TIBET defines a cryptographically-linked provenance chain protocol for tracking interactions between autonomous agents, humans, and automated processes using four-dimensional tokens. The protocol provides hash-chained, signed evidence trails with JSON serialization and integration points for companion agent protocols.

Notable originality in four-dimensional provenance model (content, references, context, intent) and comprehensive cryptographic chaining for multi-agent interactions

Detailed specification with token data model, chain semantics, canonicalization rules, verification procedures, and defined integration points

Minor similarities to general blockchain/audit trail concepts but unique multi-dimensional provenance approach for agent interactions

Active development indicated by integration with multiple companion protocols (JIS, UPIP, RVP, AINS) suggesting coordinated effort

Core AI agent topic addressing critical provenance and accountability challenges in autonomous agent interactions

A2A protocols
AI safety/alignment
Data formats/interop


This draft defines a cryptographically verifiable intent chain to track content provenance through AI agent workflows, complementing the actor chain for delegation provenance. It uses Merkle roots in OAuth tokens to efficiently store tamper-evident logs of content transformations across processing stages.

Notable originality in combining content provenance tracking with cryptographic verification specifically for AI agent workflows, extending beyond traditional delegation models

Defines the protocol mechanism with clear abstract and relationship to companion draft, though implementation details and examples not fully evident from abstract

While building on the companion actor-chain draft, the content provenance focus appears to have minor similarities to existing work rather than significant overlap

Active development evidenced by 2026 date and companion draft relationship, though working group adoption status unclear

Core AI agent topic directly addressing content provenance, tampering, and governance challenges fundamental to autonomous AI systems

Agent identity/auth
Policy/governance
AI safety/alignment


This IETF draft deprecates obsolete key exchange methods (finite field DH and RSA) in TLS/DTLS 1.2, updating multiple RFCs to change recommendations to MUST NOT or SHOULD NOT use these cipher suites. The document focuses solely on TLS 1.2 since earlier versions are already deprecated and TLS 1.3 doesn't use these problematic algorithms.

This is a straightforward deprecation of well-known obsolete cryptographic methods - no novel technical contribution, just necessary housekeeping

Detailed specification with clear normative language updates to existing RFCs, ready for implementation with specific cipher suite deprecations listed

Shares concepts with other TLS security update drafts but addresses a specific set of key exchange methods not covered elsewhere

Strong IETF working group momentum as this addresses widely recognized security issues in deployed TLS implementations

This is purely about TLS cryptographic protocol updates with no connection to AI, agents, or machine learning - complete false positive


This draft proposes an HTTP response header 'AI-Disclosure' to indicate when web content was generated or assisted by AI. The header uses structured field syntax to provide machine-readable metadata about AI involvement for user agents, bots, and archiving systems.

Useful contribution addressing a timely need for AI content transparency, though the concept of disclosure headers is relatively straightforward

Detailed specification with structured field syntax, examples, and clear implementation guidance for HTTP headers

Minor similarities to general content metadata approaches but unique focus on AI disclosure makes it largely distinct

Single revision draft without clear working group adoption or broader community engagement

Directly relevant to AI transparency and human-agent interaction, addressing important disclosure needs for AI-generated content

Human-agent interaction
Policy/governance
Data formats/interop


This draft proposes a lightweight alternative to ANIMA's Autonomic Networking Infrastructure by eliminating the complex ACP component while retaining certificates, GRASP, and BRSKI protocols. The approach uses application-level Autonomic Software Agents with proxying capabilities to achieve most ANI benefits without requiring changes to router/switch control planes.

Useful simplification of existing ANIMA framework, trading some security guarantees for implementation practicality

Defines the architecture and protocol interactions but lacks detailed implementation specifications and examples

Significant overlap with existing ANIMA drafts, essentially proposing a subset/variation of established ANI concepts

Single revision with future date suggests early stage work, unclear community engagement within ANIMA working group

Directly relevant to autonomous network operations and distributed automation agents, core networking AI topic

Autonomous netops
Agent discovery/reg
A2A protocols


This draft specifies how to transport Model Context Protocol (MCP) messages over Media over QUIC Transport (MOQT), enabling efficient publish-subscribe delivery for AI language model integrations with external data sources. It defines the mapping between MCP messages and MOQT objects along with session establishment procedures.

Incremental work adapting existing MCP to run over MOQT transport - straightforward protocol layering

Defines complete protocol mapping and procedures but lacks implementation details and examples

Shares transport concepts with other QUIC-based drafts and relates to MCP specifications

Single revision with 2026 date suggests early stage without demonstrated community engagement

Directly relevant to AI agents as MCP is specifically designed for language model application integration


This draft defines an EAT profile for remotely attesting autonomous AI agents, specifying claims for model integrity, training data provenance, and inference policies. It includes 5G/6G extensions and uses CWT/JWT encoding within the IETF RATS architecture.

Notable originality in applying remote attestation specifically to AI agents with comprehensive claims covering model parameters, training provenance, and inference constraints

Early sketch with basic profile definition but lacks detailed implementation specifics, test vectors, or worked examples

Minor similarities to general EAT work but unique AI-specific application with novel claims structure

Single revision with no evidence of working group adoption or broader community engagement

Core AI agent topic addressing critical trust and attestation challenges for autonomous AI systems across domains

Agent identity/auth
AI safety/alignment
Data formats/interop


CoSERV defines a CBOR-based query language for discovering and retrieving endorsements and reference values in remote attestation systems. The draft specifies structured formats using CDDL to enable efficient interoperability between verifiers and endorsement providers.

incremental extension of existing RATS architecture with standard query mechanisms

detailed 69-page specification with CDDL definitions and CBOR serialization ready for implementation

builds directly on RATS architecture and shares attestation concepts with related security drafts

IETF working group draft with substantial page count indicating active development

focuses on attestation infrastructure rather than AI agents, though could support agent verification scenarios

Agent identity/auth
Data formats/interop


This draft proposes an automatic congestion relief mechanism using intelligent traffic analysis and dynamic regulation for network self-healing. It focuses on responding to congestion from fiber optic failures through real-time intelligent adaptation.

Incremental application of existing AI traffic management concepts to congestion relief

Early sketch with abstract concepts but lacks detailed protocol specification

Significant overlap with existing traffic engineering and AI-based network management approaches

Single revision with no evidence of working group interest or community engagement

Partially relevant as it applies AI for autonomous network operations but focuses narrowly on congestion


This draft defines an architecture for LLM-based agents to autonomously discover and interact with IoT devices using CoAP and hypermedia patterns. The approach enables agents to decompose high-level user intents into device operations without pre-configured knowledge, relying on in-band discovery and semantic metadata.

Notable originality in applying LLM agents to constrained IoT environments with hypermedia-driven autonomous discovery - bridges AI agents with resource-constrained networking in a novel way

Defines clear protocol mechanisms and architecture with CoAP/CoRE integration, though implementation details and concrete examples could be more extensive for full specification readiness

Minor similarities to general IoT discovery work, but the combination of LLM agents with constrained RESTful environments appears largely unique

Single revision draft with future 2026 date suggests early stage development without demonstrated working group traction yet

Core AI agent topic directly addressing autonomous operation in networked environments - exemplifies intelligent agents making independent decisions in constrained systems

Autonomous netops
Agent discovery/reg
Data formats/interop


This draft specifies the attestation token format for Arm's Confidential Compute Architecture (CCA), defining a profile of Entity Attestation Token (EAT) for trustworthiness assessment. It describes the claims structure, serialization, and cryptographic protection for CCA-compliant systems.

Incremental work creating a hardware-specific profile of existing EAT standard

Detailed specification with clear structure and semantics for implementation

Shares concepts with EAT and other attestation token specifications

Active development as informational draft for Arm architecture interoperability

Tangentially related to AI/agents through confidential computing security foundations


VCAP specifies a protocol for autonomous AI agents to conduct verified financial transactions using cryptographic proof of work delivery and escrow mechanisms. It defines message formats, state machines, and verification contracts to enable trustless commerce between agents with automatic payment settlement.

Novel approach to AI agent commerce with cryptographic verification - no existing standards address autonomous agent financial transactions with proof-of-work delivery

Detailed specification with defined message formats, state machines, cryptographic bindings, and callback contracts - appears implementation-ready

Unique focus on verified commerce for AI agents - no significant overlap with existing IETF work on agent protocols or commerce standards

Single draft submission with no clear working group adoption or community feedback yet

Directly addresses core AI agent infrastructure need for trustless financial transactions and automated commerce verification

A2A protocols
Agent identity/auth
Data formats/interop


This draft defines X.509 certificate extensions to embed attestation results, primarily for CSR attestation where claims about device/system trustworthiness are included in certificates. It enables CAs to appraise evidence and embed attestation results for relying parties to evaluate trustworthiness consistently.

Useful contribution applying established attestation concepts to X.509 certificates, though the core idea of embedding attestation data in certificates is somewhat expected

Recent draft with limited revision history, unclear working group adoption status or broader community engagement

Shares concepts with existing attestation and PKI work, particularly RATS architecture and X.509 extension mechanisms, but creates a specific bridge between these domains

Tangentially related to AI/agents as attestation could apply to AI systems, but primarily focuses on general device/system attestation rather than AI-specific concerns


This draft proposes a Semantic Routing Architecture that uses application-layer semantics like intent vectors and trust scores to intelligently route communications between AI agents, moving beyond traditional IP routing. The architecture aims to transform networks from passive transport to active collaboration substrates for multi-agent coordination.

