Status of This Memo

This document is not an Internet Standards Track specification; it is published for informational purposes.¶

This is a contribution to the RFC Series, independently of any other RFC stream. The RFC Editor has chosen to publish this document at its discretion and makes no statement about its value for implementation or deployment. Documents approved for publication by the RFC Editor are not candidates for any level of Internet Standard; see Section 2 of RFC 7841.¶

Information about the current status of this document, any errata, and how to provide feedback on it may be obtained at https://www.rfc-editor.org/info/rfc0000.¶

Copyright Notice

Copyright (c) 2020 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.¶

Table of Contents

1. Introduction

This document describes the JSON Canonicalization Scheme (JCS). The JCS specification defines how to create a canonical representation of JSON [RFC8259] data by building on the strict serialization methods for JSON primitives defined by ECMAScript [ES6], constraining JSON data to the I-JSON [RFC7493] subset, and by using deterministic property sorting. The output from JCS is a "hashable" representation of JSON data that can be used by cryptographic methods. The subsequent paragraphs outline the primary design considerations.¶

Cryptographic operations like hashing and signing need the data to be expressed in an invariant format so that the operations are reliably repeatable. One way to accomplish this is to convert the data into a format that has a simple and fixed representation, like base64url [RFC4648]. This is how JSON Web Signature (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, using canonicalization enables a JSON Object to remain a JSON Object even after being signed. This can simplify system design, documentation, and logging.¶

To avoid "reinventing the wheel", JCS relies on the serialization of JSON primitives (strings, numbers, and literals), as defined by ECMAScript (aka JavaScript) beginning with version 6 [ES6], hereafter referred to as "ES6".¶

Seasoned XML developers may recall difficulties getting XML signatures to validate. This was usually due to different interpretations of the quite intricate XML canonicalization rules as well as of the equally complex Web Services security standards. The reasons why JCS should not suffer from similar issues are:¶

o

The absence of a namespace concept and default values.¶

o

Constraining data to the I‑JSON [RFC7493] subset. This eliminates the need for specific parsers for dealing with canonicalization.¶

o

JCS-compatible serialization of JSON primitives is currently supported by most Web browsers as well as by Node.js [NODEJS].¶

o

The full JCS specification is currently supported by multiple open-source implementations (see Appendix G). See also Appendix F for implementation guidelines.¶

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

For potential uses outside of cryptography, see [JSONCOMP].¶

The intended audiences of this document are JSON tool vendors as well as designers of JSON-based cryptographic solutions. The reader is assumed to be knowledgeable in ECMAScript, including the JSON object.¶

2. Terminology

Note that this document is not on the IETF standards track. However, a conformant implementation is supposed to adhere to the specified behavior for security and interoperability reasons. This text uses BCP 14 to describe that necessary behavior.¶

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 details related to creating a canonical JSON representation and how they are addressed by JCS.¶

Appendix F describes the RECOMMENDED way of adding JCS support to existing JSON tools.¶

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

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

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

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

        ""
        "a"
        "aa"
        "ab"

  {
    "\u20ac": "Euro Sign",
    "\r": "Carriage Return",
    "\ufb33": "Hebrew Letter Dalet With Dagesh",
    "1": "One",
    "\ud83d\ude00": "Emoji: Grinning Face",
    "\u0080": "Control",
    "\u00f6": "Latin Small Letter O With Diaeresis"
  }

  "Carriage Return"
  "One"
  "Control"
  "Latin Small Letter O With Diaeresis"
  "Euro Sign"
  "Emoji: Grinning Face"
  "Hebrew Letter Dalet With Dagesh"

  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

4. IANA Considerations

This document has no IANA actions.¶

5. Security Considerations

It is crucial to perform sanity checks on input data to avoid overflowing buffers and similar things that could affect the integrity of the system.¶

When JCS is applied to signature schemes like the one described in Appendix F, applications MUST perform the following operations before acting upon received data:¶

1. Parse the JSON data and verify that it adheres to I-JSON.¶
2. Verify the data for correctness according to the conventions defined by the ecosystem where it is to be used. This also includes locating the property holding the signature data.¶
3. Verify the signature.¶

If any of these steps fail, the operation in progress MUST be aborted.¶

Appendix A. ES6 Sample Canonicalizer

Below is an example of a JCS canonicalizer for usage with ES6-based systems:¶

  ////////////////////////////////////////////////////////////
  // Since the primary purpose of this code is highlighting //
  // the core of the JCS algorithm, error handling and      //
  // UTF-8 generation were not implemented.                 //
  ////////////////////////////////////////////////////////////
  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) {
                      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.¶

