WIMSE Applicability for AI Agents
draft-ni-wimse-ai-agent-identity-02
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| Document | Type | Active Internet-Draft (individual) | |
|---|---|---|---|
| Authors | Ni Yuan , Peter Chunchi Liu | ||
| Last updated | 2026-02-28 | ||
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draft-ni-wimse-ai-agent-identity-02
Workload Identity in Multi System Environments Y. Ni
Internet-Draft C. P. Liu
Intended status: Informational Huawei
Expires: 1 September 2026 28 February 2026
WIMSE Applicability for AI Agents
draft-ni-wimse-ai-agent-identity-02
Abstract
This document discusses WIMSE applicability to Agentic AI, so as to
establish independent identities and credential management mechanisms
for AI agents.
About This Document
This note is to be removed before publishing as an RFC.
Status information for this document may be found at
https://datatracker.ietf.org/doc/draft-ni-wimse-ai-agent-identity/.
Discussion of this document takes place on the Workload Identity in
Multi System Environments Working Group mailing list
(mailto:wimse@ietf.org), which is archived at
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https://www.ietf.org/mailman/listinfo/wimse/.
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This Internet-Draft will expire on 1 September 2026.
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Copyright Notice
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This document is subject to BCP 78 and the IETF Trust's Legal
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Please review these documents carefully, as they describe your rights
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Conventions and Definitions . . . . . . . . . . . . . . . . . 4
3. Architecture . . . . . . . . . . . . . . . . . . . . . . . . 4
3.1. Bootstrapping AI Agent Identity and Credentials . . . . . 5
3.2. Attestation . . . . . . . . . . . . . . . . . . . . . . . 6
4. Identity Binding Extensions for WIMSE . . . . . . . . . . . . 6
4.1. Use Cases . . . . . . . . . . . . . . . . . . . . . . . . 6
4.1.1. Cross-organization Interaction . . . . . . . . . . . 7
4.2. Issuance Models . . . . . . . . . . . . . . . . . . . . . 7
4.2.1. Agent-Mediated (Owner-Pre-Signed) . . . . . . . . . . 7
4.2.2. Owner-Mediated (Gateway Mode) . . . . . . . . . . . . 9
4.2.3. Server-Mediated (Challenge-Response) . . . . . . . . 10
5. Comparison with CHEQ . . . . . . . . . . . . . . . . . . . . 11
6. Initial Trust Establishment . . . . . . . . . . . . . . . . . 12
7. Security Considerations . . . . . . . . . . . . . . . . . . . 13
8. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 13
9. References . . . . . . . . . . . . . . . . . . . . . . . . . 13
9.1. Normative References . . . . . . . . . . . . . . . . . . 13
9.2. Informative References . . . . . . . . . . . . . . . . . 13
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . 14
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 14
1. Introduction
AI agents are autonomous software entities that receive an intent,
process contextual information, and execute decisions at machine
speed with minimal human intervention. Without appropriate
guardrails, they may give rise to significant risks:
* Blurred Network Boundaries: AI agents may operate across systems
and platforms, which expands attack surface and amplifies security
risks.
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* Arbitrary and Unpredictable Access Patterns: AI agents may perform
unexpected actions or access sensitive resources susceptible to
malicious manipulation or logical errors.
* Lack of Accountability: Tracing an AI agent's actions is
inherently difficult, leading to difficulty to detect erroneous
behaviors.
* Context Rot: A gradual degradation of their ability to maintain
relevant and coherent call contexts over time.
Therefore, for AI agents, the traditional perimeter-based security
model has to transform into the identity-based security model, which
is a prequisite to implementing precise access control and ensuring
security visibility.
To realize this goal, a mechanism should be designed considering the
following requirements:
* Independent, Trustworthy Identities: AI agents should have
independent and trustworthy identities and credentials, distinct
from those of devices and users. This allows the AI agent to act
either on its own behalf or as a delegation of a user, have its
own access tokens and workflows.
* Automated Credential Management: An automated mechanism is
necessary for managing credentials with reduced validity period to
minimize security exposure.
* Minimal Privileged Access Tokens: AI agents should have task-
oriented, fine-grained access tokens with short validity periods.
* Explicit Workflows: AI agents need explicit workflow management in
order to avoid random agentic access. The workflow could be long-
termed and static, or could be short-termed and task-triggered,
but the call context must always be visible and preserved.