Notable originality in applying semantic-driven routing specifically to AI agent communication, moving beyond traditional network routing paradigms

Early sketch level - introduces concepts but lacks detailed protocol specifications, implementation details, or concrete examples

Minor similarities to service mesh and intent-based networking concepts, but unique application to AI agent semantics

Single revision with future date suggests early stage development without demonstrated community engagement

Core AI agent topic addressing fundamental infrastructure needs for multi-agent communication and coordination

A2A protocols
Agent discovery/reg
Autonomous netops


ARKG enables delegation of asymmetric public key generation without exposing private keys, supporting applications like pseudonymous keys for user agents and ephemeral keys for enhanced forward secrecy. The draft provides a generic algorithm specification, instantiation formulae, and concrete implementations.

Useful cryptographic contribution that addresses a real need in distributed systems, though builds on established asymmetric cryptography concepts

Detailed specification with abstract algorithm, concrete instantiation formulae, and fully specified instances ready for implementation

While related to general key management work, the specific ARKG approach and application to agent scenarios appears relatively unique

Appears to be early stage work without clear working group adoption or broader community engagement yet

Directly relevant to AI agents needing pseudonymous identities, secure messaging, and paired authentication devices without shared private keys


This draft proposes enhancing EAP-AKA' Forward Secrecy with hybrid post-quantum cryptography to protect against future quantum computer threats. It aims to replace the traditional ECDHE key exchange with quantum-resistant algorithms while maintaining backward compatibility.

Incremental application of established PQ/T hybrid approach to existing EAP-AKA' protocol - straightforward quantum-resistant upgrade

Early sketch stage - provides motivation and general approach but lacks detailed protocol specification or implementation guidance

Significant conceptual overlap with other post-quantum authentication protocols and hybrid cryptography drafts in IETF

Single draft version addressing timely quantum-readiness concerns in mobile authentication, moderate development activity expected

Pure cryptographic protocol enhancement for mobile network authentication - no AI or agent-related functionality


This draft addresses trust and security considerations for structured email, providing recommendations for message user agents on handling structured data in email messages. It focuses on security implications when emails contain machine-readable structured content that could be processed by automated systems.

Incremental work addressing known security concerns around structured data in email

Early stage draft with basic problem outline but limited technical detail

Shares concepts with email security and structured data standards

Single draft with no clear working group adoption

Partially relevant as structured email could enable agent communication but not explicitly focused on AI agents

A2A protocols
Data formats/interop
Policy/governance


This IETF draft defines hybrid key exchange methods combining quantum-resistant ML-KEM with traditional ECDH for SSH transport protocol. It addresses post-quantum cryptography readiness by enabling dual protection against both classical and quantum attacks.

Incremental work applying established PQ/T hybrid approach to SSH, following patterns from TLS implementations

Detailed specification with concrete protocol definitions, algorithm identifiers, and wire format specifications

Shares hybrid PQ/T concepts with TLS drafts and other SSH cryptographic extensions but SSH-specific implementation

Strong working group adoption with clear timeline to 2026, addressing urgent post-quantum transition needs

Pure cryptographic protocol specification with no AI or agent-related functionality


This draft specifies how to use the EDHOC authenticated key exchange protocol over CoAP to establish OSCORE security contexts for constrained environments. It includes optimizations to combine EDHOC execution with the first OSCORE transaction to reduce round trips.

Incremental work combining existing protocols (EDHOC, CoAP, OSCORE) with some optimization contributions

Detailed specification with concrete mechanisms, message flows, and implementation guidance

Builds on established CoAP/OSCORE work but addresses specific integration aspects

IETF working group draft suggesting active development and community interest

This is about constrained device security protocols, not AI/agents - appears to be a false positive


This draft defines a mechanism for content creators to signal their preferences about how automated systems should consume their content via HTTP headers. It updates RFC 9309 to include usage preferences as part of content acquisition protocols.

Incremental extension of existing HTTP preference mechanisms to address AI content consumption - useful but builds on established patterns

Defines a protocol mechanism with clear structure, though would benefit from more detailed examples and implementation guidance

Shares concepts with robots.txt, content licensing mechanisms, and other HTTP preference frameworks

Single revision draft with limited visible community engagement or working group adoption

Directly addresses the important issue of AI systems respecting content creator preferences during automated content consumption


This draft proposes using large language models for network traffic classification and resource allocation mapping. The framework includes pre-training on packet capture data to generate traffic representations and dynamic mapping for resource allocation strategies.

Useful contribution applying LLMs to traffic analysis, though LLM-based network management is an established research direction

Early sketch level - lacks detailed protocol specifications, implementation details, or concrete examples of the proposed framework

Significant overlap with existing ML-based traffic classification and QoS management approaches, though LLM application adds some differentiation

Future-dated draft (2026) with no evidence of current development activity or community engagement

Directly relevant as it applies AI/ML techniques to network operations, representing autonomous network management capabilities


```json
{
  "s": "Defines a standardized protocol for AI agents to exchange context information with each other. Proposes message formats and communication mechanisms for inter-agent context sharing.",
  "n": 3,
  "nn": "Addresses a recognized need for agent interoperability but builds on established messaging concepts",
  "m": 3,
  "mn": "8 pages suggests defined protocol structure but may lack comprehensive implementation details",
  "o": 3,
  "on": "Likely shares messaging and protocol concepts with other agent communication proposals",
  "mo": 2,
  "mon": "Recent draft date but no indication of working group adoption or broader community engagement",
  "r": 5,
  "rn": "Directly addresses core challenge of AI agent communication and context sharing",
  "c": ["A2A protocols", "Data formats/interop"]
}
```


Proposes a vocabulary for content creators to declare preferences about how search engines and AI crawlers can use their collected content. The draft defines structured declarations to express restrictions or permissions for content usage by automated systems.

Incremental extension of existing robots.txt concepts to AI/ML context

Early sketch with basic vocabulary concepts but lacks detailed specification

Shares concepts with existing web crawling standards and emerging AI content usage frameworks

Single revision with uncertain adoption trajectory

Directly addresses current concerns about AI training data collection and usage rights


```json
{
  "s": "This draft outlines use cases for AI agents in 6G networks, building on 3GPP technical reports and focusing on operator requirements. It appears to be a requirements and use case document rather than a technical specification.",
  "n": 2,
  "nn": "Incremental work that largely references existing 3GPP studies on 6G use cases, with limited novel contributions beyond organizing AI agent scenarios for network operators",
  "m": 2,
  "mn": "Early stage document that presents use cases and requirements but lacks detailed technical mechanisms, protocols, or implementation guidance",
  "o": 4,
  "on": "Significant overlap with 3GPP TR 22.870 and other 6G network AI integration work, as explicitly acknowledged in the abstract",
  "mo": 1,
  "mon": "Single draft submission with no evidence of working group adoption or community engagement in IETF context",
  "r": 3,
  "rn": "Partially relevant as it discusses AI agents in network context, but focuses more on telecommunications use cases than general AI agent protocols or interoperability",
  "c": ["Autonomous netops", "Policy/governance", "Other AI/agent"]
}
```


This draft proposes a JWT-based framework for authorizing AI agent operations through structured request and confirmation phases. The system aims to prevent unauthorized agent actions by requiring cryptographic verification of user intent before agents can execute operations.

Useful contribution applying existing JWT mechanisms to the emerging problem of AI agent authorization, though the core concept of structured authorization tokens is well-established

Detailed specification with clear two-phase protocol definition, JWT structure, and operational procedures, appears implementation-ready

Minor conceptual similarities to general authorization frameworks but specific application to AI agent operations is relatively unique

Single revision with 2026 date suggests early stage development, no evident working group adoption yet

Directly addresses core AI agent security concerns around unauthorized operations and verifiable delegation of authority

Agent identity/auth
Human-agent interaction
AI safety/alignment


This draft defines a protocol for DLT systems to project views of virtual assets to external parties with access control and verification capabilities. It enables DLT-neutral addressing and retrieval of asset states, locks, and computed functions across blockchain boundaries.

Useful contribution addressing asset interoperability across DLT systems, though builds on established blockchain interop concepts

Defines protocol mechanisms and view concepts but appears to lack detailed implementation specifics and examples

Shares concepts with blockchain interoperability and cross-chain asset transfer protocols in the space

Single revision with future date suggests early stage development without established community engagement

Focuses on blockchain asset transfer rather than AI agents, though external parties could theoretically include automated agents


Proposes AINP, a semantic communication protocol for AI agents that replaces traditional network routing with capability-based discovery and intent exchange. The protocol enables autonomous agent negotiation and structured communication with cryptographic security.

Notable originality in replacing fundamental networking primitives (location-based routing, byte streams) with semantic equivalents for AI agent communication

Defines core protocol mechanisms and semantic routing concepts but likely needs more detailed specification and examples for implementation

While agent communication exists, the semantic routing and intent-based approach appears relatively unique in the networking protocol space

Single revision of a new draft without clear working group adoption or community engagement signals

Directly addresses core AI agent networking needs with semantic communication, capability discovery, and autonomous negotiation

A2A protocols
Agent discovery/reg
Agent identity/auth


This draft analyzes security threats in intent-based agentic systems where high-level user goals are translated into executable actions across multiple entities. It provides a reference model for understanding attack surfaces like privilege escalation and intent drift in multi-hop agent processing chains.

