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JSON Canonicalization Scheme (JCS)
draft-rundgren-json-canonicalization-scheme-04

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This is an older version of an Internet-Draft that was ultimately published as RFC 8785.
Authors Anders Rundgren , Bret Jordan , Samuel Erdtman
Last updated 2019-02-06
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draft-rundgren-json-canonicalization-scheme-04
Network Working Group                                        A. Rundgren
Internet-Draft                                               Independent
Intended status: Standards Track                               B. Jordan
Expires: August 10, 2019                            Symantec Corporation
                                                              S. Erdtman
                                                              Spotify AB
                                                        February 6, 2019

                   JSON Canonicalization Scheme (JCS)
             draft-rundgren-json-canonicalization-scheme-04

Abstract

   Cryptographic operations like hashing and signing requires that the
   original data does not change during serialization or parsing.  By
   applying the rules defined by the JSON Canonicalization Scheme (JCS),
   data provided in JSON [RFC8259] format can be exchanged "as is",
   while still being usable by secure cryptographic operations.  JCS
   achieves this by building on the serialization formats for JSON
   primitives as defined by ECMAScript [ES6], constraining JSON data to
   the I-JSON [RFC7493] subset, and through a platform independent
   property sorting scheme.

   The intended audiences of this document are JSON tool vendors, as
   well as designers of JSON based cryptographic solutions.

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF).  Note that other groups may also distribute
   working documents as Internet-Drafts.  The list of current Internet-
   Drafts is at https://datatracker.ietf.org/drafts/current/.

   Internet-Drafts are draft documents valid for a maximum of six months
   and may be updated, replaced, or obsoleted by other documents at any
   time.  It is inappropriate to use Internet-Drafts as reference
   material or to cite them other than as "work in progress."

   This Internet-Draft will expire on August 10, 2019.

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Copyright Notice

   Copyright (c) 2019 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents
   (https://trustee.ietf.org/license-info) in effect on the date of
   publication of this document.  Please review these documents
   carefully, as they describe your rights and restrictions with respect
   to this document.  Code Components extracted from this document must
   include Simplified BSD License text as described in Section 4.e of
   the Trust Legal Provisions and are provided without warranty as
   described in the Simplified BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
   2.  Terminology . . . . . . . . . . . . . . . . . . . . . . . . .   4
   3.  Detailed Operation  . . . . . . . . . . . . . . . . . . . . .   4
     3.1.  Creation of Input Data  . . . . . . . . . . . . . . . . .   4
     3.2.  Generation of Canonical JSON Data . . . . . . . . . . . .   5
       3.2.1.  Whitespace  . . . . . . . . . . . . . . . . . . . . .   5
       3.2.2.  Serialization of Primitive Data Types . . . . . . . .   5
         3.2.2.1.  Serialization of Literals . . . . . . . . . . . .   6
         3.2.2.2.  Serialization of Strings  . . . . . . . . . . . .   6
         3.2.2.3.  Serialization of Numbers  . . . . . . . . . . . .   6
       3.2.3.  Sorting of Object Properties  . . . . . . . . . . . .   7
       3.2.4.  UTF-8 Generation  . . . . . . . . . . . . . . . . . .   8
   4.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .   8
   5.  Security Considerations . . . . . . . . . . . . . . . . . . .   9
   6.  Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .   9
   7.  References  . . . . . . . . . . . . . . . . . . . . . . . . .   9
     7.1.  Normative References  . . . . . . . . . . . . . . . . . .   9
     7.2.  Informal References . . . . . . . . . . . . . . . . . . .  10
     7.3.  URIs  . . . . . . . . . . . . . . . . . . . . . . . . . .  10
   Appendix A.  ES6 Sample Canonicalizer . . . . . . . . . . . . . .  11
   Appendix B.  Number Serialization Samples . . . . . . . . . . . .  12
   Appendix C.  Canonicalized JSON as "Wire Format"  . . . . . . . .  14
   Appendix D.  Dealing with Big Numbers . . . . . . . . . . . . . .  15
   Appendix E.  String Subtype Handling  . . . . . . . . . . . . . .  15
     E.1.  Immutable String Method . . . . . . . . . . . . . . . . .  17
     E.2.  Data Normalization Method . . . . . . . . . . . . . . . .  17
     E.3.  Subtypes in Arrays  . . . . . . . . . . . . . . . . . . .  18
   Appendix F.  Implementation Guidelines  . . . . . . . . . . . . .  18
   Appendix G.  Open Source Implementations  . . . . . . . . . . . .  19
   Appendix H.  Other JSON Canonicalization Efforts  . . . . . . . .  20
   Appendix I.  Development Portal . . . . . . . . . . . . . . . . .  20

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   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  20

1.  Introduction

   Cryptographic operations like hashing and signing requires that the
   original data does not change during serialization or parsing.  One
   way of accomplishing this is converting the data into a format that
   has a simple and fixed representation like Base64Url [RFC4648], which
   is how JWS [RFC7515] addressed this issue.