This document discusses possibility of using WIMSE architecture to
provide AI agent identities and credentials. It accords with the
original WIMSE use case in Section 3.3.1 Bootstrapping Workload
Identifiers and Credentials of [I-D.ietf-wimse-arch-06]. We also
discuss requirements of extending WIMSE architecture to bind
workload/AI agent identity to its owner's identity.
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2. Conventions and Definitions
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and
"OPTIONAL" in this document are to be interpreted as described in BCP
14 [RFC2119] [RFC8174] when, and only when, they appear in all
capitals, as shown here.
This document uses terms and concepts defined by WIMSE architecture.
For a complete glossary please refer to [I-D.ietf-wimse-arch-06]:
* Trust Domain: A logical grouping of systems that share a common
set of security controls and policies. Agent credentials are
issued under the authority of a trust domain.
* AI Agent: The autonomous software entity that initiates the
credential request. This document may refer to it as the "agent",
but is is essentially the workload instead of the agent in the
WIMSE architecture.
* Identity Server: A trusted entity issuing agent identity and
credentials. For simplicity, this document may refer to this
component as the "server".
* Identity Proxy: An intermediary component that can request,
inspect, replace or augment agent identity credentials. It
exposes an Agent API locally to agents. For simplicity, this
document may refer to this component as the "proxy".
In addition, this document introduces the following new terms: *
Owner: An entity (individual or organization) responsible for the an
agent, which can provide a cryptographic signature to bind the agent
identity to a specific principal. Logically, an owner may manifest
in various forms, including a natural person (e.g., via a manual
confirmation process), a physical device (e.g., a hardware security
module), or an automated policy engine that grants approval based on
pre-defined security policies. * Dual-Identity Credential: A
credential that contains the identifiers and associated public keys
of both an agent and its owner. The credential is cryptographically
bound to both entities.
3. Architecture
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3.1. Bootstrapping AI Agent Identity and Credentials
This document presumes that the identity server has already been
issued a signing certificate which has set keyCertSign in the key
usage extension. The server and the proxy are assumed to have
established a secure channel. A basic workflow is shown in Figure 1.
1. As an intermediary between the server and the agents, the proxy
provides an agent API that agents can use to initiate identity
credential requests. These requests include a public key and a
signature as proof-of-possession to demonstrate control of the
corresponding private key.
2. The proxy forwards these requests, along with the attestation
evidence for verifing the operational status of the agent, to the
server for processing.
3. The server validates the evidence received from the proxy, and
issues the corresponding identity credentials.
4. Once issued, the proxy forwards the agent identity credentials.
+----------------------------+
| Identity Server |
+-------------- ^ + ---------+
(2)identity | |(3)identity
credential | | credential
request & | |
evidence | |
+-----------------+-+-----------------------------------+
| Trust Domain | | (1)identity |
| | | credential |
| +--------------++ v ---------+ request +-------+ |
| | | <--------------+ | |
| |Identity Proxy| Agent API +--------------> Agent | |
| | | | (4)identity | | |
| +--------------+----- ^ -----+ credential +-------+ |
| evidence | |
+-----------------------+-------------------------------+
| Hosting Operating Systems and Hardware |
+-------------------------------------------------------+
_Figure 1: Basic Architecture and the Workflow_
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3.2. Attestation
During the request and issuance of identity credentials, the proxy
should gather attestation evidence from the operating system and
hardware to verify the operational status of the agent. This
information is used by a RATS Verifier (could be the server) to
support identity server's decision of whether or not to issue the
identity credential of an agent, whether it is a bootstrapping or a
renewal request. The structure and claims of this evidence may refer
to the Entity Attestation Token (EAT) profile for Autonomous AI
Agents [I-D.draft-messous-eat-ai-01], which defines specialized
claims for AI agent integrity, training provenance, and runtime
authorization.
4. Identity Binding Extensions for WIMSE
The basic WIMSE architecture ensures a trusted entity owns a trusted
workload identity that is secure to connect to. However, the agent
often operates on behalf of a human user or an organization.
Consequently, an agent requires a credential that cryptographically
binds its identity to its owner’s identity. This dual-identity
credential provides a necessary foundation for access control and
accountability. This section describes the necessity of dual-
identity credential through two representative use cases and defines
three operational models to issue it.
