Internet-Draft | draft-rundgren-json-canonicalization-scheme | September 2019 |
Rundgren, et al. | Expires 23 March 2020 | [Page] |
Cryptographic operations like hashing and signing requires that the data is expressed in an invariant format. 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 secure cryptographic operations are performed on its canonicalized counterpart in the producer and consumer end points. The JSON Canonicalization Scheme (JCS) 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.¶
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Cryptographic operations like hashing and signing requires that the data is expressed in an invariant format. 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:¶
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.¶
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in BCP 14 [RFC2119] [RFC8174] when, and only when, they appear in all capitals, as shown here.¶
This section describes different issues related to creating a canonical JSON representation, and how they are addressed by JCS.¶
Data to be serialized is usually achieved by:¶
Irrespective of the method used, the data to be serialized MUST be adapted for I‑JSON [RFC7493] formatting, which implies the following:¶
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" (https://www.unicode.org/reports/tr15/), 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.¶
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.¶
Whitespace between JSON tokens MUST NOT be emitted.¶
Assume a JSON object as follows is parsed:¶
{ "numbers": [333333333.33333329, 1E30, 4.50, 2e-3, 0.000000000000000000000000001], "string": "\u20ac$\u000F\u000aA'\u0042\u0022\u005c\\\"\/", "literals": [null, true, false] }¶
If the parsed data is subsequently serialized
using a serializer compliant with ES6's JSON.stringify()
,
the result would (with a line wrap added for display purposes only),
be rather divergent with respect to the original data:¶
{"numbers":[333333333.3333333,1e+30,4.5,0.002,1e-27],"string": "€$\u000f\nA'B\"\\\\\"/","literals":[null,true,false]}¶
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.¶
There is no issue with the JSON literals
null
, true
, and false
since they already have a
fixed definition in JSON [RFC8259].¶
For JSON String data (which includes JSON Object property names as well), each Unicode code point MUST be serialized as described below (see section 24.3.2.2 of [ES6]):¶
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.¶
JSON Number data 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. 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.¶
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:¶
{"literals":[null,true,false],"numbers":[333333333.3333333, 1e+30,4.5,0.002,1e-27],"string":"€$\u000f\nA'B\"\\\\\"/"}¶
The rules for lexicographic sorting of JSON Object properties according to JCS are as follows:¶
When a JSON Object is about to have its properties sorted, the following measures MUST be adhered to:¶
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:¶
"" "a" "aa" "ab"¶
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" "One" "Control" "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.¶
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.¶
This document has no IANA actions.¶
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:¶
If any of these steps fail, the operation in progress MUST be aborted.¶
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.¶
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 += '}'; } } };¶
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) │ └──────────────────┴───────────────────────────┴─────────────────────┘¶
Notes:¶
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.¶
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.¶
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.¶
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:¶
{"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 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:¶
{"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-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 [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).¶
Since the JSON Array construct permits mixing arbitrary JSON data types, custom parsing and serialization code may be required to cope with subtypes anyway.¶
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:¶
A compatible signature verification scheme would then be as follows:¶
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.¶
The following Open Source implementations have been verified to be compatible with JCS:¶
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.¶
The JCS specification is currently developed at: https://github.com/cyberphone/ietf-json-canon.¶
The most recent "editors' copy" can be found at: https://cyberphone.github.io/ietf-json-canon.¶
JCS source code and extensive test data is available at: https://github.com/cyberphone/json-canonicalization¶
[[ to be removed by the RFC Editor before publication as an RFC ]]¶
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