment mechanisms means that authorization decisions cannot incorporate an agent's actual behavioral history, leading to either overly restrictive policies that limit legitimate agent autonomy or overly permissive policies that create security risks. The Agent Behavior Verification Protocol (ABVP) addresses these limitations by providing a standardized framework for Continuous Trustworthiness Verification that extends beyond initial authentication to ongoing behavioral validation. ABVP complements existing agent authentication protocols by introducing behavior attestation mechanisms that capture, verify, and attest to agent behavior patterns using cryptographic proofs. The protocol leverages hardware-backed attestation capabilities, similar to those used in verifiable agent conversations [draft-birkholz- verifiable-agent-conversations], while extending the verification scope from message integrity to comprehensive behavior pattern validation. ABVP integrates with existing authorization frameworks by providing behavior verification inputs that enhance access control decisions. Rather than replacing current agent protocols, ABVP serves as a behavior verification layer that can be bound to existing communication protocols and authorization systems. The protocol enables verification registries to maintain distributed records of agent behavior attestations, allowing multiple parties to contribute to and benefit from behavioral trustworthiness assessments. This approach supports multi-vendor environments where agents from different providers must demonstrate behavioral compliance to shared policies and constraints. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in BCP 14 [RFC2119] [RFC8174] when, and only when, they appear in all capitals, as shown here. This document assumes familiarity with cryptographic attestation concepts, JSON-based data structures [RFC8259], and existing agent protocol frameworks. 2. Terminology This document uses terminology from several domains including cryptographic attestation, autonomous agent systems, and distributed verification protocols. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in BCP 14 [RFC2119] [RFC8174] when, and only when, they appear in all capitals, as shown here. **Agent**: An autonomous software entity that operates independently to achieve specified goals, potentially across multiple network environments and administrative domains. Agents may modify their behavior over time through learning, adaptation, or policy updates as defined in [draft-aylward- aiga-1]. **Behavior Attestation**: A cryptographically signed assertion about an agent's observed behavior patterns over a specified time period. Behavior attestations provide verifiable evidence of agent actions, decisions, and compliance with established policies, extending the concept of verifiable agent conversations [draft-birkholz-verifiable-agent-conversations] to broader behavioral patterns. **Behavior Policy**: A formal specification of expected agent behavior patterns and constraints, expressed as machine-readable rules that define acceptable and unacceptable agent actions. Behavior policies serve as the normative baseline against which agent behavior is measured and verified. **Behavior Trace**: A structured, chronologically ordered record of agent actions, decisions, and reasoning processes that can be cryptographically verified for integrity and authenticity. Behavior traces form the evidentiary foundation for behavior attestations and MUST be tamper-evident through cryptographic linking as specified in [RFC9052]. **Trust Anchor**: A root source of trust for behavior verification, typically backed by hardware attestation mechanisms, trusted execution environments, or multi-party consensus protocols. Trust anchors provide the cryptographic foundation for establishing the authenticity and integrity of behavior attestations, similar to certificate authorities in PKI systems [RFC5280]. **Verification Proof**: Cryptographic evidence that demonstrates an agent's compliance with specified behavioral constraints, generated through zero-knowledge proofs, hash chains, or other cryptographic mechanisms. Verification proofs enable third parties to validate agent behavior without requiring access to sensitive operational details, supporting the cryptographic proof-based autonomy model [draft-berlinai-vera]. **Verification Registry**: A distributed system for storing, indexing, and validating behavior attestations and verification proofs. The registry provides a queryable interface for behavior verification while maintaining appropriate privacy controls and access restrictions based on authorization frameworks such as OAuth 2.0 [RFC6749]. **Behavior Attestation Engine (BAE)**: A trusted component responsible for continuously monitoring agent behavior, generating behavior traces, and producing cryptographically signed behavior attestations. The BAE operates within a trusted execution environment or relies on hardware security modules to ensure the integrity of the attestation process. 