4.1. Use Cases
### Network Access Control in Campus
Campus administrators require authentication of agents before
granting access to internal network via authentication protocols such
as IEEE 802.1X (e.g., using EAP-TLS). In this scenario, the
Authentication Server must verify the agent's credential and
determine its network privileges. A single-identity credential only
allows the Authentication Server to identify the agent itself.
Without further information, Authentication Server may treat the
agent as a guest, providing only limited public access or rejecting
the request to protect sensitive zones. A dual-identity credential
allows the Authentication Server to verify both the agent's identity
and the specific user or department it represents. For instance, an
agent representing Alice from the R&D department can be identified as
a trusted entity, and can receive proper access privileges according
to existing IAM information (like RBAC). This enables the network to
implement user-specific segmentation, such as automatically assigning
the agent to the R&D VLAN rather than a guest network.
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4.1.1. Cross-organization Interaction
In collaborative enterprise environments, it is essential to ensure
that any agent requesting services is explicitly approved by its
organization. This requirement spans the entire credential
lifecycle, from issuance to interaction.
* Issuance: When an agent requests an identity credential, the
identity server may require organizational oversight. By binding
the agent's identity credential request to its corresponding
organization, the server can verify the organizational approval
before issuing the credential. In other words, dual-identity
credential could be a manifestation of Human-in-the-Loop (HITL)
mechanisms.
* Interaction: When an agent accesses another agent or a service
across organizational boundaries, authentication is necessary to
ensure the request is from a valid entity, as illustrated in the
A2A protocol[A2A-SPEC] and WIMSE
architecture[I-D.ietf-wimse-arch-06]. A dual-identity credential
carries an organizational approval, which provides a strong basis
for trust, ensuring both accountability and traceability for
cross-organization interactions.
4.2. Issuance Models
Identity binding can be integrated into the WIMSE workflow in several
ways. we introduce the following three models according to the
mediation point where the agent's identity and organizational
authority are cryptographically bound. Before initiating the dual-
identity issuance flow, a pre-established trust relationship must
exist, where the identity server is provisioned with trust anchors
(e.g., public keys, CA certificates, or hardware-backed credentials)
to verify the owner’s signature. The mechanism by which these trust
anchors are established, distributed, or updated is out of scope of
this document.
4.2.1. Agent-Mediated (Owner-Pre-Signed)
In this model, the owner acts as a local offline approvar, which
provides a signature on the agent's request before it is submitted to
the proxy. The identity binding phase, consisting of the following
two steps, is added prior to the standard issuance flow defined in
Figure 1:
a. The agent generates an identity credential request and sends it
to the owner.
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b. The owner signs the request and returns the signature to the
agent. The agent then combines the original request and the owner's
signature into a new composite request.
The following steps are similar to the basic architecture, that is,
the agent send the new composite request to the server via the proxy
(steps 1 and 2), then the server verifies the request and issues the
dual-identity credential to the agent via the proxy (steps 3 and 4).
+----------------------------+
| Identity Server |
+-------------- ^ + ---------+
(2)| |(3)
+-----------------+-+---------------------------------+
| Trust Domain | | +-------+ |
| | | | owner | |
| | | +--^-+--+ |
| | | (a)request| |(b)signature |
| +--------------++ v -------+ (1) +--+-v--+ |
| | | ------+ | |
| |Identity Proxy| Agent API ------> Agent | |
| | | | (4) | | |
| +--------------+-----------+ +-------+ |
+-----------------------------------------------------+
_Figure 2: Agent-Mediate Model_
* Typical Application Scenarios: This model is ideal for local
identity binding where the owner and agent operate on the same
host . It supports asynchronous and offline owner confirmation,
allowing the owner use local signing module (e.g., a hardware
security key) to pre-sign the agent's request. For instance, a
developer using a personal hardware security key to sign an
agent's request directly on their local machine. Therefore, this
model obviously supports hardware-based identity binding,
cryptographically anchoring the agent’s dual-identity to the
specific physical device managed by the owner.
* Attack Surface: The primary attack surface lies at the local
environment, focusing on two main risks. First is human-agent
trust exploitation: an attacked or rogue agent may manipulate
human users to approve malicious request. Second is the
compromise of signing keys: if the owner’s local private keys are
not protected by hardware (e.g., TPM), an attacker can forge
confirmations.
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4.2.2. Owner-Mediated (Gateway Mode)
In this model, the owner acts as the supervisory gatekeeper between
the proxy and the server. It inspects requests relayed by the proxy
to ensure compliance with organizational policies, providing
cryptographic binding only after approval.