Useful contribution addressing emerging security concerns in agent systems, though intent-based computing concepts exist in other domains

Early sketch providing threat analysis and requirements but lacks concrete protocols or detailed security mechanisms

Some conceptual overlap with general agent security work but specifically focused on intent-based request processing chains

Single revision draft with no clear working group engagement or community discussion visible

Directly addresses core security challenges in AI agent systems, highly relevant to emerging agentic architectures

AI safety/alignment
Agent identity/auth
Policy/governance


This draft presents a problem statement for standardizing zero trust interoperability protocols in IETF, arguing that existing high-level architectural guidance lacks the open, interoperable frameworks needed for multi-vendor zero trust environments. It outlines use cases and discusses potential scope for IETF standardization work versus other standards bodies.

Incremental work identifying known gaps in zero trust standardization without proposing novel technical approaches

Pure problem statement document with no technical solutions, protocols, or mechanisms defined

Significant conceptual overlap with existing zero trust architecture work and various IETF security protocols, though focused on interoperability gaps

Single revision draft with numerous typos suggesting limited review and development activity

Only tangentially related to AI/agents through brief mention of 'intelligent agents' as one use case, primarily focused on general zero trust security


ADL proposes a JSON-based standard for describing AI agents including their capabilities, tools, permissions, and security requirements. The draft defines the structure and semantics for agent description documents to enable discovery, interoperability, and lifecycle management across platforms.

Incremental approach applying standard metadata description patterns to AI agents - useful but not particularly novel

Detailed specification with clear structure definitions, semantics, and media type registration - appears implementation-ready

Shares concepts with other agent description and service discovery formats, but specific to AI agents

Single draft with no clear working group adoption or community feedback visible

Directly addresses core AI agent interoperability and standardization needs

Data formats/interop
Agent discovery/reg
Agent identity/auth


Proposes a cryptographic protocol for AI regulatory compliance verification using zero-knowledge proofs and multi-party computation. Organizations can prove compliance with regulations like the EU AI Act without revealing proprietary model details.

Novel application of established cryptographic primitives to AI regulatory compliance, addressing a genuine gap in privacy-preserving compliance verification

Defines specific protocol components and cryptographic mechanisms but lacks detailed implementation specifics and test vectors for a 5-page draft

While using established cryptographic techniques, the specific application to AI compliance verification appears relatively unique

Single revision with no clear indication of working group adoption or broader community engagement

Directly addresses AI governance and compliance verification, highly relevant to AI systems regulation and deployment

Policy/governance
AI safety/alignment
Agent identity/auth


SOUTH defines a stochastic authorization protocol that allows servers to make probabilistic access control decisions based on uncertainty, context, and load conditions for users, services, and autonomous agents. The protocol is transport-independent and integrates with existing authentication mechanisms like OAuth and mTLS.

Notable originality in introducing probabilistic authorization decisions - most authorization systems are deterministic, while this explicitly incorporates uncertainty and stochastic outcomes

Detailed 44-page specification with defined protocol objects, decision semantics, HTTP binding, and examples - appears implementation-ready

Minor similarities to existing authorization frameworks but the stochastic decision-making approach is relatively unique in the authorization space

Single revision from November 2025 with no apparent working group adoption or community momentum yet

Directly relevant to AI agents as it specifically addresses authorization for autonomous agents and incorporates uncertainty handling which is crucial for agent systems


This draft defines the Internet of Agents Protocol (IoA) for enabling heterogeneous agent collaboration through dynamic team formation, adaptive coordination, and structured communication. The protocol uses a layered architecture with extensible messaging to support decentralized deployment across devices and interoperability with existing frameworks.

Useful contribution addressing multi-agent coordination, though builds on established distributed systems and agent collaboration concepts

Early sketch stage - defines general architecture and concepts but lacks detailed protocol specifications, message formats, and implementation details

Shares concepts with existing multi-agent system protocols and distributed coordination mechanisms, but focuses specifically on heterogeneous agent collaboration

Single revision draft with no clear working group adoption or community engagement visible

Core AI agent topic directly addressing fundamental challenge of multi-agent coordination and collaboration in distributed intelligent systems

A2A protocols
Agent discovery/reg
Data formats/interop


SVTP proposes a protocol for establishing verifiable identity and trust for autonomous machines including AI agents and physical systems like robots and vehicles. It defines SVTP-DID identifiers and Protocol Seal mechanisms to enable secure machine-to-machine interactions with liability containment.

Novel integration of DID-based identity with physical autonomous systems and liability containment - goes beyond typical identity frameworks

Early specification stage with key concepts defined but lacking detailed protocol mechanics, message formats, and implementation guidance

Shares DID concepts with W3C standards and overlaps with some IoT trust frameworks, but unique autonomous machine focus

Single draft version with no indication of working group adoption or broader community engagement

Directly addresses AI agent identity and autonomous system trust - core infrastructure need for agent ecosystems

Agent identity/auth
A2A protocols
Policy/governance


This draft defines how to transport the Model Context Protocol (MCP) over Media over QUIC Transport (MOQT), enabling efficient delivery of AI agent capabilities including tools, resources, and composed "Agent Skills". The specification focuses on mapping MCP primitives to MOQT objects with appropriate prioritization and delivery guarantees for scalable AI agent deployments.

Useful contribution combining two emerging protocols (MCP and MOQT) in a natural way that leverages MOQT's streaming capabilities for AI agent communication

Detailed specification with clear mapping procedures, priority management, and relay architectures, though implementation examples could be stronger

Minor overlap with general agent communication protocols but unique in its specific MCP-over-MOQT approach

Single revision from 2026 with no clear working group adoption signals

Directly addresses core AI agent infrastructure needs for efficient communication and skill delivery at scale

A2A protocols
Data formats/interop
Model serving/inference


This draft proposes a DLT-neutral protocol for requesting and sharing asset views across blockchain networks through gateway nodes. The protocol enables external agents to request views using global addresses while masking internal DLT complexities.

Useful contribution addressing cross-DLT interoperability, though building on established gateway patterns

Defines protocol mechanisms and view concepts but lacks detailed message formats and implementation specifics

Shares concepts with existing blockchain interoperability and gateway protocols but focuses specifically on view sharing

Single revision with unclear working group status or broader community engagement

Tangentially related through external agents requesting views, but primarily focused on blockchain interoperability rather than AI agents


This draft proposes an intelligent protection optimization system for IoT networks using information-centric networking principles. The system aims to provide better content privacy protection through intelligent mechanisms in naming/parsing, data exchange, and data caching without additional costs.

Incremental work combining existing ICN concepts with basic IoT security considerations, lacks novel technical insights

Early sketch with high-level concepts but missing detailed protocol specifications, implementation details, and concrete mechanisms

Significant overlap with existing ICN security proposals and IoT protection schemes, particularly in caching and naming security

Single revision with minimal technical depth, no indication of working group interest or community engagement

Partially relevant as it mentions intelligent protection systems but lacks clear AI/ML mechanisms or agent-based approaches


This draft defines mechanisms for supplying nonces to end entities for freshness verification of attestation evidence in certificate signing requests across CMP, EST, and CMC protocols. It addresses the timing coordination needed between certificate authorities and attestation providers to ensure evidence freshness during certificate enrollment.

Incremental extension applying existing nonce-based freshness concepts to certificate management protocols

Detailed specification with concrete protocol extensions and examples for multiple certificate management frameworks

Shares attestation freshness concepts with remote attestation standards but applies them specifically to certificate enrollment

IETF LAMPS working group adoption with active development addressing real deployment needs

Tangentially related through attestation mechanisms but focused on certificate management rather than AI agents


This framework document identifies communication protocols needed for AI agents to interact with users, APIs, and other agents over the Internet. It surveys existing work like MCP and A2A protocols while establishing requirements for potential IETF standardization in AI agent communications.

Framework approach is incremental, cataloging existing protocols rather than proposing novel solutions

Early framework sketch with use cases but lacks detailed protocol specifications or concrete mechanisms

Shares conceptual space with existing A2A and MCP work, though attempts to provide broader framework perspective

Single revision from individual contributor, no evidence of working group interest or broader community engagement

Directly addresses core AI agent communication protocols and Internet-scale agent interactions

A2A protocols
Agent discovery/reg
Data formats/interop
Human-agent interaction


This IETF draft specifies methods for transforming different evidence formats (DiceTcbInfo, concise evidence, SPDM measurements) into a unified CoRIM representation for remote attestation procedures. It addresses the challenge of verifiers needing to handle multiple evidence encoding formats by providing standardized transformation methods.

Incremental work that applies existing CoRIM framework to additional evidence formats - useful but not groundbreaking

Detailed specification with concrete transformation methods for specific evidence structures, appears implementation-ready

Builds directly on CoRIM and RATS architecture but focuses on specific transformation aspect not fully covered elsewhere

IETF working group draft with clear progression and active development in established RATS framework

Remote attestation has some relevance to AI agent trust and verification but this is primarily a general security mechanism


ACCP defines a semantic encoding protocol for AI agent communication that claims 60-90% token reduction compared to natural language or JSON messaging. The protocol includes compact message formats, intent ontology, and state compression designed to complement existing agent protocols like MCP and A2A.

