ietf-draft-analyzer/data/reports/generated-drafts/draft-ai-agent-behavior-verification-protocol-00.txt

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].

   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.

   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