3. Problem Statement Current agent verification systems primarily focus on establishing "who" an agent is through identity and capability attestation, but fail to address the fundamental question of "how" an agent behaves over time. Traditional approaches, as described in existing frameworks [RFC6749] and emerging agent protocols [draft-birkholz- verifiable-agent-conversations], concentrate on static verification points such as initial authentication, capability declarations, and single-point attestations. While these mechanisms successfully establish agent identity and initial trustworthiness, they create significant gaps in ongoing behavioral assurance as agents operate with increasing autonomy across distributed network environments. The challenge becomes more acute when considering autonomous agents that inherently modify their behavior patterns based on environmental feedback, learning algorithms, or Real-Time Task Adaptability requirements [draft-cui-ai-agent-task]. Existing attestation systems, including advanced approaches like Multi- Vendor TEE Attestation (M-TACE) [draft-aylward-aiga-1], excel at verifying the integrity of agent code and initial state but cannot validate whether an agent's runtime behavior adheres to expected policies after deployment. This creates a verification gap where an agent may pass initial attestation checks while subsequently exhibiting behaviors that violate operational constraints, security policies, or ethical guidelines without detection. Furthermore, current verification approaches lack standardized mechanisms for continuous behavior monitoring across heterogeneous environments. Agent Reasoning Trace Capture techniques [draft- birkholz-verifiable-agent-conversations] provide valuable insights into decision-making processes but do not establish cryptographic proofs of behavioral compliance that can be verified by third parties. The absence of standardized Behavior Traces and Verification Proofs means that each deployment environment must develop proprietary monitoring solutions, leading to fragmented trust models and limited interoperability between agent ecosystems. The temporal dimension of agent behavior verification presents additional challenges that existing protocols do not adequately address. Static verification mechanisms cannot account for the dynamic nature of autonomous agents that adapt their strategies, modify their interaction patterns, or evolve their decision-making processes over operational lifetimes. Without continuous Behavior Attestation capabilities, network operators and service providers cannot maintain confidence in agent trustworthiness beyond initial deployment, creating significant risks for mission-critical applications and cross-organizational agent interactions. Current authorization frameworks also lack integration points for ongoing behavioral verification, focusing instead on capability- based access control determined at authentication time. The absence of standardized Behavior Policy enforcement mechanisms means that agents operating within their assigned capabilities may still exhibit problematic behaviors that violate implicit operational expectations or emergent security requirements. This gap becomes particularly problematic in multi-tenant environments where agents from different organizations interact, requiring mutual assurance of behavioral compliance that extends beyond simple identity verification. The scalability challenges of behavior verification compound these issues, as existing approaches do not provide efficient mechanisms for aggregating behavioral evidence across distributed deployments or enabling third-party verification of agent conduct. Without standardized Verification Registry systems and Trust Anchor mechanisms, each verification attempt requires independent evidence collection and validation, creating computational and administrative overhead that limits practical deployment of comprehensive behavior monitoring in large-scale autonomous agent environments. 4. ABVP Architecture and Components The Agent Behavior Verification Protocol (ABVP) architecture consists of three primary components that work together to provide continuous behavior verification for autonomous AI agents. These components establish a comprehensive framework for capturing, validating, and attesting to agent behavior patterns in real-time across diverse operational environments. The architecture is designed to be vendor-neutral, protocol-agnostic, and compatible with existing agent authentication and authorization frameworks as defined in [RFC6749] and referenced in [draft-aylward-aiga-1]. +----------+ +--------------+ +-------------+ | | | Behavior | | | | Agent |--->| Attestation |--->| Verification| | | | Engine | | Registry | +----------+ +------+-------+ +------+------+ | | v v +------+-------+ +------+------+ | Behavior | | Trust | | Traces | | Anchor | | (signed) | | Management | +--------------+ +-------------+ Figure 1: ABVP Architecture Components The Behavior Attestation Engine (BAE) serves as the core component responsible for capturing agent behavior traces and generating cryptographic attestations. Each BAE MUST maintain a secure execution environment that continuously monitors agent actions, decisions, and reasoning processes without interfering with agent operation. The BAE generates behavior traces using structured formats based on [RFC8259] and creates cryptographically signed attestations using mechanisms defined in [RFC9052]. These attestations follow the Five Enforcement Pillars with Typed Schemas pattern, providing comprehensive coverage across authorization enforcement, data handling compliance, operational boundary adherence, communication protocol compliance, and resource utilization monitoring. The BAE SHOULD integrate with hardware-based Trusted Execution Environments (TEEs) when available to provide additional attestation integrity guarantees as specified in existing RATS frameworks. Verification Registries provide distributed storage and validation services for behavior attestations and verification proofs generated by BAEs. These registries operate