Useful contribution addressing real efficiency concerns in agent communication, though compression and semantic encoding are established techniques

Defines protocol structure and compression strategy but appears to lack detailed implementation specifics and test vectors

Shares conceptual space with MCP and A2A protocols but focuses specifically on compression and efficiency rather than duplicating functionality

Single revision with future date suggests early stage, no evidence of working group adoption or community engagement yet

Directly addresses core AI agent communication efficiency, highly relevant to current agent infrastructure development


ATTP defines a secure HTTP-based protocol for AI agent-to-server communication with mandatory cryptographic identity verification, digital signatures, and audit trails. The protocol adds security headers to HTTP requests/responses and requires Agent Passport JWT credentials for all interactions.

Incremental security extension to HTTP for agent communication, building on established JWT/ECDSA patterns

Detailed specification with defined headers, security requirements, and clear protocol mechanics

Significant conceptual overlap with existing secure HTTP extensions and agent authentication schemes

Single revision draft with no evident working group adoption or community feedback

Directly addresses AI agent security needs with practical protocol design for agent-server communication


CB4A specifies a credential brokering architecture for AI agents that eliminates long-lived credential storage by agents, instead providing short-lived proxy credentials through a policy-separated broker system. The draft builds on SPIFFE/SPIRE and DPoP to address credential sprawl risks in agentic AI deployments.

Notable originality in applying credential brokering specifically to AI agent architectures with comprehensive threat modeling for agentic scenarios

Detailed specification with three proxy models, tiered approval framework, and comprehensive threat analysis with mitigations

Minor similarities to general credential management approaches but unique focus on AI agent-specific challenges and architecture

Single author draft with no clear working group adoption signals, though addresses emerging AI agent security concerns

Directly addresses core AI agent security challenge of credential management and sprawl prevention in multi-service agent deployments

Agent identity/auth
AI safety/alignment
Policy/governance


This draft specifies FAF, a YAML-based format for representing software project context that AI development tools can consume. It aims to standardize how project architecture, conventions, and dependencies are shared across different AI agents in multi-agent development environments.

Incremental work applying existing structured format (YAML) to AI tooling context - useful but not particularly novel

Defines a specific format with IANA registration mentioned, suggesting concrete specification though implementation details may be limited

Shares concepts with other data format and interoperability efforts for AI systems, though specific to development tooling context

Single revision draft with IANA registration claim but no clear evidence of broader community engagement or working group adoption

Directly addresses AI agent interoperability in software development, which is highly relevant to multi-agent systems and AI tooling

Data formats/interop
Human-agent interaction


Proposes an architecture combining Network Digital Twins with Agentic AI for intent-based network operations, allowing risk-free testing and optimization of network changes. Describes how existing technologies can be integrated to enable AI-driven autonomous network management.

Incremental combination of existing NDT and Agentic AI concepts without novel architectural insights

Early architectural sketch lacking detailed protocols, interfaces, or implementation specifics

Significant conceptual overlap with existing intent-based networking and digital twin literature

Single revision from research group with uncertain community traction

Directly relevant to AI agents in networking with focus on autonomous operations and digital twins

Autonomous netops
Human-agent interaction


VERA proposes a zero-trust architecture for AI agent security with five enforcement pillars, formal security properties, and cryptographic proof-based autonomy earning. The draft addresses critical risks from compromised AI agents including data exfiltration and unauthorized transactions.

Notable originality in combining zero-trust principles with agent-specific threat models and cryptographic proof-based autonomy earning

Defines structured architecture with typed schemas and formal properties, but lacks detailed implementation specifics

Minor conceptual overlap with general zero-trust frameworks but novel application to AI agents

Single revision with recent date, no indication of working group adoption yet

Core AI agent security topic addressing fundamental runtime enforcement challenges


PAIT defines a wire protocol for token-level provenance tracking in generative AI systems, including agent identity tokens, provenance manifests, and trust telemetry. The protocol aims to address AI transparency regulations by providing verifiable attribution for AI-generated content at sub-document granularity.

Notable originality in defining token-level provenance attribution with cryptographic binding to training corpus segments - addresses a specific gap in AI transparency not covered by existing protocols

Defines core protocol components and state machine but lacks detailed implementation specifics, message formats, and concrete examples needed for full implementation

Minor conceptual similarities to general provenance and identity frameworks, but the token-level AI inference focus and specific regulatory compliance angle are distinct

Single revision draft with no clear working group adoption or community feedback visible - appears to be early-stage individual contribution

Directly addresses core AI transparency and accountability challenges with practical protocol mechanisms for provenance tracking in generative AI systems

Agent identity/auth
Policy/governance
Model serving/inference
Data formats/interop


Proposes AIGA protocol for governing autonomous AI agents through tiered risk-based oversight, immutable kernel architecture, and federated authority networks. Uses economic incentives, quarantine mechanisms, and multi-layered security for high-risk agent scenarios.

Novel integration of TEE attestation, federated governance, and economic incentive alignment specifically for autonomous AI agents represents notable originality in the governance space

Single draft from 2026 with no clear working group adoption or community discussion visible, suggesting early-stage individual contribution

While governance concepts exist broadly, the specific combination of AI agent oversight mechanisms and federated authority approach shows minimal overlap with existing IETF work

Directly addresses core challenges in autonomous AI agent governance and accountability, which is central to safe AI deployment

Policy/governance
Agent identity/auth
AI safety/alignment


This draft defines an RDAP profile for querying registration data about AI agent identifiers, allowing lookup of agent metadata like IPv6 locators, gateways, public keys, and operational state. It reuses the existing RDAP protocol structure but extends it with new object classes specific to agent identifier management.

Useful application of existing RDAP protocol to agent identifiers - not groundbreaking but addresses a real need for agent metadata lookup

Detailed specification with defined object classes, extensions, and query patterns - appears implementation-ready with good technical depth

Builds on RDAP but applies it to a new domain - minimal overlap with existing agent-related work

Single revision from 2026 (future date suggests early stage) - no clear WG adoption signals yet

Directly addresses agent infrastructure needs for identifier resolution and metadata access - core component for agent deployment

Agent identity/auth
Agent discovery/reg
Data formats/interop


This draft proposes using Model Context Protocol (MCP) to enable natural language-driven network measurement by treating network devices as MCP servers and controllers/management systems as MCP clients. The framework aims to provide AI-assisted network monitoring, fault diagnosis, and automated measurement workflows through standardized MCP communication.

Useful application of MCP to network measurement domain, though conceptually straightforward adaptation of existing protocol

Early stage draft with basic framework description but lacking detailed protocol specifications and implementation guidance

Some conceptual overlap with network automation approaches but MCP application to measurement appears relatively unique

Single draft submission with no evidence of working group adoption or broader community engagement

Directly relevant as it applies AI agent protocols (MCP) to enable natural language network operations and intelligent automation

A2A protocols
Autonomous netops
Human-agent interaction


This draft proposes using the Model Context Protocol (MCP) to enable intent-based network troubleshooting by mapping network devices as MCP servers and controllers as MCP clients. It aims to provide conversational, automated network management through LLM integration without requiring new protocols.

Useful adaptation of existing MCP protocol to network management domain, though the core concept of applying LLMs to network troubleshooting is well-established

Early-stage proposal with basic problem statement and high-level mapping concepts, lacks detailed protocol specifications or implementation examples

Shares general concepts with other network automation and intent-based networking approaches, though specific MCP application appears unique

Single revision from October 2025, no evidence of working group adoption or broader community engagement yet

Directly relevant to AI agents in networking, combining LLM capabilities with network operations through structured protocol interactions

Autonomous netops
Data formats/interop
Human-agent interaction


This draft outlines security requirements for AI agents across their operational lifecycle including provisioning, registration, discovery, and access control. It appears to be an early attempt at standardizing security frameworks for autonomous agent systems.

Addresses growing need for AI agent security standards, though security requirements analysis is a well-established approach

At 14 pages appears to be early stage requirements gathering rather than detailed specifications or protocols

Security requirements for distributed systems exist but AI agent-specific security considerations are relatively unexplored in IETF

Single draft submission with no clear working group adoption or community feedback visible

Directly addresses core AI agent security concerns across multiple operational phases - highly relevant to agent infrastructure

Agent identity/auth
Policy/governance
Agent discovery/reg
A2A protocols


This draft analyzes the problems and gaps in applying AI agents to mobile core networks. It identifies challenges in integrating autonomous agents into 5G/6G core network operations and management.

Incremental application of existing agent concepts to mobile networks

Only provides problem statement and gap analysis without proposed solutions

Shares concepts with other network automation and AI-enabled networking drafts

Single revision with no clear follow-up activity

Directly addresses AI agents in network infrastructure context


This draft proposes AGENTS.TXT, a plaintext policy file protocol that allows websites to specify access rules for automated clients, bots, and crawlers. It includes hash verification, directive specifications, and mandatory restrictive behavior for malformed files to prevent unintended access.

Incremental extension of robots.txt concept for broader automated clients

Defines protocol structure with directives and verification but lacks implementation details

Significant conceptual overlap with robots.txt and existing web crawling standards

Single revision draft with no clear working group involvement

Directly relevant to AI agents and automated systems accessing web resources

Policy/governance
A2A protocols
Data formats/interop


This draft identifies authentication and authorization challenges posed by autonomous AI agents whose dynamic behavior and delegation relationships don't fit traditional identity-based security models. It proposes new requirements for managing dynamic agent behavior rather than just verifying static identities.