   Another solution is to create a canonical version of the data,
   similar to what was done for the XML Signature [XMLDSIG] standard.
   The primary advantage with a canonicalizing scheme is that data can
   be kept in its original form.  This is the core rationale behind JCS.
   Put another way: by using canonicalization a JSON Object may remain a
   JSON Object even after being signed which simplifies system design,
   documentation and logging.

   To avoid "reinventing the wheel", JCS relies on serialization of JSON
   primitives compatible with ECMAScript (aka JavaScript) beginning with
   version 6 [ES6], hereafter referred to as "ES6".

   Seasoned XML developers recalling difficulties getting signatures to
   validate (usually due to different interpretations of the quite
   intricate XML canonicalization rules as well as of the equally
   extensive Web Services security standards), may rightfully wonder why
   JCS would not suffer from similar issues.  The reasons are twofold:

   o  The absence of a namespace concept and default values, as well as
      constraining data to the I-JSON subset eliminate the need for
      specific number parsing schemes for dealing with canonicalization.

   o  JCS compatible serialization of JSON primitives is supported by
      most current Web browsers and as well as by Node.js [NODEJS],
      while the full JCS specification is supported by multiple Open
      Source implementations (see Appendix G).  See also Appendix F.

   In summary, the JCS specification describes how serialization of JSON
   primitives compliant with ES6, combined with an elementary property
   sorting scheme, can be used for supporting "Hashable" JSON.  Note
   that "true" canonicalization is an optional JCS feature, usually not
   needed for cryptographic operations.  See Appendix E for details.

   JCS is compatible with some existing systems relying on JSON
   canonicalization such as JWK Thumbprint [RFC7638] and Keybase
   [KEYBASE].

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2.  Terminology

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   "SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and
   "OPTIONAL" in this document are to be interpreted as described in BCP
   14 [RFC2119] [RFC8174] when, and only when, they appear in all
   capitals, as shown here.

3.  Detailed Operation

   This section describes the different issues related to creating a
   canonical JSON representation, and how they are addressed by JCS.

3.1.  Creation of Input Data

   In order to serialize JSON data, one needs data that is adapted for
   JSON serialization.  This is usually achieved by:

   o  Parsing previously generated JSON data.

   o  Programmatically creating data.

   Irrespective of the method used, the data to be serialized MUST be
   compatible both with ES6 and I-JSON [RFC7493], which implies the
   following:

   o  There MUST NOT be any duplicate property names within an element
      to be serialized as a JSON Object.

   o  String data MUST be expressible as Unicode [UNICODE].

   o  Numeric data MUST be expressible as IEEE-754 [IEEE754] double
      precision values.  For applications needing higher precision or
      longer integers than offered by IEEE-754 double precision,
      Appendix D outlines how such requirements can be supported in an
      interoperable and extensible way.

   Note: parsed String data MUST NOT be altered during subsequent
   serializations.  For more information see Appendix E.

   Note: although the Unicode standard offers a possibility combining
   certain characters into one, referred to as "Unicode Normalization"
   (https://www.unicode.org/reports/tr15/ [1]), such functionality MUST
   be delegated to the application layer.

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3.2.  Generation of Canonical JSON Data

   The following subsections describe the steps required for creating a
   canonical JSON representation of the data elaborated on in the
   previous section.

   Appendix A shows sample code for an ES6 based canonicalizer, matching
   the JCS specification.

3.2.1.  Whitespace

   Whitespace between JSON elements MUST NOT be emitted.

3.2.2.  Serialization of Primitive Data Types

   Assume that you parse a JSON object like the following:

     {
       "numbers": [333333333.33333329, 1E30, 4.50,
                   2e-3, 0.000000000000000000000000001],
       "string": "\u20ac$\u000F\u000aA'\u0042\u0022\u005c\\\"\/",
       "literals": [null, true, false]
     }

   If you subsequently serialize the parsed data using a serializer
   compliant with ES6's "JSON.stringify()", the result would (with a
   line wrap added for display purposes only), be rather divergent with
   respect to representation of data:

     {"numbers":[333333333.3333333,1e+30,4.5,0.002,1e-27],"string":
     "\u20ac$\u000f\nA'B\"\\\\\"/","literals":[null,true,false]}

      Note: \u20ac denotes the Euro character, which not
      being ASCII, is currently not displayable in RFCs.