using a federated trust model similar to the Public Registry Enrollment Mode, enabling cross-organizational behavior verification without requiring direct trust relationships between all participants. Each registry MUST validate the cryptographic integrity of incoming attestations, verify the authenticity of the attesting BAE, and maintain tamper-evident logs of all verification activities. Verification Registries support both real-time queries for immediate behavior verification and batch processing for historical behavior analysis. The registries expose standardized APIs that allow verifying parties to retrieve behavior attestations, validate verification proofs, and assess agent trustworthiness based on historical behavior patterns. Trust Anchor Management provides the foundational trust infrastructure that enables the entire ABVP ecosystem to function reliably. Trust anchors serve as root sources of trust for behavior verification and are typically backed by hardware attestation mechanisms, multi-party consensus systems, or established certificate authorities as defined in [RFC5280]. The Trust Anchor Management component MUST provide mechanisms for trust anchor discovery, validation, and lifecycle management including key rotation and revocation. Following the DNS TXT Records approach for agent identity distribution, trust anchor information MAY be published using DNS infrastructure to enable scalable trust anchor discovery across organizational boundaries. Trust Anchor Management also defines the policies and procedures for establishing new trust anchors, managing trust relationships between different ABVP deployments, and handling trust anchor compromise or revocation scenarios. The interaction between these components creates a continuous behavior verification loop that provides ongoing assurance of agent trustworthiness. When an agent performs actions, the associated BAE captures these activities as behavior traces and generates signed attestations that are stored in Verification Registries. Verifying parties can query these registries to obtain current and historical behavior attestations, validate them against relevant trust anchors, and make informed decisions about agent trustworthiness. This architecture supports both centralized deployments within single organizations and federated deployments spanning multiple organizations, enabling behavior verification across the full spectrum of autonomous agent operational scenarios. The modular design allows organizations to implement components incrementally while maintaining interoperability with existing agent infrastructure and protocols such as those defined in [draft-birkholz-verifiable-agent-conversations]. 5. Behavior Capture and Attestation Mechanisms The ABVP behavior capture subsystem defines standardized mechanisms for recording agent actions, decisions, and reasoning processes in a cryptographically verifiable format. Agent implementations MUST generate behavior traces that capture sufficient detail to enable meaningful verification against behavioral policies. These traces MUST include timestamped records of agent actions, input stimuli, decision reasoning (as specified in [draft-birkholz-verifiable-agent-conversations]), and any policy evaluations performed by the agent. The behavior capture mechanism SHOULD be implemented as close to the agent's core reasoning engine as possible to minimize opportunities for tampering or selective reporting. Behavior traces MUST be structured as JSON objects [RFC8259] containing mandatory fields for agent identity, timestamp, action type, input context, and reasoning chain. The reasoning chain field leverages the agent reasoning trace capture mechanisms defined in [draft-birkholz-verifiable-agent-conversations] to provide transparency into the agent's decision-making process. Each trace entry MUST be signed using the agent's cryptographic identity as established through hardware-backed verification systems [draft-aylward-aiga-1]. Implementations MAY compress or summarize behavior traces for efficiency while maintaining cryptographic integrity through merkle tree structures or similar authenticated data structures. The attestation generation process transforms behavior traces into cryptographically signed behavior attestations that can be independently verified by third parties. Attestation engines MUST create attestations in JSON Web Signature (JWS) format [RFC7515] using keys derived from or backed by hardware trust anchors. For implementations with Trusted Platform Module (TPM) support, attestations SHOULD include TPM-backed signatures following patterns similar to those defined for email attestation in [draft- drake-email-tpm-attestation]. The attestation payload MUST include a hash of the complete behavior trace, the evaluation period, applicable behavior policies, and compliance assertions. Hardware attestation integration provides the foundational trust layer for ABVP by anchoring behavior attestations to tamper- resistant hardware. Agents operating on platforms with Trusted Execution Environment (TEE) capabilities MUST generate attestations from within the TEE to ensure behavior trace integrity. The attestation process MUST establish a cryptographic chain of trust from the hardware root of trust through the agent's runtime environment to the behavior attestation itself. This chain enables verifiers to confirm not only that the attestation is authentic but also that the underlying behavior capture mechanism has not been compromised. Attestation formats MUST support both real-time streaming attestations for continuous verification and batch attestations for periodic compliance reporting. Streaming attestations provide immediate behavior verification but require more computational overhead, while batch attestations enable efficient verification of longer behavior patterns. Implementations SHOULD support attestation aggregation mechanisms that allow multiple related behavior traces to be combined into a single attestation without losing verification granularity. All attestations MUST include sufficient metadata to enable policy evaluation and MUST be resistant to replay attacks through appropriate nonce and timestamp mechanisms as specified in [RFC8446] for cryptographic freshness. 