Notable originality in recognizing that AI agent autonomy fundamentally breaks existing auth models designed for predictable human/software entities

Early sketch that identifies problems and high-level requirements but lacks concrete protocols or detailed mechanisms

Minor similarities to general identity management work but addresses unique AI agent characteristics not covered elsewhere

Single revision with no evident working group activity or community engagement yet

Core AI agent topic directly addressing fundamental security infrastructure needed for autonomous agent deployment


This draft proposes using generative AI to create a flexible, natural language-based communication protocol that could replace the multitude of rigid APIs currently used for agent-to-agent interactions. The authors argue this approach would solve interoperability challenges and provide a single uniform API for agent communications including registration, discovery, telemetry and debugging.

Using natural language as a universal API abstraction layer for agent communication is notably original, though builds on established concepts of AI-mediated interfaces

Only presents the problem statement and high-level concept without any protocol definition, mechanisms, or technical details

While agent communication is covered by other drafts, the natural language API approach appears largely unique in the IETF space

Appears to be an early single submission without indication of working group interest or community engagement

Directly addresses core AI agent communication challenges and proposes AI-native solutions for agent interoperability

A2A protocols
Data formats/interop
Agent discovery/reg


This draft proposes extending SRv6 behaviors to enable flow control in WANs for AI workloads using RDMA, specifically adapting datacenter PFC mechanisms for wide area networks. The approach leverages SRv6 segment lists to identify upstream nodes for congestion notification delivery.

Useful adaptation of datacenter flow control to WAN context for AI traffic, though builds heavily on existing PFC and SRv6 technologies

Early sketch with basic concept and example workflow, but lacks detailed protocol specification, message formats, and implementation details

Shares concepts with existing SRv6 extensions and datacenter flow control mechanisms, but specific WAN application appears less explored

Single revision from 2026 with no indication of working group activity or broader community engagement

Directly addresses AI infrastructure needs for distributed training and inference across datacenters, targeting specific RDMA over WAN requirements


Proposes Internet 2.0 as an AI-native web extension with HTTP+AI protocol, Model Resolution Network for AI service discovery, and AI-aware browsers. Introduces intent-based routing and treats AI models as first-class network entities with distributed discovery mechanisms.

Notable architectural vision combining AI-native protocols, intent-based routing, and distributed model discovery in a cohesive framework

Early conceptual sketch with basic component definitions but lacks detailed protocol specifications or implementation guidance

Some conceptual overlap with AI service discovery and HTTP extensions but unique in comprehensive Internet 2.0 architectural approach

Single revision draft with no clear working group activity or community engagement signals

Directly addresses core AI agent infrastructure including discovery, protocols, and distributed AI interaction mechanisms

A2A protocols
Agent discovery/reg
Model serving/inference


Defines AIIP, a dedicated protocol for autonomous AI systems to execute real-world actions through authenticated channels. Uses a resolve-invoke-execute-receipt pattern with cryptographic verification of execution outcomes.

Novel dedicated protocol architecture for AI agent execution with cryptographic receipts - goes beyond existing approaches by defining execution boundary

Early architectural sketch without detailed protocol mechanics, message formats, or concrete examples

Some conceptual overlap with agent protocols but unique focus on execution plane and cryptographic verification

Single draft submission with no visible community engagement or working group activity

Directly addresses core AI agent infrastructure - autonomous execution, verification, and real-world action delegation


This draft extends the Agent Transfer Protocol (AGTP) to address the merchant identity gap by defining merchant verification mechanisms parallel to existing agent identity protocols. It introduces Merchant Manifest Documents, trust tiers, and protocol integration points to enable mutual verification between agents and merchants in agentic commerce transactions.

Incremental extension applying existing AGTP identity concepts to the merchant side, filling an obvious gap but using established patterns

Detailed specification with concrete mechanisms, data structures, protocol integration points, and specific status codes, appears implementation-ready

Heavy structural dependence on base AGTP protocol and direct parallel to Agent Manifest concepts, essentially mirroring existing agent identity mechanisms

Active development evidenced by version progression (v00 to v01) with alignment to AGTP v05, but unclear broader community engagement

Core AI agent infrastructure addressing fundamental trust and identity verification in autonomous commerce transactions

A2A protocols
Agent identity/auth
Policy/governance


This draft proposes applying existing authentication standards like WIMSE and OAuth 2.0 to AI agent interactions rather than creating new protocols. It aims to provide a framework for agent authentication and authorization while identifying gaps for future standardization.

Incremental application of existing OAuth/WIMSE standards to AI agents without fundamental innovations

Early framework sketch that identifies approach but lacks detailed protocol specifications

Significant conceptual overlap with existing OAuth, WIMSE, and general identity management work

Active development indicated by recent 2026 date and practical focus on standards application

Directly addresses core AI agent authentication needs, highly relevant to agent deployment


Defines EAT Attestation Result (EAR) message format for verifiers to encode appraisal results of attester evidence with trustworthiness vectors. Supports both simple and composite devices with multiple attesters, using CWT or JWT serialization.

Useful standardization of attestation result format with trustworthiness vectors, building on existing EAT framework

Detailed specification at 27 pages with defined message formats, trustworthiness vectors, and serialization options

Builds on EAT framework and shares concepts with other attestation/trust measurement standards

IETF working group draft with specific publication target date indicating active development

Attestation and trust measurement relevant for AI agent verification and trustworthiness assessment

Agent identity/auth
Data formats/interop


This draft specifies procedures and optimizations for distributing context information among multiple agents in multi-agent systems to improve execution latency, reduce token consumption, and increase task completion rates. It focuses on precise control mechanisms for context distribution during complex multi-round workflows.

Addresses a legitimate technical challenge in multi-agent systems with context optimization focus

Early stage specification with basic problem definition but lacking detailed protocols

Shares concepts with general multi-agent coordination work but specific context distribution angle is less common

Single draft submission with no indication of community engagement or follow-up activity

Directly addresses core multi-agent system coordination challenges essential for AI agent deployments


This draft extends RDAP to include verification status information for contact fields like email addresses and phone numbers. It aims to improve data quality and trustworthiness by indicating which contact data has been verified and the verification methods used.

Incremental extension adding verification metadata to existing RDAP contact fields - useful but straightforward enhancement

Detailed specification with clear protocol extensions, field definitions, and comprehensive examples showing verified contact structures

Shares verification concepts with other trust/authentication protocols but applies them specifically to RDAP contact data

Active development as evidenced by 2026 date, but momentum unclear without seeing revision history or working group status

This is purely about domain registration data verification protocols, not related to AI agents or autonomous systems


This draft proposes Agent Name Service (ANS), a DNS-inspired directory system for AI agent discovery using PKI certificates for identity verification. It defines registration, renewal, and resolution mechanisms with a modular protocol adapter layer supporting various agent communication standards.

Novel application of DNS concepts to AI agent discovery with innovative capability-aware resolution and protocol-agnostic registry design

Detailed specification with JSON schemas, algorithms, threat analysis, and comprehensive protocol definitions approaching implementation readiness

Unique focus on agent discovery with DNS-inspired approach, minimal overlap with existing IETF work

Single draft with no apparent working group activity or community feedback yet

Directly addresses core AI agent infrastructure need for secure discovery and interoperability in multi-agent systems

Agent discovery/reg
Agent identity/auth
A2A protocols
Data formats/interop


This draft specifies a NETCONF mechanism to trace configuration changes back to their originating network management system using external trace IDs. It includes a YANG module to map local configuration changes to their sources, enabling better troubleshooting and root cause analysis in multi-NMS environments.

Incremental extension of existing NETCONF capabilities with trace ID correlation - useful but straightforward addition to current practices

Detailed specification with concrete YANG module and clear mechanisms for trace ID propagation and mapping across network management layers

Shares configuration management and tracing concepts with existing NETCONF/RESTCONF work, but specific external trace ID approach has limited direct overlap

IETF working group draft with recent revision date, indicating active development and institutional backing within established standards process

Directly supports autonomous network operations by enabling automated root cause analysis and closed-loop automation for self-healing networks


This draft presents a problem statement for AI agent-to-agent discovery mechanisms, identifying requirements and considerations for how autonomous agents can find and connect with each other. It appears to be an early-stage exploration of discovery protocols needed as AI agents become more prevalent in networked environments.

Addresses a legitimate emerging need for agent discovery protocols, building on established service discovery concepts but applying them to the AI agent domain

Pure problem statement format with requirements gathering - no actual protocol mechanisms or technical solutions proposed

Shares conceptual ground with existing service discovery protocols (DNS-SD, mDNS) but focuses specifically on AI agent characteristics and requirements

Single draft submission with no clear working group adoption or broader community engagement visible

Directly addresses core AI agent networking infrastructure needs - discovery is fundamental for agent-to-agent communication and coordination


This draft proposes a reference architecture for privacy-preserving federated learning across multi-tenant AI agent systems, combining federated averaging with differential privacy and secure aggregation. The approach aims to enable collaborative model training between organizations while maintaining tenant data isolation and formal privacy guarantees.

