]> Transmute

orie@transmute.industries

mesur.io

mprorock@mesur.io

mavennet

mahmoud@mavennet.com

Security Secure Patterns for Internet CrEdentials digitial credentials data model profiles policy guidance Digital Credentials are frequently modeled on documents, forms, and messages that enable a holder to prove they have attributes that are acceptable to a verifier. This document provides guidance to verifiers enabling them to describe their requirements such that they can be translated into digital credential profiles. About This Document The latest revision of this draft can be found at . Status information for this document may be found at . Discussion of this document takes place on the Secure Patterns for Internet CrEdentials Working Group mailing list (), which is archived at . Subscribe at . Source for this draft and an issue tracker can be found at .

Introduction Verifiers have digital credential requirements that reduce their liability, improve their transaction throughput, comply with local, regional, or international laws, and support their environmental, social and governance objectives and values. Requirements are often expressed as "Policy Documents", and furnished to holders, to enable them to easily comply. For example, sometimes to receive a new credential, a holder may need to present one or more existing credentials, and different regional agencies might have unique requirements regarding the quality, age, and issuing authority of these credentials. Not all the attributes of a credential may be necessary to disclose, and the details of the serialization are often less relevant to the verifier than the authenticity and integrity of the credential attributes. Verifiers need to update their policies as new credential formats become available, but still need to ensure that mandatory attributes are disclosed, even while changing the securing mechanisms and serialization details. Depending on how a verifier wrote their policy, the process of updating it to take advantage of new capabilities, safer cryptography, smaller message sizes, or advances in data minimization, can be difficult. This document provides guidance to policy writers, enabling them to construct policies that can be translated into human and machine verifiable profiles, enabling digital credential formats to evolve with the speed and precision at which policies can be written. It strives to concretely provide a means for "improving ways of working between policy experts and technical experts" Policy experts are IETF stakeholders

Terminology The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in BCP 14 when, and only when, they appear in all capitals, as shown here.

Ontology:

a set of concepts and categories in a subject area or domain that shows their properties and the relations between them. (oxford dictionary citation fixme)

Ontologies Verifiers can share their view of a subject area or domain by acknowledging or leveraging ontologies. Ontologies can be leveraged to model information requirements, with or without requiring the data format to explicitly encode the ontology or leverage the ontology directly in the construction of digital credentials. For example, the ontology defined in can be used to describe the information required in a digital credential for RFCs, without requiring the digital credential to contain the literal strings used to serialize the ontology, for example the string: "ftp://shalmaneser.org/rfc#area", need not be present, so long as the verifier describes that the string "area" is equivalent in their profile text. Policy writers SHOULD distinguish between the information they require, and the ontologies that can express the concepts needed to understand the information.

Information vs Data Information is abstract, we can express the same information in many different ways, including in many different serializations. The following statement for example, expresses information: That can also be expressed in different data structures, while preserving the information: in JSON: Verifiers can write policies that mandate a single method to encode information in a serialization and allow only one serialization. This can reduce both the cost to implement and the attack surface associated with the digital credentials that are acceptable to the verifier. However, if a new serialization is invented, that is simpler to support, and more directly aligns with the values of the verifier and their mission objectives, having such a policy could prevent the verifier from adopting the new and improved serialization, even if it secures the same information and provides additional benefits, beyond integrity and authenticity, such as compactness, reduced computation and storage costs, or safer formal modeling capabilities. Policy writers SHOULD distinguish between the information they require, and the acceptable serializations that can express this information required.

Schema vs Definition Once a verifier has documented their information requirements, and selected data formats capable of expressing the required information while satisfying their policies and values, the details of the acceptable data format SHOULD be considered. There are a number of subtle details regarding octet encodings that can lead to security or performance issues in digital credential formats. For example, understanding the allowed data types for expressing information, be it an integer, a floating point number, a string, or a boolean value. Policy writers SHOULD describe the allowed data types for the expression of information, and SHOULD NOT support polymorphic types. Schema or data definition languages such as SHOULD be used when describing acceptable expressions of information models, so that validation of data instances can be automated.