6. Protocol Integration and Bindings ABVP is designed to operate as a complementary layer alongside existing agent protocols and authorization frameworks, providing behavior verification capabilities without disrupting established communication patterns. The protocol integrates through standardized extension points and binding mechanisms that allow existing agent infrastructures to incrementally adopt behavior verification. ABVP bindings MUST be implemented in a manner that preserves backward compatibility with agents that do not support behavior verification while providing enhanced trust capabilities for ABVP-enabled environments. The protocol defines three primary integration patterns: inline verification where behavior attestations are embedded directly in protocol messages, out-of-band verification where behavior proofs are transmitted through separate channels, and registry-based verification where behavior attestations are stored in distributed verification registries for asynchronous validation. For OAuth 2.0 [RFC6749] and similar authorization frameworks, ABVP extends token-based flows by including behavior verification claims within JWT tokens [RFC7519] or as additional attestation headers. The Behavior Attestation Engine generates verification proofs that reference the agent's recent behavior traces and embeds these within the authorization context, enabling authorization servers to make access decisions based on both identity and behavioral compliance. Integration with Trusted Execution Environment (TEE) based agent frameworks leverages hardware attestation capabilities to anchor behavior verification in secure enclaves. ABVP bindings for TEE environments utilize the JOSE DVS extension mechanisms to provide derived verification signatures that combine hardware attestation with behavior proofs. The protocol supports integration with existing verifiable agent conversation frameworks [draft-birkholz- verifiable-agent-conversations] by extending conversation attestation to include behavioral compliance assertions. When integrated with agent discovery protocols, ABVP provides post- discovery authorization handshake capabilities that validate behavioral constraints before permitting tool execution or authority delegation. Protocol message formats utilize CBOR Web Token (CWT) structures [RFC9052] for compact behavior attestations in bandwidth- constrained environments, while supporting JSON-based attestation formats [RFC8259] for web-oriented integrations. ABVP bindings MUST specify the transport-specific mechanisms for behavior verification, including TLS 1.3 [RFC8446] extension points for embedding behavior proofs in secure channels and X.509 [RFC5280] certificate extensions for long-term behavior attestation storage. The protocol defines standard header fields and message extensions that enable behavior verification across HTTP-based agent communications, WebSocket connections, and message queue systems. Behavior policy alignment with standardized vocabularies such as AIPREF enables consistent behavior verification across multi- vendor agent environments. ABVP protocol bindings support dynamic policy negotiation where agents and verification entities can establish mutually acceptable behavior constraints and attestation formats during protocol handshake. The integration framework provides hooks for custom behavior verification logic while maintaining interoperability through standardized attestation formats and verification procedures. Implementation guidance specifies how existing agent frameworks can incrementally adopt ABVP capabilities, starting with passive behavior logging and progressing to active behavior enforcement and attestation generation. 7. Verification Workflows and Enforcement This section defines the operational workflows that enable continuous behavior verification for autonomous agents. ABVP supports three primary verification patterns: real-time verification for immediate trust decisions, batch verification for historical compliance assessment, and dispute resolution for handling verification conflicts. Each workflow integrates with existing authorization frameworks while providing the behavioral assurance layer necessary for autonomous agent operations. Agent BAE Registry Verifier | | | | |--action-->| | | | |--trace------>| | | |--attest----->| | | | | | | | |<--query-----| | | |---proof---->| | | | |--eval | | | | | | | [batch] | | | |<--audit-----| | | |---report--->| | | | | Figure 2: Real-time Verification Workflow Real-time verification workflows enable immediate assessment of agent behavior during active operations. When an agent initiates actions that require behavioral validation, the Behavior Attestation Engine MUST generate a verification proof that demonstrates compliance with applicable behavior policies. The verification proof SHALL be constructed using Public Key Derived HMAC mechanisms as