Useful contribution combining established techniques (federated learning, differential privacy) for the specific context of multi-tenant AI agents, but builds on well-known privacy-preserving ML approaches

Early sketch stage - only 13 pages for a complex architecture covering federated learning, differential privacy, and secure aggregation likely indicates high-level overview without detailed protocol specifications

Shares significant conceptual overlap with existing federated learning and privacy-preserving ML literature, though specific application to multi-tenant AI agents may be less explored

Single revision with recent 2026 date suggests early-stage work without demonstrated community engagement or working group adoption

Directly relevant to AI agent systems, addressing the important challenge of collaborative learning across organizational boundaries while preserving privacy in multi-tenant deployments

AI safety/alignment
Policy/governance
Model serving/inference


This draft extends the Model Context Protocol (MCP) to enable network equipment like routers and switches to act as MCP servers, allowing AI-driven network controllers to manage infrastructure through standardized JSON-RPC interactions. It defines new capability tokens, tools, resources, and error codes specifically for network management while maintaining backwards compatibility with existing MCP implementations.

Useful application of existing MCP framework to network management domain, though the core idea of AI-driven network operations is well-established

Defines protocol extensions and mechanisms but likely needs more detailed specifications and implementation examples for full deployment

While network management protocols exist, applying MCP specifically to this domain has minimal direct overlap with other IETF work

Single revision with October 2025 date, no clear indication of working group adoption or broader community engagement yet

Directly relevant to AI agents in networking, addressing practical integration between AI systems and network infrastructure management

Autonomous netops
A2A protocols
Data formats/interop


This draft proposes extensions to HTTP Bearer authentication to enable automatic token fetching from Security Token Services during 401/407 flows. It aims to improve user experience by eliminating PKCE requirements and allowing token caching while providing OIDC fallback mechanisms.

Incremental improvement to existing Bearer auth flows, combining well-known patterns but not introducing fundamentally new concepts

Defines specific protocol mechanisms and flows with clear examples, though could benefit from more implementation details

Significant overlap with existing OAuth 2.0, OIDC, and HTTP authentication RFCs, building incrementally on established standards

Appears to be single revision with limited evidence of broader community engagement or working group adoption

Partially relevant as improved authentication flows could benefit AI agents and automated systems, though not specifically targeting AI use cases


ECAP proposes a cryptographically-secured protocol to replace robots.txt, requiring verifiable consent agreements between websites and AI crawlers/scrapers. The protocol uses digital signatures and declarative policies to create enforceable access controls rather than voluntary guidelines.

Notable originality in applying cryptographic verification to web crawling consent - moves beyond voluntary standards to enforceable agreements

Early sketch stage - only 3 pages with abstract-level description, lacks protocol details, message formats, or implementation guidance

Minor conceptual similarities to existing authentication protocols but unique application to crawler consent management

Single revision with recent date suggests initial proposal without demonstrated community engagement or working group adoption

Core AI agent topic - directly addresses critical issue of AI scraper consent and ethical data collection that's highly relevant to current AI deployment concerns

Policy/governance
Agent identity/auth
A2A protocols


This draft specifies agent identity management for an Internet of Agents (IOA) system, defining requirements for agent identities, registration processes, and identifier structures. It outlines basic and extended identity management functions to be performed by agent gateways.

Incremental work applying traditional identity management concepts to agent systems without significant novel approaches

Early sketch level - provides high-level framework but lacks detailed protocol specifications and implementation details

Significant conceptual overlap with existing identity management systems and other agent infrastructure proposals

Single revision with no apparent working group activity or broader community engagement

Core AI agent topic directly addressing fundamental infrastructure needs for agent identification and management

Agent identity/auth
Agent discovery/reg
A2A protocols


Defines Domain-Verified Skills (DVS) protocol for AI agents to discover and execute skill definitions served over HTTPS, using domain-based trust without centralized registries. Trust is established through Trust Root URL prefixes that scope verification boundaries.

Novel application of DNS/TLS trust infrastructure to AI agent skill verification, creative path-scoping solution for UGC platforms

Single draft submission with no apparent working group adoption or community discussion yet

Some conceptual similarity to general service discovery but unique AI agent skill focus and domain-based trust approach

Directly addresses core AI agent needs for skill discovery, verification, and execution with practical trust model

Agent discovery/reg
Agent identity/auth
Data formats/interop


This draft establishes standardized terminology for benchmarking Large Language Model inference serving systems, covering latency, throughput, resource utilization, and quality metrics. It provides a shared vocabulary for evaluating inference engines, application gateways, and compound agentic systems without prescribing specific methodologies.

Incremental work defining terminology for an emerging but well-understood domain

Detailed terminology definitions with clear scope and comprehensive coverage of LLM serving metrics

Limited overlap as LLM serving benchmarking terminology is relatively specialized

Active development in emerging field but no clear WG adoption signals

Directly relevant to AI agent infrastructure as LLM serving is core to agent systems


This draft explores applying existing IETF YANG data models (AC, TE Topology, SR Policy, QoS) to support dynamic UCMP policy enforcement for AI inference workloads across distributed edge cloud sites. It serves as a practical evaluation of current YANG model applicability and identifies gaps in cloud-initiated, time-bounded network policy coordination.

Incremental application of existing YANG models to AI inference use case, with straightforward mapping exercise

Early sketch exploring applicability with gap identification but lacks detailed protocol mechanisms or implementation specifics

Shares networking automation concepts with existing TE and QoS drafts, though specific AI inference application provides some differentiation

Single revision with niche focus on YANG model applicability; limited broader community engagement evident

Partially relevant - addresses network infrastructure requirements for AI inference workloads but focuses more on networking protocols than AI agent behavior


This draft specifies hybrid post-quantum key agreement mechanisms for TLS 1.3 that combine ML-KEM lattice-based cryptography with traditional ECDHE. It defines three specific combinations to provide quantum-resistant security while maintaining compatibility with current elliptic curve implementations.

Incremental work combining well-established post-quantum ML-KEM with standard ECDHE - straightforward hybrid approach following expected migration patterns

Detailed specification with concrete parameter combinations, algorithm definitions, and appears implementation-ready for TLS 1.3 integration

Significant overlap with other post-quantum TLS drafts and hybrid key exchange mechanisms - builds on established ML-KEM and ECDHE standards

IETF working group draft with strong industry momentum for post-quantum cryptography migration, critical for quantum-resistant TLS deployment

Pure cryptographic protocol specification for general TLS security - not specifically related to AI agents or autonomous systems


This draft specifies how to integrate remote attestation capabilities into the EDHOC lightweight key exchange protocol using the RATS architecture. It enables verification of device/software integrity during the authentication handshake process.

Useful integration of existing RATS attestation with EDHOC, providing practical value for IoT security scenarios

Detailed specification with protocol flows and message formats, appears implementation-ready

Builds on established EDHOC and RATS frameworks but creates novel integration approach

IETF working group draft with clear adoption path and active development

This is about cryptographic protocols and device attestation, not AI agents or artificial intelligence systems


This draft proposes a new DNS resource record type called AGENT that extends SVCB for discovering and resolving AI agent services. It addresses limitations in current DNS for agent service resolution by defining SVCB-compatible mappings specifically for intelligent agent communication protocols.

Useful contribution applying existing SVCB framework to emerging agent discovery needs

Early sketch with basic problem statement and proposed approach but lacks detailed specification

Minor similarities to SVCB extensions but addresses distinct agent-specific use case

Single draft with no apparent working group activity or community engagement

Directly addresses agent infrastructure needs for service discovery and protocol negotiation

Agent discovery/reg
A2A protocols
Data formats/interop


This draft identifies use cases and challenges for ALTO (Application-Layer Traffic Optimization) in multi-domain network environments where traffic paths span multiple autonomous networks. It outlines three specific multi-domain scenarios and briefly discusses implementation approaches to address the identified challenges.

Incremental extension of existing ALTO work to multi-domain scenarios, fairly straightforward problem identification

Early stage work presenting use cases and challenges with only brief mentions of implementation solutions

Builds directly on existing ALTO specifications but addresses a distinct multi-domain aspect

Single revision draft from January 2024 with no clear indicators of working group adoption or community engagement

While about traffic optimization which could involve AI applications, this is primarily a networking protocol extension without direct AI/agent focus


This draft proposes a framework for integrating Large Language Models into network management systems with mandatory human oversight and decision approval loops. It defines telemetry modules, LLM decision components, and standardized data models to enable human-AI collaboration in network operations.

Useful contribution combining LLMs with network management, though human-in-the-loop concepts are established in other domains

Early framework sketch with high-level components described but lacking detailed protocols, APIs, or implementation specifics

Some conceptual overlap with general AI-assisted operations frameworks but specific network management focus is relatively unique

Active development in IRTF research group with growing interest in AI-driven network operations, though still early stage

Core AI agent topic directly addressing human-AI collaboration in critical infrastructure management

Human-agent interaction
Autonomous netops
Data formats/interop


This draft proposes Agent Internet Protocol (AIP) as a network-layer protocol for AI agent communication, using agent:// URIs instead of IP addresses and serving as the narrow waist for an Agent Network Protocol suite. It defines message formats, addressing, and processing rules analogous to IP but tailored for autonomous AI agents.

Creating a dedicated network protocol layer specifically for AI agents with human-readable capability-descriptive naming is notably original

Comprehensive 32-page specification with detailed message formats, addressing model, error handling, and layer interfaces suggests implementation-ready detail

While building on IP concepts, the agent-specific addressing and protocol design appears largely unique

Single draft from 2026 with no indication of working group adoption or broader community engagement

Directly addresses core AI agent networking infrastructure, proposing fundamental protocols for agent-to-agent communication

A2A protocols
Agent identity/auth
Agent discovery/reg


This draft extends IETF RATS architecture to support multiple verifiers coordinating together to assess attester trustworthiness. It defines topological patterns for multi-verifier systems while remaining agnostic to specific protocols or implementations.

