Internet-Draft draft-rundgren-json-canonicalization-scheme September 2019
Rundgren, et al. Expires 30 March 2020 [Page]
Network Working Group
Intended Status:
A. Rundgren
B. Jordan
Symantec Corporation
S. Erdtman
Spotify AB

JSON Canonicalization Scheme (JCS)


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 address this is to create a canonical representation of the data. Canonicalization also permits data to be exchanged in its original form on the "wire" while cryptographic operations performed on the canonicalized counterpart of the data in the producer and consumer end points, generate consistent results. This document describes the JSON Canonicalization Scheme (JCS). The JCS specification defines how to create a canonical representation of JSON data by building on the strict serialization methods for JSON primitives defined by ECMAScript, constraining JSON data to the I-JSON subset, and by using deterministic property sorting.

Status of This Memo

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This Internet-Draft will expire on 30 March 2020.

1. Introduction

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 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:

The absence of a namespace concept and default values.
Constraining data to the I‑JSON [RFC7493] subset. This eliminates the need for specific parsers for dealing with canonicalization.
JCS compatible serialization of JSON primitives is currently supported by most Web browsers and as well as by Node.js [NODEJS],
The full JCS specification is currently supported by multiple Open Source implementations (see Appendix G). See also Appendix F.

In summary the JCS specification defines how to create a canonical representation of JSON 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.

JCS is compatible with some existing systems relying on JSON canonicalization such as 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 have a basic knowledge of ECMAScript including the "JSON" object.

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

3.1. Creation of Input Data

Data to be serialized is usually achieved by:

Parsing previously generated JSON data.
Programmatically creating data.

Irrespective of the method used, the data to be serialized MUST be adapted for I‑JSON [RFC7493] formatting, which implies the following:

JSON Objects MUST NOT exhibit duplicate property names.
JSON String data MUST be expressible as Unicode [UNICODE].
JSON Number 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.

An additional constraint is that parsed JSON String data MUST NOT be altered during subsequent serializations. For more information see Appendix E.

Note: although the Unicode standard offers the possibility of combining certain characters into one, referred to as "Unicode Normalization" (, JCS' string processing does not take this in consideration. That is, all components involved in a scheme depending on JCS, MUST preserve Unicode string data "as is".

Note: how structured objects like sets are represented in JSON is out of scope for JCS. See also Appendix F.

3.2. Generation of Canonical JSON Data

The following subsections describe the steps required to create 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 tokens MUST NOT be emitted.

3.2.2. Serialization of Primitive Data Types

Assume a JSON object as follows is parsed:

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

If the parsed data is subsequently serialized 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 the original data:


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 in the example, numbers are subject to rounding as well.

The following subsections describe the serialization of primitive JSON data types according to JCS. This part is identical to that of ES6. In the (unlikely) event that a future version of ECMAScript would invalidate any of the following serialization methods, it will be up to the developer community to either stick to this specification or create a new specification. Serialization of Literals

In accordance with JSON [RFC8259], the literals "null", "true", and "false" MUST be serialized as null, true, and false respectively. Serialization of Strings

For JSON String data (which includes JSON Object property names as well), each Unicode code point MUST be serialized as described below (see section of [ES6]):

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.
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 resulting sequence of Unicode code points MUST be enclosed in double quotes (").

Note: some JSON systems permit the use of invalid Unicode data like "lone surrogates" (e.g. U+DEAD). Since this may lead to interoperability issues including broken signatures, occurrences of such data MUST cause a compliant JCS implementation to terminate with an appropriate error. Serialization of Numbers

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

Due to the relative complexity of this part, the algorithm itself is not included in this document. For implementers of JCS compliant number serialization, Google's V8 [V8] may serve as a reference. Another compatible number serialization reference implementation is Ryu [RYU], that is used by the JCS open source Java implementation mentioned in Appendix G.

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.

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

3.2.3. Sorting of Object Properties

Although the previous step normalized the representation of primitive JSON data types, the result would not yet 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:


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

JSON Object properties MUST be sorted recursively, which means that JSON child Objects MUST have their properties sorted as well.
JSON Array data MUST also be scanned for the presence of JSON Objects (if an object is found then its properties MUST be sorted), 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:

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

Property name 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.

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


The rationale for basing the sorting algorithm on UTF-16 code units is that it maps directly to the string type in ECMAScript (featured in Web browsers and Node.js), Java and .NET. In addition, JSON only supports escape sequences expressed as UTF-16 code units making knowledge and handling of such data a necessity anyway. Systems using another internal representation of string data will need to convert JSON property name 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.

The following test data can be used for verifying the correctness of the sorting scheme in a JCS implementation. JSON test data:

    "\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"

Expected argument order after sorting property strings:

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

Note: for the purpose of obtaining a deterministic property order, sorting on UTF-8 or UTF-32 encoded data would also work, but the outcome for JSON data like above would differ and thus be incompatible with this specification. However, in practice, property names are rarely defined outside of 7-bit ASCII making it possible to sort on string data in UTF-8 or UTF-32 format without conversions to UTF-16 and still be compatible with JCS. If this is a viable option or not depends on the environment JCS is used in.

3.2.4. UTF-8 Generation

Finally, in order to create a platform independent representation, the result of the preceding step 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.

4. IANA Considerations

This document has no IANA actions.

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.

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.

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 Scott Ananian, Tim Bray, Ben Campbell, Adrian Farell, Richard Gibson, Bron Gondwana, John-Mark Gurney, John Levine, Mark Miller, Matt 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.