Notes:¶

(1)

For maximum compliance with the ES6 JSON object, values that are to be interpreted as true integers SHOULD be in the range -9007199254740991 to 9007199254740991. However, how numbers are used in applications do not affect the JCS algorithm.¶

(2)

Although a set of specific integers like 2**68 could be regarded as having extended precision, the JCS/ES6 number serialization algorithm does not take this into consideration.¶

(3)

Value out range, not permitted in JSON. See Section 3.2.2.3.¶

(4)

This number is exactly 1424953923781206.25 but will, after the "Note 2" rule mentioned in Section 3.2.2.3, be truncated and rounded to the closest even value.¶

For a more exhaustive validation of a JCS number serializer, you may test against a file (currently) available in the development portal (see Appendix I) containing a large set of sample values. Another option is running V8 [V8] as a live reference together with a program generating a substantial amount of random IEEE-754 values.¶

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 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 that 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. Canonicalization also converts JSON data into a single line of text, which may be less than ideal for debugging and logging.¶

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 [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 of 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 JSON 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 as described in 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 can, depending on JSON parsing method, lead to interoperability problems, which MUST be dealt with by JCS-compliant applications targeting a wider audience.¶

Assume you want to parse a JSON object where the schema designer assigned the property "big" for holding a BigInt subtype and "time" for holding a DateTime subtype, while "val" is supposed to be a JSON Number compliant with JCS. The following example shows such an object:¶

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

Parsing of this object can be accomplished by the following ES6 statement:¶

  var object = JSON.parse(JSON_object_featured_as_a_string);

After parsing, the actual data can be extracted, which for subtypes, also involves a conversion step using the result of the parsing process (an ECMAScript object) as input:¶

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

Note that the BigInt data type is currently only natively supported by V8 [V8].¶

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 of parsing JSON data, which also can be used with ECMAScript as shown below:¶

  // "BigInt" requires the following code to become JSON serializable
  BigInt.prototype.toJSON = function() {
      return this.toString();
  };

  // JSON parsing using a method based on "stream"
  var object = JSON.parse(JSON_object_featured_as_a_string,
      (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, presumably 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 fly by the native subtype that, when serialized, may exhibit a different and platform-dependent pattern.¶

That is, stream- and schema-based parsing MUST treat subtypes as "pure" (immutable) JSON String types and perform the actual conversion to the designated native type in a subsequent step. 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 "pure" 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).¶

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 introduced through externally supplied canonicalizer software acting as a post processor to existing JSON serializers. This arrangement also relieves the JCS implementer from having to deal with how underlying data is to be represented in JSON.¶

The post processor concept enables signature creation schemes like the following:¶

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:¶

• JavaScript: <https://www.npmjs.com/package/canonicalize>¶
• Java: <https://github.com/erdtman/java-json-canonicalization>¶
• Go: <https://github.com/cyberphone/json-canonicalization/tree/master/go>¶
• .NET/C#: <https://github.com/cyberphone/json-canonicalization/tree/master/dotnet>¶
• Python: <https://github.com/cyberphone/json-canonicalization/tree/master/python3>¶

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:¶

• <https://tools.ietf.org/html/draft-staykov-hu-json-canonical-form-00>¶
• <https://gibson042.github.io/canonicaljson-spec/>¶
• <http://wiki.laptop.org/go/Canonical_JSON>¶

The listed efforts all build on text-level JSON to JSON transformations. The primary feature of text-level canonicalization is that it can be made neutral to the flavor of JSON used. However, such schemes also imply major changes to the JSON parsing process, which is a likely hurdle for adoption. Albeit at the expense of certain JSON and application constraints, JCS was designed to be compatible with existing JSON tools.¶

Appendix I. Development Portal

The JCS specification is currently developed at: <https://github.com/cyberphone/ietf-json-canon>.¶

JCS source code and extensive test data is available at: <https://github.com/cyberphone/json-canonicalization>.¶

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 Scott Ananian, Tim Bray, Ben Campbell, Adrian Farell, Richard Gibson, Bron Gondwana, John-Mark Gurney, John Levine, Mark Miller, Matthew Miller, Mike Jones, Mark Nottingham, Mike Samuel, Jim Schaad, Robert Tupelo-Schneck, and Michal Wadas.¶

For carrying out real-world concept verification, the software and support for number serialization provided by Ulf Adams, Tanner Gooding, and Remy Oudompheng was very helpful.¶

Authors' Addresses