Useful architectural extension addressing real need for distributed attestation in complex systems

Early architectural sketch with basic patterns but lacks detailed mechanisms or protocols

Minor overlap with base RATS architecture but addresses distinct multi-verifier coordination gap

Single revision with February 2026 date, appears to be early-stage work

Remote attestation is tangentially related to AI agents but primarily focused on general system trustworthiness


DAAP v2.0 provides a comprehensive protocol for monitoring and controlling autonomous AI agents through cryptographic identity verification, periodic check-ins, and remote shutdown capabilities. The protocol addresses AI safety concerns with hardware-backed security, real-time behavioral monitoring, and ethical governance frameworks.

Notable originality in combining hardware-backed security with AI-specific behavioral monitoring and remote shutdown capabilities in a standardized protocol framework

Detailed 18-page specification with comprehensive protocol mechanisms including authentication, monitoring, and control systems

Minor similarities to general device management protocols but unique application to AI agent accountability and safety

Single revision with no indication of working group adoption or broader community engagement

Core AI agent topic directly addressing critical challenges in AI safety, accountability, and autonomous agent control

AI safety/alignment
Agent identity/auth
Policy/governance
A2A protocols


AgentDNS proposes a DNS-inspired naming and service discovery system that enables LLM agents to autonomously find and securely invoke third-party agent services across different vendors. The system introduces a unified namespace with semantic discovery, protocol-aware interoperability, and unified authentication for large-scale agent collaboration.

Novel application of DNS concepts to agent ecosystems with semantic discovery and cross-vendor interoperability - addresses emerging need for agent-to-agent service discovery

Early conceptual draft at 22 pages but likely lacks detailed protocol specifications, message formats, and implementation details needed for a working system

While inspired by DNS, the agent-specific semantic discovery and cross-vendor authentication aspects appear relatively unique in the agent networking space

Single draft from 2026 with no apparent working group adoption or community development indicated

Directly addresses core agent infrastructure needs for service discovery, interoperability, and trust management in multi-agent systems


This draft extends SIP to support the Model Context Protocol (MCP), adding option tags, headers, and media types for AI model context exchange. It enables MCP payload transmission during SIP session establishment and mid-dialog communications.

Useful integration of existing protocols (SIP + MCP) for a legitimate use case, though the extension follows standard SIP patterns

Detailed specification with new option tags, headers, media types, and multiple exchange mechanisms - appears implementation-ready

While building on established SIP extension patterns, the specific MCP integration appears to be a unique approach

Single revision from April 2026 with no visible working group activity or community discussion

Directly relevant to AI agent communication infrastructure, enabling context sharing between agents via established telephony protocols


This draft specifies quantum-resistant cipher suites for the EDHOC lightweight authenticated key exchange protocol, integrating ML-DSA signatures and ML-KEM key exchange algorithms. It defines how EDHOC operates with post-quantum cryptography for both signature-based and PSK-based authentication methods.

Straightforward integration of standardized post-quantum algorithms into existing EDHOC protocol - incremental but necessary work

Detailed specification with concrete cipher suite definitions and protocol operations, appears implementation-ready

Shares post-quantum cryptography integration concepts with other protocol upgrade drafts, but specific to EDHOC

Strong momentum given NIST PQC standardization completion and industry urgency for quantum-resistant protocols

Pure cryptographic protocol specification focused on quantum resistance - not related to AI or autonomous agents


Proposes a protocol for embedding service type identifiers into network packets to enable intelligent traffic recognition and policy-based forwarding. The mechanism works across IPv4/IPv6 headers, MPLS labels, and Ethernet frames for applications like VR, scientific computing, and IoT.

Incremental extension of existing traffic classification and QoS marking concepts to include service type awareness

Defines a protocol mechanism with header formats but lacks detailed implementation specifics and test cases

Significant overlap with existing QoS marking (DSCP), traffic engineering, and service chaining protocols

Single draft with fabricated working group name suggests limited real development activity

Only tangentially AI-related through mention of 'intelligent' traffic recognition, primarily a network QoS protocol


This draft defines N-ACT, a standardized protocol for AI agents to discover and invoke third-party tools via normalized APIs. It focuses on enterprise environments and defines enumeration APIs for tool discovery and invocation APIs for runtime execution.

Incremental standardization of existing AI tool integration patterns, building on established OpenAI function calling approaches

Defines core protocol mechanisms with API specifications, though lacks detailed implementation examples and comprehensive error handling

Significant conceptual overlap with existing tool integration frameworks and OpenAI function calling specifications

Single draft submission with no evidence of working group adoption or broader community engagement

Directly addresses core AI agent functionality around tool integration, a fundamental capability for enterprise agent deployment


```json
{
  "s": "Defines Agent Name System (ANS) for mapping human-readable agent:// URIs to cryptographic peer identities in autonomous AI agent networks. Provides name registration/resolution protocol with gossip and DHT dissemination mechanisms.",
  "n": 4,
  "nn": "Novel application of naming systems specifically for AI agent networks with agent:// URI scheme and multi-modal addressing (unicast/anycast/channel)",
  "m": 4,
  "mn": "Detailed 34-page specification with defined record formats, AITP methods, resolution algorithms, and dissemination mechanisms",
  "o": 2,
  "on": "Some conceptual similarity to DNS and other naming systems but specifically designed for AI agent peer-to-peer networks",
  "mo": 2,
  "mon": "Single draft from March 2026 with no clear working group adoption or community feedback visible",
  "r": 5,
  "rn": "Core AI agent infrastructure addressing fundamental naming and identity binding requirements for autonomous agent networks",
  "c": ["Agent identity/auth", "Agent discovery/reg", "A2A protocols"]
}
```


This draft specifies AGTP-API, a contract layer for the Agent Transfer Protocol that defines method catalogs, path grammar, endpoints, and runtime negotiation mechanisms for autonomous agent interactions. It consolidates and supersedes previous AGIS and AGTP-Methods drafts into a unified API specification.

Notable originality in defining a comprehensive API contract layer specifically for autonomous agents, including novel concepts like semantic blocks, synthesis runtime negotiation, and structural rejection codes

Detailed specification with comprehensive coverage of API components, method catalogs, endpoint definitions, and specific status codes, appears implementation-ready

Minor similarities to standard REST API design patterns, but the autonomous agent context and specific mechanisms like PROPOSE-and-synthesis are fairly unique

Active development evidenced by consolidation of previous drafts and comprehensive rewrite, but unclear if there's broader community adoption beyond the author

Core AI agent topic focusing specifically on autonomous agent communication protocols and API design


This draft proposes using agentic AI for distributed sensing and communication optimization in ISAC networks, addressing the complex joint selection of sensing entities, processing locations, and network configurations. It presents initial architectural considerations for enabling closed-loop reconfiguration of sensing and networking resources under time-varying conditions.

Useful contribution applying agentic AI to ISAC networks, though builds incrementally on existing sensing and AI concepts

Early sketch with initial considerations and potential solution directions, lacks detailed mechanisms or protocols

Minor similarities to other network optimization drafts but focuses on unique ISAC sensing scenario

Single revision draft with future date, no evidence of working group adoption or community engagement yet

Directly relevant as it specifically addresses agentic AI for network optimization with distributed decision-making


This draft defines a semantic-driven traffic shaping contract that allows AI applications to provide network metadata about tensor flows to enable differentiated forwarding and resource allocation. The approach aims to improve efficiency by moving beyond treating AI traffic as opaque byte streams to semantic-aware network scheduling.

Notable originality in bridging AI application semantics with network-layer traffic management through explicit contracts

Early sketch stage - defines concept but lacks detailed protocol mechanisms, message formats, or implementation specifics

Minor similarities to general QoS and traffic engineering work, but semantic-driven AI traffic contracts appear relatively unique

Single revision with no clear working group adoption or broader community engagement visible

Core AI agent topic - directly addresses network infrastructure optimization for AI training and inference workloads


AGTP defines a dedicated application-layer protocol for AI agent traffic that addresses limitations of HTTP for agent communication. It features runtime contract negotiation with a 12-method floor organized as cognitive and mechanics verbs, plus agent identity addressing.

Creating a dedicated transport protocol for AI agents with runtime contract negotiation is notably original compared to existing HTTP-based approaches

Very detailed 133-page specification with IANA registrations, formal URI grammar, complete method definitions, and comprehensive protocol mechanics

While it mentions existing AGMPs (MCP, ACP, A2A, ANP), AGTP positions itself as a transport substrate rather than competing messaging protocol

Version 07 indicates active development with significant changes, but unclear if this has broader community adoption or WG interest

Directly addresses core AI agent infrastructure needs including identity, observability, and semantic vocabulary for agent-to-agent communication


This draft updates the HTTP Cookie and Set-Cookie header field specifications, replacing RFC 6265 to address historical security and privacy issues while maintaining compatibility with existing widespread usage. The document provides a comprehensive revision of the cookie mechanism that underlies stateful HTTP sessions across the web.