   The reason for the difference between the parsed data and its
   serialized counterpart, is due to a wide tolerance on input data (as
   defined by JSON [RFC8259]), while output data (as defined by ES6),
   has a fixed representation.  As can be seen by the example, numbers
   are subject to rounding as well.

   The following subsections describe serialization of primitive JSON
   data types according to JCS.  This part is identical to that of ES6.

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3.2.2.1.  Serialization of Literals

   The JSON literals "null", "true", and "false" present no challenge
   since they already have a fixed definition in JSON [RFC8259].

3.2.2.2.  Serialization of Strings

   For JSON String data (which includes JSON Object property names as
   well), each character MUST be serialized as described below (also
   matching Section 24.3.2.2 of [ES6]):

   o  If the Unicode value falls within the traditional ASCII control
      character range (U+0000 through U+001F), it MUST be serialized
      using lowercase hexadecimal Unicode notation (\uhhhh) unless it is
      in the set of predefined JSON control characters U+0008, U+0009,
      U+000A, U+000C or U+000D which MUST be serialized as \b, \t, \n,
      \f and \r respectively.

   o  If the Unicode value is outside of the ASCII control character
      range, it MUST be serialized "as is" unless it is equivalent to
      U+005C (\) or U+0022 (") which MUST be serialized as \\ and \"
      respectively.

   Finally, the serialized string value MUST be enclosed in double
   quotes (").

   Note: some JSON systems permit the use of invalid Unicode data
   including "lone surrogates" (e.g.  U+DEAD).  Since this leads to
   interoperability issues including broken signatures, occurrences of
   such data MUST cause the JCS algorithm to terminate with an error
   indication.

3.2.2.3.  Serialization of Numbers

   JSON data of type Number MUST be serialized according to
   Section 7.1.12.1 of [ES6] including the "Note 2" enhancement.

   Due to the relative complexity of this part, the algorithm itself is
   not included in this document.  However, the specification is fully
   implemented by for example Google's V8 [V8].  The open source Java
   implementation mentioned in Appendix G uses a recently developed
   number serialization algorithm called Ryu [RYU].

   ES6 builds on the IEEE-754 [IEEE754] double precision standard for
   representing JSON Number data.  Appendix B holds a set of IEEE-754
   sample values and their corresponding JSON serialization.

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3.2.3.  Sorting of Object Properties

   Although the previous step indeed normalized the representation of
   primitive JSON data types, the result would not qualify as
   "canonical" since JSON Object properties are not in lexicographic
   (alphabetical) order.

   Applied to the sample in Section 3.2.2, a properly canonicalized
   version should (with a line wrap added for display purposes only),
   read as:

     {"literals":[null,true,false],"numbers":[333333333.3333333,
     1e+30,4.5,0.002,1e-27],"string":"\u20ac$\u000f\nA'B\"\\\\\"/"}

      Note: \u20ac denotes the Euro character, which not
      being ASCII, is currently not displayable in RFCs.

   The rules for lexicographic sorting of JSON Object properties
   according to JCS are as follows:

   o  JSON Object properties MUST be sorted in a recursive manner which
      means that possible JSON child Objects MUST have their properties
      sorted as well.

   o  JSON Array data MUST also be scanned for presence of JSON Objects
      (and applying associated property sorting), but array element
      order MUST NOT be changed.

   When a JSON Object is about to have its properties sorted, the
   following measures MUST be adhered to:

   o  The sorting process is applied to property strings in their "raw"
      (unescaped) form.  That is, a newline character is treated as
      U+000A.

   o  Property strings to be sorted are formatted as arrays of UTF-16
      [UNICODE] code units.  The sorting is based on pure value
      comparisons, where code units are treated as unsigned integers,
      independent of locale settings.

   o  Property strings either have different values at some index that
      is a valid index for both strings, or their lengths are different,
      or both.  If they have different values at one or more index
      positions, let k be the smallest such index; then the string whose
      value at position k has the smaller value, as determined by using
      the < operator, lexicographically precedes the other string.  If
      there is no index position at which they differ, then the shorter
      string lexicographically precedes the longer string.