Designing Data Structures Although schema or data definition languages can help address some common security issues such as validation as described in , there are still problematic expressions of information which should generally be avoided even when fully specifying data. Most commonly deeply nested data structures, or lists of deeply nested data structures containing lists. Most digital credentials are about asserting attributes of a subject, in a way that is secured by the issuer, and provable by the holder. This can naturally be expressed using a simple map data type. int, ; age ? &(age: 2) => int, } ]]> Strings and arbitrary length data structures SHOULD be avoided, whenever possible. As the issuer secures the data, the interpretation of the data is always in the context of:

1. the definitions published by the issuer.
2. the data the issuer chose to secure that expresses the information.

Policy writers SHOULD leverage tabular data structures (tables, csv) whenever possible. Policy writers SHOULD externalize definitions of data structures wherever possible, and use those external definitions to generate relevant sections of the policy document. Policy writers SHOULD ensure that output documents are computer readable, and that when tabular data is embedded in a policy document, that it is clearly separated from other sections of tabular data. Documents SHOULD be sectioned by logical concepts, and document sections dealing with the description of data structures SHOULD be clearly identifed and not mixed with other data structure descriptions without clear separation. Policy writers SHOULD clearly version policy documents, and SHOULD clearly identify the date of publication, start date of applicabiilty of the policy, and if known, the end date of applicability. Policy writers SHOULD clearly define the scope of the policy, and the audience to which the policy applies to. These scope and audience definitions SHOULD take place in their own sections. Policy writers SHOULD restrict what data is expressed in a digital credential and how the data is expressed not just the information that is required to be present. Policy writers SHOULD avoid making recommendations where the same information may be conveyed in many different, but equivalent data structures. When leveraging CBOR, SHOULD be used. Policy writers should avoid creating "frameworks" where interoperability is not immediately available .

Security Considerations TODO Security

Cryptographic Agility TODO Cryptographic Agility Registries / Pick at least 2, use at least N bit security... avoid MUST support.... recommend AT LEAST support.

Internationalized Names TODO Internationalized Names Strings / domain names... Unicode.

Exploiting Data Validation Max depth exceeded in JSON, cannonicalization timeout in XML / JSON-LD, similar issues with large CBOR structures.

IANA Considerations This document has no IANA actions.

References Normative References This Glossary provides definitions, abbreviations, and explanations of terminology for information system security. The 334 pages of entries offer recommendations to improve the comprehensibility of written material that is generated in the Internet Standards Process (RFC 2026). The recommendations follow the principles that such writing should (a) use the same term or definition whenever the same concept is mentioned; (b) use terms in their plainest, dictionary sense; (c) use terms that are already well-established in open publications; and (d) avoid terms that either favor a particular vendor or favor a particular technology or mechanism over other, competing techniques that already exist or could be developed. This memo provides information for the Internet community. This document proposes a notational convention to express Concise Binary Object Representation (CBOR) data structures (RFC 7049). Its main goal is to provide an easy and unambiguous way to express structures for protocol messages and data formats that use CBOR or JSON. This document discusses aspects of centralization that relate to Internet standards efforts. It argues that, while standards bodies have a limited ability to prevent many forms of centralization, they can still make contributions that assist in the decentralization of the Internet. Universität Bremen TZI CBOR (STD 94, RFC 8949) defines "Deterministically Encoded CBOR" in its Section 4.2, providing some flexibility for application specific decisions. To facilitate Deterministic Encoding to be offered as a selectable feature of generic encoders, the present document defines a CBOR Common Deterministic Encoding (CDE) Profile that can be shared by a large set of applications with potentially diverging detailed requirements. This document also introduces the concept of Application Profiles, which are layered on top of the CBOR CDE Profile and can address more application specific requirements. Application Profiles are defined in separate documents. In many standards track documents several words are used to signify the requirements in the specification. These words are often capitalized. This document defines these words as they should be interpreted in IETF documents. This document specifies an Internet Best Current Practices for the Internet Community, and requests discussion and suggestions for improvements. RFC 2119 specifies common key words that may be used in protocol specifications. This document aims to reduce the ambiguity by clarifying that only UPPERCASE usage of the key words have the defined special meanings. Informative References Impedance Mismatch LLC This document defines an ontology that describes the specifications published by the RFC Editor, together with ancillary documents.

Informative References [I_D.draft-hoffmann-gendispatch-policy-stakeholders] "Policy experts are IETF stakeholders", Work in Progress, Internet-Draft, draft-hoffmann-gendispatch-policy-stakeholders-03, 10 January 2024, https://datatracker.ietf.org/doc/html/draft-hoffmann-gendispatch-policy-stakeholders-03

Acknowledgments TODO acknowledge.