Incremental improvement over existing cookie standards, addressing known issues rather than introducing novel concepts

Detailed specification with comprehensive coverage of cookie mechanisms, ready for implementation

Direct update/replacement of RFC 6265 and 6265bis, essentially the same core functionality

Active HTTPBIS working group development with clear path to standardization

HTTP cookie mechanism is fundamental web infrastructure, not specifically related to AI or agents


This draft proposes a framework for decentralized LLM inference across untrusted participants, treating inference as distributed layer-wise execution with explicit deadlines rather than monolithic computation. It addresses the limitations of centralized LLM deployments by enabling coordination among heterogeneous compute resources without requiring trusted operators.

Notable originality in applying layer-aware distributed execution to LLM inference with explicit deadline constraints and untrusted participant coordination - goes beyond typical federated learning approaches

Single revision with March 2026 date suggests very early stage work without established community engagement or working group adoption

Minor similarities to general distributed computing and federated learning concepts, but the LLM-specific layer-aware approach with deadline constraints appears relatively unique

Core AI agent topic directly addressing LLM inference infrastructure, which is fundamental to AI agent deployment and operation at scale

Model serving/inference
A2A protocols
Autonomous netops


This draft specifies an optimized KEM-based authentication method for EDHOC protocol in scenarios where the initiator knows the responder's credentials beforehand. The approach enables post-quantum signature-free authentication using a three-message handshake while maintaining mutual authentication and forward secrecy.

Incremental optimization of existing KEM-based EDHOC authentication for a specific but common use case

Detailed 26-page specification with concrete protocol definition and mechanisms for implementation

Significant overlap with existing KEM-based Authentication for EDHOC draft, building directly upon that work

Single revision with no clear indication of working group adoption or broader community engagement

This is a cryptographic protocol specification for device authentication, not related to AI or autonomous agents


This draft proposes an AI-assisted framework for automating network protocol testing using large language models, with components for protocol formalization, test generation, and iterative refinement. It defines 6 automation maturity levels (0-5) ranging from manual testing to fully autonomous adaptive systems.

Applies established AI/LLM concepts to protocol testing domain with structured maturity levels - useful contribution but not groundbreaking

Early framework sketch with high-level components and maturity definitions, but lacks detailed mechanisms, algorithms, or concrete implementation guidance

Some conceptual overlap with general AI testing frameworks but specific focus on network protocol testing appears relatively unique

Single draft submission with no indication of working group interest or community engagement beyond initial publication

Directly addresses AI-assisted automation in networking domain with clear agent-like capabilities at higher maturity levels

Autonomous netops
Model serving/inference


This draft proposes a MANET internetworking framework using AERO and OMNI technologies to enable mobile ad-hoc networks to connect with fixed networks like the Internet. It builds on existing RFC 2501 MANET definitions to provide gateway and routing mechanisms.

Incremental work combining existing AERO/OMNI technologies for MANET internetworking, standard networking protocol development

Defines specific protocol framework and mechanisms for MANET internetworking with technical details

Significant overlap with existing MANET routing protocols and internetworking approaches, builds heavily on established AERO/OMNI work

Limited momentum indicated, appears to be individual submission with single revision

This is purely about mobile ad-hoc network routing and internetworking protocols, not related to AI or agents despite 'autonomous system' terminology


Defines a JSON-based 'Signature Agent Card' format for web bots to advertise metadata about themselves including identity, purpose, rate limits, and cryptographic keys. Establishes an IANA registry for extensible discovery of agent information through a directory service.

Useful contribution applying established agent card concepts specifically to web bot authentication with cryptographic signatures

Early sketch with basic format description but lacking detailed protocol mechanics, implementation guidance, or concrete examples

Significant overlap with existing agent card formats and web authentication mechanisms, though specific combination may be novel

Single revision with future date suggests early stage work without demonstrated community engagement or working group adoption

Directly relevant to AI agent authentication and discovery, addressing key challenges in bot identification and trust establishment

Agent identity/auth
Agent discovery/reg
Data formats/interop


This draft extends OAuth 2.0 token revocation to support agent-based batch operations, cascade propagation, and audit trails for autonomous systems. It introduces new endpoints and protocols to handle revocation at the agent level rather than individual tokens.

Useful contribution addressing practical gaps in OAuth for agent scenarios, though builds incrementally on existing revocation mechanisms

Defines protocol mechanisms and new endpoints but appears to lack detailed implementation specifics and comprehensive examples

Minor conceptual overlap with general OAuth extensions but takes a distinct agent-centric approach to revocation

Single revision with future date suggests early stage work without demonstrated community engagement

Directly addresses authentication and authorization needs for autonomous agent networks and cross-domain scenarios


AIDP defines a control-plane protocol for secure agent interactions, delegation, and interoperability across heterogeneous systems. The protocol includes mechanisms for intent expression, authority enforcement, capability delegation, and auditable action execution.

Notable originality in creating a comprehensive control-plane protocol specifically for agent interactions with delegation and authority mechanisms

Detailed 34-page specification with defined protocol mechanisms, likely includes examples and substantial technical detail

Minor similarities to existing protocols but unique focus on agent delegation and control-plane interactions

Single revision with recent date suggests early stage without established community momentum

Core AI agent topic addressing fundamental needs for agent interoperability, delegation, and secure interactions

A2A protocols
Agent identity/auth
Data formats/interop
Policy/governance


JEP defines a protocol for verifiable decision events with four immutable verbs (Judgment, Delegation, Termination, Verification) using signed JSON structures. It aims to provide interoperability for decision records across human, organizational, software, and autonomous agent systems.

Novel approach to creating a universal protocol for verifiable decision events across diverse agent types with well-defined event semantics

Defines core protocol structure with JSON/JWS but lacks detailed implementation examples and test vectors

Some conceptual overlap with event logging and audit trails, but unique focus on decision event verifiability across agent types

Single draft with future date suggests early stage development with no visible community engagement yet

Directly addresses autonomous agent decision tracking and verification, key for multi-agent system accountability

A2A protocols
Data formats/interop
Agent identity/auth


This draft identifies the need for geospatial resource discovery services that enable applications like AR and autonomous systems to discover resources based on physical location rather than predefined identifiers. It presents a problem statement and conceptual architecture for spatial-based discovery mechanisms.

Addresses a genuinely novel problem space where discovery begins with physical presence rather than known identifiers, which is fundamentally different from traditional name-based resolution

Purely a problem statement and high-level conceptual architecture with no protocol definitions, data formats, or implementation details

Unique approach to spatial-based resource discovery that doesn't overlap significantly with existing internet protocols or standards

Recent draft from 2026 but appears to be initial work with no indication of working group adoption or broader community engagement yet

Highly relevant to AI agents, particularly autonomous systems, robotics, and AR applications that need to discover resources based on spatial context rather than predetermined names

Agent discovery/reg
Autonomous netops
Data formats/interop


This draft extends SCIM 2.0 to support identity management for AI agents and agentic applications by adding new resource types and schemas. It aims to enable cross-domain agent identity management using existing SCIM infrastructure rather than creating new protocols.

Useful contribution applying established identity management patterns to the emerging agent ecosystem

Early sketch - abstract only provides high-level concepts without protocol details or concrete schemas

Minor similarities to general identity management approaches but unique focus on agent-specific SCIM extensions

Future-dated draft (2026) suggests this is conceptual work without current implementation momentum

Directly addresses agent identity management needs, though focuses more on infrastructure than core AI capabilities

Agent identity/auth
Data formats/interop


This draft enhances EAP-AKA' Forward Secrecy with hybrid post-quantum cryptography to protect against future quantum computer threats. It addresses the vulnerability of current ECDHE-based ephemeral key exchange by incorporating quantum-resistant algorithms.

Incremental enhancement applying established post-quantum cryptography concepts to existing EAP-AKA' protocol

Defined protocol enhancement with clear problem statement and solution approach, but may lack implementation details

Shares post-quantum cryptography concepts with other hybrid PQC drafts and builds on existing EAP-AKA' specifications

IETF working group draft with clear standardization path, addressing urgent quantum-readiness requirements

Not about AI or agents - this is a network authentication protocol enhancement for quantum resistance


This draft specifies how the Agent-to-Agent (A2A) protocol can be transported over Media over QUIC Transport (MOQT), leveraging MOQT's publish/subscribe model and streaming capabilities for real-time AI agent communication. It addresses the transport layer requirements for A2A protocol operations including discovery, negotiation, and collaboration between AI agents.

Incremental work applying existing MOQT transport to A2A protocols - straightforward protocol mapping rather than novel approach

Appears to define specific protocol mechanisms for A2A over MOQT but limited detail available from abstract about implementation specifics

Likely shares transport concepts with other QUIC-based drafts and A2A protocol work, though specific A2A-MOQT combination may be unique

Single draft with October 2025 date suggests very early stage work with no clear community uptake yet

Directly addresses AI agent communication transport needs, which is core infrastructure for multi-agent systems

A2A protocols
Agent discovery/reg
Data formats/interop


This draft updates RFC8878 to make window size limits for Zstandard compression a requirement rather than recommendation in HTTP contexts. It addresses interoperability issues where browsers limit memory usage by restricting zstd window sizes.

Trivial clarification converting existing recommendation to requirement with no new technical content

Well-defined specification update with clear requirements and implementation guidance

Direct update to existing RFC8878 with complete overlap on the specific window sizing topic

IETF working group draft with clear adoption path addressing real interoperability problems

Pure HTTP compression specification with no AI or agent-related content