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   o  In plain English this means that property names are sorted in
      ascending order like the following:

           ""
           "a"
           "aa"
           "ab"

   The rationale for basing the sort algorithm on UTF-16 code units is
   that it maps directly to the string type in ECMAScript (includes Web
   browsers), Java and .NET.  Systems using another internal
   representation of string data will need to convert JSON property
   strings into arrays of UTF-16 code units before sorting.  The
   conversion from UTF-8 or UTF-32 to UTF-16 is defined by the Unicode
   [UNICODE] standard.

   Note: for the purpose of obtaining a deterministic property order,
   sorting on UTF-8 or UTF-32 encoded data would also work, but the
   result would differ (and thus be incompatible with this
   specification).

3.2.4.  UTF-8 Generation

   Finally, in order to create a platform independent representation,
   the resulting JSON string data MUST be encoded in UTF-8.

   Applied to the sample in Section 3.2.3 this should yield the
   following bytes here shown in hexadecimal notation:

     7b 22 6c 69 74 65 72 61 6c 73 22 3a 5b 6e 75 6c 6c 2c 74 72
     75 65 2c 66 61 6c 73 65 5d 2c 22 6e 75 6d 62 65 72 73 22 3a
     5b 33 33 33 33 33 33 33 33 33 2e 33 33 33 33 33 33 33 2c 31
     65 2b 33 30 2c 34 2e 35 2c 30 2e 30 30 32 2c 31 65 2d 32 37
     5d 2c 22 73 74 72 69 6e 67 22 3a 22 e2 82 ac 24 5c 75 30 30
     30 66 5c 6e 41 27 42 5c 22 5c 5c 5c 5c 5c 22 2f 22 7d

   This data is intended to be usable as input to cryptographic methods.

   For other uses see Appendix C.

4.  IANA Considerations

   This document has no IANA actions.

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5.  Security Considerations

   It is vital performing "sanity" checks on input data to avoid
   overflowing buffers and similar things that could affect the
   integrity of the system.

6.  Acknowledgements

   Building on ES6 Number serialization was originally proposed by James
   Manger.  This ultimately led to the adoption of the entire ES6
   serialization scheme for JSON primitives.

   Other people who have contributed with valuable input to this
   specification include Bron Gondwana, Jim Schaad, John-Mark Gurney,
   Mark Nottingham, Mike Jones, Mike Miller, Mike Samuel, Michal Wadas,
   Richard Gibson, Robert Tupelo-Schneck and Scott Ananian.

7.  References

7.1.  Normative References

   [ES6]      Ecma International, "ECMAScript 2015 Language
              Specification", <https://www.ecma-international.org/ecma-
              262/6.0/index.html>.

   [IEEE754]  IEEE, "IEEE Standard for Floating-Point Arithmetic",
              August 2008, <http://grouper.ieee.org/groups/754/>.

   [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/info/rfc2119>.

   [RFC7493]  Bray, T., Ed., "The I-JSON Message Format", RFC 7493,
              DOI 10.17487/RFC7493, March 2015,
              <https://www.rfc-editor.org/info/rfc7493>.

   [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/info/rfc8174>.

   [RFC8259]  Bray, T., Ed., "The JavaScript Object Notation (JSON) Data
              Interchange Format", STD 90, RFC 8259,
              DOI 10.17487/RFC8259, December 2017,
              <https://www.rfc-editor.org/info/rfc8259>.

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   [UNICODE]  The Unicode Consortium, "The Unicode Standard, Version
              10.0.0",
              <https://www.unicode.org/versions/Unicode10.0.0/>.

7.2.  Informal References

   [KEYBASE]  "Keybase",
              <https://keybase.io/docs/api/1.0/canonical_packings#json>.

   [NODEJS]   "Node.js", <https://nodejs.org>.

   [OPENAPI]  "The OpenAPI Initiative", <https://www.openapis.org/>.

   [RFC4648]  Josefsson, S., "The Base16, Base32, and Base64 Data
              Encodings", RFC 4648, DOI 10.17487/RFC4648, October 2006,
              <https://www.rfc-editor.org/info/rfc4648>.

   [RFC7515]  Jones, M., Bradley, J., and N. Sakimura, "JSON Web
              Signature (JWS)", RFC 7515, DOI 10.17487/RFC7515, May
              2015, <https://www.rfc-editor.org/info/rfc7515>.