7. References

7.1. Normative References

Ecma International, "ECMAScript 2015 Language Specification", , <>.
IEEE, "IEEE Standard for Floating-Point Arithmetic", , <>.
Bradner, S., "Key words for use in RFCs to Indicate Requirement Levels", BCP 14, RFC 2119, DOI 10.17487/RFC2119, , <>.
Bray, T., Ed., "The I-JSON Message Format", RFC 7493, DOI 10.17487/RFC7493, , <>.
Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC 2119 Key Words", BCP 14, RFC 8174, DOI 10.17487/RFC8174, , <>.
Bray, T., Ed., "The JavaScript Object Notation (JSON) Data Interchange Format", STD 90, RFC 8259, DOI 10.17487/RFC8259, , <>.
The Unicode Consortium, "The Unicode Standard, Version 12.1.0", , <>.

7.2. Informative References

A. Rundgren, ""Comparable" JSON - Work in progress", <>.
"Keybase", <>.
"Node.js", <>.
"The OpenAPI Initiative", <>.
Josefsson, S., "The Base16, Base32, and Base64 Data Encodings", RFC 4648, DOI 10.17487/RFC4648, , <>.
Jones, M., Bradley, J., and N. Sakimura, "JSON Web Signature (JWS)", RFC 7515, DOI 10.17487/RFC7515, , <>.
Jones, M. and N. Sakimura, "JSON Web Key (JWK) Thumbprint", RFC 7638, DOI 10.17487/RFC7638, , <>.
Ulf Adams, "Ryu floating point number serializing algorithm", <>.
Google LLC, "Chrome V8 Open Source JavaScript Engine", <>.
W3C, "XML Signature Syntax and Processing Version 1.1", <>.

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 = '';
      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 //
              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 //
              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                │
│ 8000000000000000 │ 0                         │ Minus zero          │
│ 0000000000000001 │ 5e-324                    │ Min pos number      │
│ 8000000000000001 │ -5e-324                   │ Min neg number      │
│ 7fefffffffffffff │ 1.7976931348623157e+308   │ Max pos number      │
│ ffefffffffffffff │ -1.7976931348623157e+308  │ Max neg number      │
│ 4340000000000000 │ 9007199254740992          │ Max pos integer (1) │
│ c340000000000000 │ -9007199254740992         │ Max neg integer (1) │
│ 4430000000000000 │ 295147905179352830000     │ ~2**68          (2) │
│ 7fffffffffffffff │                           │ NaN             (3) │
│ 7ff0000000000000 │                           │ Infinity        (3) │
│ 44b52d02c7e14af5 │ 9.999999999999997e+22     │                     │
│ 44b52d02c7e14af6 │ 1e+23                     │                     │
│ 44b52d02c7e14af7 │ 1.0000000000000001e+23    │                     │
│ 444b1ae4d6e2ef4e │ 999999999999999700000     │                     │
│ 444b1ae4d6e2ef4f │ 999999999999999900000     │                     │
│ 444b1ae4d6e2ef50 │ 1e+21                     │                     │
│ 3eb0c6f7a0b5ed8c │ 9.999999999999997e-7      │                     │
│ 3eb0c6f7a0b5ed8d │ 0.000001                  │                     │
│ 41b3de4355555553 │ 333333333.3333332         │                     │
│ 41b3de4355555554 │ 333333333.33333325        │                     │
│ 41b3de4355555555 │ 333333333.3333333         │                     │
│ 41b3de4355555556 │ 333333333.3333334         │                     │
│ 41b3de4355555557 │ 333333333.33333343        │                     │
│ becbf647612f3696 │ -0.0000033333333333333333 │                     │
│ 43143ff3c1cb0959 │ 1424953923781206.2        │ Round to even   (4) │


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

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. 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 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 "BigInteger" 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 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 involve 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

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


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

  // Note: "BigInt" is implemented by Google's V8 ECMAScript engine.
  // It requires the following code to become JSON serializable.
  BigInt.prototype.toJSON = function() {
      return this.toString();

  // JSON parsing using a "stream" based method
  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:


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-fly by the native subtype which 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
  private string _amount;

  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).

E.1. Subtypes in Arrays

Since the JSON Array construct permits mixing arbitrary JSON data types, custom parsing and serialization code may be required to cope with subtypes anyway.

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:

  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 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:

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:

The most recent "editors' copy" can be found at:

JCS source code and extensive test data is available at:

Appendix J. Document History

[[ to be removed by the RFC Editor before publication as an RFC ]]

Version 00-06:

  • See IETF diff listings.

Version 07:

  • Initial converson to XML RFC version 3.
  • Changed intended status to "Informational".
  • Added UTF-16 test data and explanations.

Version 08:

  • Updated Abstract.
  • Added a "Note 2" number serialization sample.
  • Updated Security Considerations.
  • Tried to clear up the JSON input data section.
  • Added a line about Unicode normalization.
  • Added a line about serialiation of structured data.
  • Added a missing fact about "BigInt" (V8 not ES6).

Version 09:

  • Updated initial line of Abstract and Introduction.
  • Added note about breaking ECMAScript changes.
  • Minor language nit fixes.

Version 10-12:

  • Language tweaks.

Authors' Addresses

Anders Rundgren
Bret Jordan
Symantec Corporation
350 Ellis Street
Mountain View, CA 94043
United States of America
Samuel Erdtman
Spotify AB
Birger Jarlsgatan 61, 4tr
SE-113 56 Stockholm