Such a mechanism is intergrated in the basic architecture as shown in
Figure 3. Firstly, the agent generates an identity credential
request and sends it to the proxy(step 1), then：
a. The proxy intercepts the request and relays it to the owner for
administrative inspection.
b. The owner reviews and signs the request. It then combines the
original request and the owner's signature into a new composite
request to be submitted to the server, along with additional
organizational materials, such as an oragnizational credential.
c. The server validates the received information and issues the
dual-identity credential back to the owner, who then dispatches it to
the proxy.
Finally, the proxy send the credential to the corresponding
agents(step 4).
Figure 3 shows a one-to-one mapping case between the owner and the
proxy. In this case, the function of owner can be integrated
directly into the proxy, collapsing the hierarchy into a single
entity to simplify the deployment. Moreover, this model also
supports a one-to-many topology, allowing a central owner to manage
multiple proxies across various trust domains.
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+----------------------------+
| Identity Server |
+------------------^-+-------+
(b)request | | (c)dual-identity
(signature) | | credential
+------------------+-v-------+
| Owner |
+------------------^-+-------+
(a)request | | (c)
+--------------------+-+--------------------------------+
| Trust Domain | | |
| +--------------+---+-v-------+ (1) +-------+ |
| | | <--------------- | |
| |Identity Proxy| Agent API |--------------> Agent | |
| | | | (4) | | |
| +--------------+-------------+ +-------+ |
+-------------------------------------------------------+
_Figure 3: Owner-Mediate Model_
* Typical Application Scenarios: This model is ideal for enterprise
governance. Since the owner sits in the middle, acting like a
middlebox to ensure no request reaches server unless it complies
with enterprise security policies and compliance requirements. It
is particularly suitable for hierarchical environments where the
owner acts as a centralized gateway for multiple proxies.
* Attack Surface: The owner becomes a high-value target and a single
point of failure. If it is compromised, an attacker can forge
approvals for any agent across the managed proxies. To mitigate
this, mutual authentication and cryptographic integrity are
mandatory between proxies and the owner. Furthermore, as a
centralized gateway, the owner is vulnerable to Denial-of-Service
attacks. It is essential to implement rate limiting and request
queuing.
4.2.3. Server-Mediated (Challenge-Response)
In this model, the owner acts as an independent verifier. The server
orchestrates the binding phase by contacting the owner as a separate
step in the issuance logic, decoupling the binding from the agent's
request.
This mechanism is integrated into the basic architecture as shown in
Figure 4. First, the agent sends an identity credential request to
the server via the proxy (steps 1 and 2), then:
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a. The server pauses the process and sends a binding challenge to
the owner on whose behalf the requesting agent acts. This initiates
the owner confirmation flow.
b. The owner reviews the challenge, signs it, and returns the
response to the server.
After that, the server validates the owner's response, completes the
identity binding, and issues the dual-identity credential to the
agent via the proxy (steps 3 and 4).
+----------------------------+(a)challenge +---- --+
| +--------------> |
| Identity Server <--------------+ Owner |
| |(b)signature | |
+-------------- ^ +----------+ +---- --+
(2)| |(3)
+-----------------+-+-----------------------------------+
| Trust Domain | | |
| +---------------+-v----------+ (1) +-------+ |
| | | |--------------+ | |
| |Identity Proxy| Agent API |--------------> Agent | |
| | | | (4) | | |
| +----------------------------+ +-------+ |
+-------------------------------------------------------+
_Figure 4: Server-Mediate Model_
* Typical Application Scenarios: This model is suitable for
scenarios requiring independent and real-time confirmation from an
owner who is not involved in the initial request path. For
instance, An agent is deployed by a service provider on behalf of
an organization. When the agent requests an identity credential,
the server initiates an out-of-band verification directly to the
administrative center.
* Attack Surface: The primary risk lies in the out-of-band channel.
Without nonces or mutual authentication, an attacker could
intercept this channel to perform response forgery or replay
attacks.
5. Comparison with CHEQ
While both this document and CHEQ [I-D.draft-rosenberg-cheq-00]
introduce a human element to enhance security, their goals and the
underlying mechanisms are different.
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CHEQ focuses primarily on controlling the actions of AI agents. It
requires user double confirmation when an AI Agent invokes an OAuth
access token request, preventing possible deviation from user
expectations.