   [RFC7638]  Jones, M. and N. Sakimura, "JSON Web Key (JWK)
              Thumbprint", RFC 7638, DOI 10.17487/RFC7638, September
              2015, <https://www.rfc-editor.org/info/rfc7638>.

   [RYU]      Ulf Adams, "Ryu floating point number serializing
              algorithm", <https://github.com/ulfjack/ryu>.

   [V8]       Google LLC, "Chrome V8 Open Source JavaScript Engine",
              <https://developers.google.com/v8/>.

   [XMLDSIG]  W3C, "XML Signature Syntax and Processing Version 1.1",
              <https://www.w3.org/TR/xmldsig-core1/>.

7.3.  URIs

   [1] https://www.unicode.org/reports/tr15/

   [2] https://www.npmjs.com/package/canonicalize

   [3] https://github.com/erdtman/java-json-canonicalization

   [4] https://github.com/cyberphone/json-canonicalization/tree/master/
       go

   [5] https://github.com/cyberphone/json-canonicalization/tree/master/
       dotnet

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   [6] https://github.com/cyberphone/json-canonicalization/tree/master/
       python3

   [7] https://tools.ietf.org/html/draft-staykov-hu-json-canonical-
       form-00

   [8] https://gibson042.github.io/canonicaljson-spec/

   [9] http://wiki.laptop.org/go/Canonical_JSON

   [10] https://github.com/cyberphone/ietf-json-canon

   [11] https://cyberphone.github.io/ietf-json-canon

   [12] https://github.com/cyberphone/json-canonicalization

Appendix A.  ES6 Sample Canonicalizer

   Below is a functionally complete example of a JCS compliant
   canonicalizer for usage with ES6 based systems.

   Note: the primary purpose of this code is highlighting the
   canonicalization algorithm.  Using the full power of ES6 would reduce
   the code size considerably but would also be more difficult to follow
   by non-experts.

     var canonicalize = function(object) {

         var buffer = '';
         serialize(object);
         return buffer;

         function serialize(object) {
             if (object === null || typeof object !== 'object' ||
                 object.toJSON != null) {
                 /////////////////////////////////////////////////
                 // Primitive type or toJSON - Use ES6/JSON     //
                 /////////////////////////////////////////////////
                 buffer += JSON.stringify(object);

             } else if (Array.isArray(object)) {
                 /////////////////////////////////////////////////
                 // Array - Maintain element order              //
                 /////////////////////////////////////////////////
                 buffer += '[';
                 let next = false;
                 object.forEach((element) => {
                     if (next) {

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                         buffer += ',';
                     }
                     next = true;
                     /////////////////////////////////////////
                     // Array element - Recursive expansion //
                     /////////////////////////////////////////
                     serialize(element);
                 });
                 buffer += ']';

             } else {
                 /////////////////////////////////////////////////
                 // Object - Sort properties before serializing //
                 /////////////////////////////////////////////////
                 buffer += '{';
                 let next = false;
                 Object.keys(object).sort().forEach((property) => {
                     if (next) {
                         buffer += ',';
                     }
                     next = true;
                     ///////////////////////////////////////////////
                     // Property names are strings - Use ES6/JSON //
                     ///////////////////////////////////////////////
                     buffer += JSON.stringify(property);
                     buffer += ':';
                     //////////////////////////////////////////
                     // Property value - Recursive expansion //
                     //////////////////////////////////////////
                     serialize(object[property]);
                 });
                 buffer += '}';
             }
         }
     };

Appendix B.  Number Serialization Samples

   The following table holds a set of ES6 compatible Number
   serialization samples, including some edge cases.  The column "IEEE-
   754" refers to the internal ES6 representation of the Number data
   type which is based on the IEEE-754 [IEEE754] standard using 64-bit
   (double precision) values, here expressed in hexadecimal.

  |====================================================================|
  |     IEEE-754     |   JSON Representation     |       Comment       |
  |====================================================================|
  | 0000000000000000 | 0                         | Zero                |