specified in [draft-bastian-jose-pkdh], allowing verifiers to authenticate behavior attestations using only public key information from the agent's JWS tokens. Resource servers implementing ABVP MUST validate these proofs against registered behavior policies before authorizing agent actions. The real-time workflow supports integration with OAuth 2.0 [RFC6749] access tokens through delegation evidence verification, enabling Resource Servers to verify behavior attestations using AS-attested keys bound to access tokens as described in [draft-chu-oauth-as- attested-user-cert]. Batch verification workflows provide mechanisms for historical behavior analysis and compliance reporting. Verification Registries MUST support batch processing of behavior traces covering extended time periods, enabling policy compliance assessment across multiple operational contexts. The batch verification process SHALL generate aggregated verification proofs that demonstrate sustained compliance with behavior policies over time. Batch workflows MUST implement congestion control mechanisms consistent with vendor-neutral behavior definitions for AI fabric environments to prevent verification processing from impacting operational performance. Verification results MUST be stored in structured formats using JSON [RFC8259] encoding and signed using CBOR Object Signing and Encryption (COSE) [RFC9052] to ensure integrity and non-repudiation. Dispute resolution workflows address scenarios where behavior verification results are contested or inconsistent across multiple verification sources. When verification conflicts arise, the dispute resolution process MUST invoke multi-party attestation mechanisms involving relevant Trust Anchors to establish authoritative behavior assessments. The dispute resolution workflow SHALL generate resolution evidence that includes cryptographic proofs from multiple verification sources and a consensus determination of agent behavior compliance. Enforcement mechanisms MUST support graduated responses to behavior policy violations, ranging from behavioral warnings and restricted operation modes to complete agent authorization revocation. Policy integration points SHALL enable dynamic adjustment of behavior constraints based on operational context, agent trust levels, and historical compliance patterns, ensuring that enforcement actions are proportionate to assessed risks while maintaining operational continuity for compliant autonomous agents. 8. Security Considerations The security architecture of ABVP introduces novel attack surfaces and trust model complexities that require careful analysis. The protocol's reliance on continuous behavior monitoring creates potential privacy vectors where sensitive agent reasoning processes and decision patterns become observable to verification entities. Implementers MUST ensure that behavior traces capture only policy-relevant actions while maintaining operational privacy through selective disclosure mechanisms. The cryptographic binding between behavior attestations and verification proofs, as defined in [RFC9052], provides integrity protection but assumes the underlying attestation infrastructure remains uncompromised. When utilizing Multi-Vendor TEE Attestation (M-TACE) as specified in [draft-aylward-aiga-1], implementations SHOULD distribute trust across multiple hardware vendors to mitigate single-vendor compromise scenarios, though this approach increases complexity in trust anchor management and attestation verification workflows. Behavior spoofing attacks represent a fundamental threat to ABVP's security model, where malicious agents attempt to generate false behavior traces that appear compliant while executing unauthorized actions. The protocol addresses this through cryptographic proof- based autonomy mechanisms that require agents to demonstrate compliance through zero-knowledge proofs before receiving operational privileges. However, the effectiveness of these protections depends critically on the tamper-resistance of the behavior capture mechanisms and the integrity of the Trusted Execution Environment. Implementations MUST validate that TEE attestations conform to the hardware security requirements defined in the relevant trust anchor specifications, and SHOULD implement continuous attestation refresh cycles to detect runtime compromises. The integration with existing authorization frameworks [RFC6749] creates additional attack vectors where compromised authorization tokens could be used to bypass behavior verification requirements. The trust model underlying ABVP assumes that Trust Anchors maintain cryptographic integrity and operate according to specified governance policies. This assumption creates systemic risks where compromise of trust anchors could invalidate entire verification domains. Implementations SHOULD implement trust anchor rotation mechanisms and maintain distributed trust models that prevent single points of failure. The protocol's integration with verifiable agent conversations [draft-birkholz-verifiable- agent-conversations] introduces cross-protocol security dependencies where vulnerabilities in conversation verification could compromise behavior attestation integrity. Additionally, the use of JSON Web Tokens [RFC7519] for attestation transport creates standard token-based attack surfaces including replay attacks and token manipulation, which MUST be mitigated through proper timestamp validation, nonce mechanisms, and secure token storage practices as specified in [RFC8446]. Temporal attacks against ABVP involve manipulating the timing of behavior