The purpose of this document is to provide distinct identity and
credentials to AI agents, whether or not it is bound to an owner user
of device's parent identity. Whether or not the agent inherits
access permission privileges from its user is out of scope of this
document.
6. Initial Trust Establishment
AI agents may operate in cloud or campus. In the cloud, the initial
trust establishment between the proxy and the server has already been
solved by solutions like SPIRE. However, in campus scenarios, the
heterogeneity and limited manageability of devices make credential
provisioning challenging, complicating initial trust establishment.
BRSKI [RFC8995] provides a feasible method by introducing a
cryptographically signed artifact called "voucher".
In the BRSKI flow, the proxy (acting as a BRSKI pledge) discovers the
server (acting as a BRSKI registrar), initiates a TLS handshake, and
sends a voucher request including its immutable manufacturer
credential-the IDevID (Initial Device Identifier). The server uses
this IDevID to contact the manufacturer's service (MASA). After
validating the request, the MASA issues a signed voucher.
The proxy then verifies the manufacturer's signature on the voucher,
which securely transferring trust from the manufacturer to the local
domain. This verified trust is a prerequisite for the server to
issue a local domain device certificate (LDevID). This certificate
enrollment step essentially follows the standard EST mechanism
[RFC7030].
However, it should be noted that BRSKI is not necessarily the only
way to achieve this secure integration. The core goal is to bridge
the initial trust gap. If the proxy is pre-configured with the
target server's public key or certificate and can securely locate it,
the standard EST protocol alone may be sufficient to establish trust
and obtain the LDevID certificate.
*Open Question:* What are the precise conditions and mechanisms for
determining the use of various bootstrap methods (including but not
limited to BRSKI and EST)?
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7. Security Considerations
TODO Security
8. IANA Considerations
This document has no IANA actions.
9. References
9.1. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119,
DOI 10.17487/RFC2119, March 1997,
<https://www.rfc-editor.org/rfc/rfc2119>.
[RFC7030] Pritikin, M., Ed., Yee, P., Ed., and D. Harkins, Ed.,
"Enrollment over Secure Transport", RFC 7030,
DOI 10.17487/RFC7030, October 2013,
<https://www.rfc-editor.org/rfc/rfc7030>.
[RFC8174] Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC
2119 Key Words", BCP 14, RFC 8174, DOI 10.17487/RFC8174,
May 2017, <https://www.rfc-editor.org/rfc/rfc8174>.
[RFC8995] Pritikin, M., Richardson, M., Eckert, T., Behringer, M.,
and K. Watsen, "Bootstrapping Remote Secure Key
Infrastructure (BRSKI)", RFC 8995, DOI 10.17487/RFC8995,
May 2021, <https://www.rfc-editor.org/rfc/rfc8995>.
9.2. Informative References
[A2A-SPEC] "Agent2Agent (A2A) Protocol Specifications", October 2025,
<https://a2a-protocol.org/latest/topics/enterprise-
ready/>.
[I-D.draft-messous-eat-ai-01]
MESSOUS, A., Morand, L., and P. C. Liu, "Entity
Attestation Token (EAT) Profile for Autonomous AI Agents",
Work in Progress, Internet-Draft, draft-messous-eat-ai-01,
23 February 2026, <https://datatracker.ietf.org/doc/html/
draft-messous-eat-ai-01>.
[I-D.draft-rosenberg-cheq-00]
Rosenberg, J., White, P., and C. F. Jennings, "CHEQ: A
Protocol for Confirmation AI Agent Decisions with Human in
the Loop (HITL)", Work in Progress, Internet-Draft, draft-
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rosenberg-cheq-00, 24 July 2025,
<https://datatracker.ietf.org/doc/html/draft-rosenberg-
cheq-00>.
[I-D.ietf-wimse-arch-06]
Salowey, J. A., Rosomakho, Y., and H. Tschofenig,
"Workload Identity in a Multi System Environment (WIMSE)
Architecture", Work in Progress, Internet-Draft, draft-
ietf-wimse-arch-06, 30 September 2025,
<https://datatracker.ietf.org/doc/html/draft-ietf-wimse-
arch-06>.
Acknowledgments
TODO acknowledge.
Authors' Addresses
Yuan Ni
Huawei
Email: niyuan1@huawei.com
Chunchi Peter Liu
Huawei
Email: liuchunchi@huawei.com
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