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  |--------------------------------------------------------------------|
  | 8000000000000000 | 0                         | Minus zero          |
  |--------------------------------------------------------------------|
  | 0000000000000001 | 5e-324                    | Smallest pos number |
  |--------------------------------------------------------------------|
  | 8000000000000001 | -5e-324                   | Smallest neg number |
  |--------------------------------------------------------------------|
  | 7fefffffffffffff | 1.7976931348623157e+308   | Largest pos number  |
  |--------------------------------------------------------------------|
  | ffefffffffffffff | -1.7976931348623157e+308  | Largest neg number  |
  |--------------------------------------------------------------------|
  | 4340000000000000 | 9007199254740992          | Largest pos integer |
  |--------------------------------------------------------------------|
  | c340000000000000 | -9007199254740992         | Largest neg integer |
  |--------------------------------------------------------------------|
  | 7fffffffffffffff |                           | NaN - Invalid       |
  |--------------------------------------------------------------------|
  | 7ff0000000000000 |                           | Infinity - Invalid  |
  |--------------------------------------------------------------------|
  | 44b52d02c7e14af5 | 9.999999999999997e+22     |                     |
  |--------------------------------------------------------------------|
  | 44b52d02c7e14af6 | 1e+23                     |                     |
  |--------------------------------------------------------------------|
  | 44b52d02c7e14af7 | 1.0000000000000001e+23    |                     |
  |--------------------------------------------------------------------|
  | 444b1ae4d6e2ef4e | 999999999999999700000     |                     |
  |--------------------------------------------------------------------|
  | 444b1ae4d6e2ef4f | 999999999999999900000     |                     |
  |--------------------------------------------------------------------|
  | 3eb0c6f7a0b5ed8d | 0.000001                  |                     |
  |--------------------------------------------------------------------|
  | 3eb0c6f7a0b5ed8c | 9.999999999999997e-7      |                     |
  |--------------------------------------------------------------------|
  | 41b3de4355555553 | 333333333.3333332         |                     |
  |--------------------------------------------------------------------|
  | 41b3de4355555554 | 333333333.33333325        |                     |
  |--------------------------------------------------------------------|
  | 41b3de4355555555 | 333333333.3333333         |                     |
  |--------------------------------------------------------------------|
  | 41b3de4355555556 | 333333333.3333334         |                     |
  |--------------------------------------------------------------------|
  | 41b3de4355555557 | 333333333.33333343        |                     |
  |--------------------------------------------------------------------|
  | becbf647612f3696 | -0.0000033333333333333333 |                     |
  |--------------------------------------------------------------------|

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   Note: for maximum compliance with ECMAScript's "JSON" object, values
   that are to be interpreted as true integers, SHOULD be in the range
   -9007199254740991 to 9007199254740991.

   Note: since NaN (Not a Number) and Infinity are not permitted in
   JSON, occurrences of such values MUST cause the JCS algorithm to
   terminate with an error indication.

   Note: although a set of specific integers like 2**68
   (4430000000000000 in IEEE-754 format) could be regarded as having
   extended precision, the JCS/ES6 number serialization algorithm does
   not take this in consideration.

Appendix C.  Canonicalized JSON as "Wire Format"

   Since the result from the canonicalization process (see
   Section 3.2.4), is fully valid JSON, it can also be used as
   "Wire Format".  However, this is just an option since cryptographic
   schemes based on JCS, in most cases would not depend on that
   externally supplied JSON data already is canonicalized.

   In fact, the ES6 standard way of serializing objects using
   "JSON.stringify()" produces a more "logical" format, where properties
   are kept in the order they were created or received.  The example
   below shows an address record which could benefit from ES6 standard
   serialization:

     {
       "name": "John Doe",
       "address": "2000 Sunset Boulevard",
       "city": "Los Angeles",
       "zip": "90001",
       "state": "CA"
     }

   Using canonicalization the properties above would be output in the
   order "address", "city", "name", "state" and "zip", which adds
   fuzziness to the data from a human (developer or technical support),
   perspective.

   That is, for many applications, canonicalization would only be used
   internally for creating a "hashable" representation of the data
   needed for cryptographic operations.

   Note: if message size is not a concern, you may even send
   "Pretty Printed" JSON data on the wire (since whitespace always is
   ignored by the canonicalization process).

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Appendix D.  Dealing with Big Numbers

   There are several issues associated with the JSON Number type, here
   illustrated by the following sample object:

     {
       "giantNumber": 1.4e+9999,
       "payMeThis": 26000.33,
       "int64Max": 9223372036854775807
     }

   Although the sample above conforms to JSON (according to [RFC8259]),
   applications would normally use different native data types for
   storing "giantNumber" and "int64Max".  In addition, monetary data
   like "payMeThis" would presumably not rely on floating point data
   types due to rounding issues with respect to decimal arithmetic.