verification to create windows where non-compliant behavior goes undetected. The protocol's real-time verification requirements create performance versus security trade-offs where verification latency could be exploited by sophisticated attackers. Implementations MUST establish maximum verification latencies and implement fail-safe mechanisms that restrict agent capabilities when verification cannot be completed within specified time bounds. The certificate-based trust model [RFC5280] underlying trust anchor validation introduces standard PKI vulnerabilities including certificate chain attacks and revocation checking failures. Privacy concerns extend beyond individual agent behavior to aggregate behavioral patterns that could reveal sensitive operational intelligence about agent deployments. The protocol SHOULD implement differential privacy mechanisms and behavioral aggregation techniques that preserve verification effectiveness while limiting information disclosure to verification entities and external observers monitoring attestation traffic patterns. 9. IANA Considerations This document requires IANA to establish and maintain several registries to support the standardized deployment of the Agent Behavior Verification Protocol. These registries are essential for ensuring interoperability across different ABVP implementations and preventing conflicts in namespace usage. The registries MUST be publicly accessible and maintained according to the policies specified in this section. IANA SHALL establish the "ABVP Behavior Verification Schema Registry" to manage standardized schemas for behavior attestation formats and verification proof structures. Registration requests MUST include the schema name, version identifier, JSON Schema definition [RFC8259], cryptographic signature requirements, and designated expert contact information. The registry SHALL use the "Expert Review" policy as defined in RFC 8126, with designated experts required to verify schema completeness, cryptographic soundness, and compatibility with existing ABVP attestation mechanisms. Schema names MUST follow the format "abvp- schema-{category}-{name}" where category indicates the behavior domain (e.g., "communication", "resource-access", "decision- making") and name provides specific identification. The "ABVP Protocol Identifier Registry" SHALL be established to manage unique identifiers for ABVP protocol bindings and integration points with existing agent protocols. Each registered identifier MUST specify the target protocol integration (such as OAuth 2.0 [RFC6749] flows or TLS 1.3 [RFC8446] handshake extensions), the ABVP message format requirements, and backward compatibility constraints. Registration follows the "IETF Review" policy, requiring protocol bindings to demonstrate security analysis and interoperability testing with at least two independent implementations. Protocol identifiers MUST use URI format with the "urn:ietf:params:abvp:" prefix to ensure global uniqueness. IANA SHALL create the "ABVP Enforcement Pillar Registry" to standardize the Five Enforcement Pillars framework referenced in this specification, ensuring consistent implementation across verification systems. Each pillar registration MUST include typed schemas that formally define monitoring requirements, enforcement actions, and compliance measurement criteria. The registry MUST maintain version control for pillar definitions and provide clear migration paths when pillar specifications evolve. This registry SHALL also coordinate with the AIPREF Vocabulary Protocol to ensure alignment between behavior verification vocabularies and AI requirement specifications, preventing semantic conflicts in multi-protocol environments. The "ABVP Trust Anchor Registry" SHALL manage identifiers and metadata for recognized trust anchor sources, including hardware attestation roots, multi-party consensus systems, and certified verification authorities. Trust anchor registrations MUST include cryptographic key information, attestation capability descriptions, supported hardware platforms (such as TPM or TEE implementations), and revocation procedures. The registry SHALL implement the "Expert Review" policy with additional requirements for security audit documentation and demonstrated operational history. All registered trust anchors MUST support the cryptographic requirements specified in RFC 9052 for COSE-based attestation formats and provide clear procedures for key rotation and emergency revocation scenarios. 10. References 10.1. Normative References [RFC 2119] RFC 2119 [RFC 8174] RFC 8174 [RFC 8446] RFC 8446 [RFC 5280] RFC 5280 [RFC 7519] RFC 7519 [RFC 9052] RFC 9052 [draft-birkholz-verifiable-agent-conversations] draft-birkholz-verifiable-agent-conversations [draft-aylward-aiga-1] draft-aylward-aiga-1 10.2. Informative References [RFC 6749] RFC 6749 [RFC 8259] RFC 8259 [RFC 9110] RFC 9110 [draft-aylward-daap-v2] draft-aylward-daap-v2 [draft-chen-agent-decoupled-authorization-model] draft-chen-agent-decoupled-authorization-model [draft-berlinai-vera] draft-berlinai-vera [draft-chen-ai-agent-auth-new-requirements] draft-chen-ai-agent-auth-new-requirements [draft-condrey-rats-witnessd-enrollment] draft-condrey-rats-witnessd-enrollment [draft-drake-email-tpm-attestation] draft-drake-email-tpm-attestation [draft-bastian-jose-dvs] draft-bastian-jose-dvs [draft-bastian-jose-pkdh] draft-bastian-jose-pkdh [draft-barney-caam] draft-barney-caam [draft-altanai-aipref-realtime-protocol-bindings] draft-altanai-aipref-realtime-protocol-bindings Author's Address Generated by IETF Draft Analyzer 2026-03-04