   The established way handling this kind of "overloading" of the JSON
   Number type (at least in an extensible manner), is through mapping
   mechanisms, instructing parsers what to do with different properties
   based on their name.  However, this greatly limits the value of using
   the Number type outside of its original somewhat constrained,
   JavaScript context.  The ES6 JSON object does not support mappings to
   JSON Number either.

   Due to the above, numbers that do not have a natural place in the
   current JSON ecosystem MUST be wrapped using the JSON String type.
   This is close to a de-facto standard for open systems.  This is also
   applicable for other data types that do not have direct support in
   JSON, like "DateTime" objects.  Also see Appendix E.

   Aided by a system using the JSON String type; be it programmatic like

     var obj = JSON.parse('{"giantNumber": "1.4e+9999"}');
     var biggie = new BigNumber(obj.giantNumber);

   or declarative schemes like OpenAPI [OPENAPI], JCS imposes no limits
   on applications, including when using ES6.

Appendix E.  String Subtype Handling

   Due to the limited set of data types featured in JSON, the JSON
   String type is commonly used for holding subtypes.  This appendix
   shows that this can lead to interoperability problems depending on
   JSON parsing method, which MUST be dealt with by JCS compliant
   applications targeting a wider audience.

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   Assume you want to parse the following JSON string holding two
   subtypes and a JSON number:

     const jstring =
         '{"time": "2019-01-28T07:45:10Z", "big": "055", "val": 3.5}';

   This can accomplished by the following ES6 statement:

     var object = JSON.parse(jstring);

   After parsing the actual data can be extracted which for subtypes
   also involve a conversion step using the parsed string argument as
   input:

     ... = new Date(object.time); // Date object
     ... = BigInt(object.big);    // Big integer
     ... = object.val;            // JSON/JS number

   Canonicalization of "object" using the sample code in Appendix A
   would return the following string:

     {"big":"055","time":"2019-01-28T07:45:10Z",val:3.5}

   Although this is (with respect to JCS) technically correct, there is
   another way parsing JSON data which also can be used with ES6 as
   shown below:

     // Currently required to make BigInt JSON serializable
     BigInt.prototype.toJSON = function() {
         return this.toString();
     };

     // JSON parsing using a "stream" based method
     var object = JSON.parse(jstring,
         (k,v) => k == 'time' ? new Date(v) : k == 'big' ? BigInt(v) : v
     );

   If you now apply the canonicalizer in Appendix A to "object", the
   following string would be generated:

     {"big":"55","time":"2019-01-28T07:45:10.000Z","val":3.5}

   In this case the string arguments for "big" and "time" have changed
   with respect to the original, presumable making an application
   depending on JCS fail.

   The reason for the deviation is that in stream and schema based JSON
   parsers, the original "string" argument is typically replaced on-the-

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   fly by the native subtype which when serialized, may exhibit a
   different and platform dependent pattern.

   The above may at first look like an insurmountable obstacle.
   However, there are two fairly straightforward ways making subtype
   serialization independent of parsing scheme elaborated on in the
   following subsections.

E.1.  Immutable String Method

   One method for coping with stream and schema based parsers is
   treating subtypes as "pure" strings with respect to JSON.  To
   accomplish this, subtype conversions are performed outside of the
   core parsing process.  In modern programming platforms like Go, Java
   and C# this can be achieved with moderate efforts by combining
   annotations, getters and setters.  Below is an example in C#/Json.NET
   showing a part of a class that is serializable as a JSON Object:

     // The immutable string solution uses a local
     // string variable for JSON serialization while
     // exposing another type to the application
     [JsonProperty("amount")]
     private string _amount;

     [JsonIgnore]
     public decimal Amount {
         get { return decimal.Parse(_amount); }
         set { _amount = value.ToString(); }
     }

   In an application "Amount" can be accessed as any other property
   while it is actually represented by a quoted string in JSON contexts.

   Note: the example above also addresses the constraints on numeric
   data implied by I-JSON (the C# "decimal" data type has quite
   different characteristics compared to IEEE-754 double precision).

   Note: the intial example in this appendix showing parsing using ES6,
   faithfully implements the immutable string method.

E.2.  Data Normalization Method

   Another method for handling stream and schema based parsing is to
   normalize subtype data.  This requires that the following measures
   are adhered to:

   o  The community or standard utilizing a specific JSON schema defines
      a strict normalized form for each of the used subtypes.

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   o  Compatible serializers are created for each subtype.

   By adding a dedicated serializer for the "Date" subtype, the sample
   JSON schema becomes compatible with JCS:

     Date.prototype.toJSON = function() {
         let date = this.toISOString();
         // In this particular case we selected a UTC notation
         // yyyy-mm-ddThh:mm:ssZ
         return date.substring(0, date.indexOf('.')) + 'Z';
     };

   The canonical string will after this upgrade read as:

     {"big":"55","time":"2019-01-28T07:45:10Z","val":3.5}

   The observant reader will note that "big" still is in error but that
   is to be expected since the "055" argument in the input data clearly
   is not a normalized form for a big integer.  That is, the originator
   of the JSON data did not follow the "contract".

   A positive side effect of this arrangement is that it enforces strict
   definitions of subtypes which improves interoperability in general as
   well.

   Defining specific subtypes and their normalized form is out of scope
   for this specification.

   Unlike the immutable string method, the data normalization method
   accomplishes "true" canonicalization which may be usable by a wider
   range of applications than "Hashable" JSON.

E.3.  Subtypes in Arrays

   Since the JSON Array construct permits mixing arbitrary JSON
   elements, custom parsing and serialization code MUST be used to
   support one (or both) of the methods described in the previous
   subsections.

Appendix F.  Implementation Guidelines

   The optimal solution is integrating support for JCS directly in JSON
   serializers (parsers need no changes).  That is, canonicalization
   would just be an additional "mode" for a JSON serializer.  However,
   this is currently not the case.  Fortunately JCS support can be
   performed through externally supplied canonicalizer software,
   enabling signature creation schemes like the following:

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   1.  Create the data to be signed.

   2.  Serialize the data using existing JSON tools.

   3.  Let the external canonicalizer process the serialized data and
       return canonicalized result data.

   4.  Sign the canonicalized data.

   5.  Add the resulting signature value to the original JSON data
       through a designated signature property.

   6.  Serialize the completed (now signed) JSON object using existing
       JSON tools.

   A compatible signature verification scheme would then be as follows:

   1.  Parse the signed JSON data using existing JSON tools.

   2.  Read and save the signature value from the designated signature
       property.

   3.  Remove the signature property from the parsed JSON object.

   4.  Serialize the remaining JSON data using existing JSON tools.

   5.  Let the external canonicalizer process the serialized data and
       return canonicalized result data.

   6.  Verify that the canonicalized data matches the saved signature
       value using the algorithm and key used for creating the
       signature.

   A canonicalizer like above is effectively only a "filter",
   potentially usable with a multitude of quite different cryptographic
   schemes.

   Using a JSON serializer with integrated JCS support, the
   serialization performed before the canonicalization step could be
   eliminated for both processes.

Appendix G.  Open Source Implementations

   The following Open Source implementations have been verified to be
   compatible with JCS:

   o  JavaScript: https://www.npmjs.com/package/canonicalize [2]

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   o  Java: https://github.com/erdtman/java-json-canonicalization [3]

   o  Go: https://github.com/cyberphone/json-
      canonicalization/tree/master/go [4]

   o  .NET/C#: https://github.com/cyberphone/json-
      canonicalization/tree/master/dotnet [5]

   o  Python: https://github.com/cyberphone/json-
      canonicalization/tree/master/python3 [6]

Appendix H.  Other JSON Canonicalization Efforts

   There are (and have been) other efforts creating "Canonical JSON".
   Below is a list of URLs to some of them:

   o  https://tools.ietf.org/html/draft-staykov-hu-json-canonical-
      form-00 [7]

   o  https://gibson042.github.io/canonicaljson-spec/ [8]

   o  http://wiki.laptop.org/go/Canonical_JSON [9]

Appendix I.  Development Portal

   The JCS specification is currently developed at:
   https://github.com/cyberphone/ietf-json-canon [10].

   The most recent "editors' copy" can be found at:
   https://cyberphone.github.io/ietf-json-canon [11].

   JCS source code and test data is available at:
   https://github.com/cyberphone/json-canonicalization [12]

Authors' Addresses

   Anders Rundgren
   Independent
   Montpellier
   France

   Email: anders.rundgren.net@gmail.com
   URI:   https://www.linkedin.com/in/andersrundgren/

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   Bret Jordan
   Symantec Corporation
   350 Ellis Street
   Mountain View  CA 94043
   USA

   Email: bret_jordan@symantec.com

   Samuel Erdtman
   Spotify AB
   Birger Jarlsgatan 61, 4tr
   Stockholm  113 56
   Sweden

   Email: erdtman@spotify.com

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