Tagging in PyASN1

1.2 Tagging in PyASN1

In order to continue with the Constructed ASN.1 types, we will first have to introduce the concept of tagging (and its pyasn1 implementation), as some of the Constructed types rely upon the tagging feature.

When a value is coming into an ASN.1-based system (received from a network or read from some storage), the receiving entity has to determine the type of the value to interpret and verify it accordingly.

Historically, the first data serialization protocol introduced in ASN.1 was BER (Basic Encoding Rules). According to BER, any serialized value is packed into a triplet of (Type, Length, Value) where Type is a code that identifies the value (which is called tag in ASN.1), length is the number of bytes occupied by the value in its serialized form and value is ASN.1 value in a form suitable for serial transmission or storage.

For that reason almost every ASN.1 type has a tag (which is actually a BER type) associated with it by default.

An ASN.1 tag could be viewed as a tuple of three numbers: (Class, Format, Number). While Number identifies a tag, Class component is used to create scopes for Numbers. Four scopes are currently defined: UNIVERSAL, context-specific, APPLICATION and PRIVATE. The Format component is actually a one-bit flag - zero for tags associated with scalar types, and one for constructed types (will be discussed later on).

MyIntegerType ::= [12] INTEGER
MyOctetString ::= [APPLICATION 0] OCTET STRING

In pyasn1, tags are implemented as immutable, tuple-like objects:

>>> from pyasn1.type import tag
>>> myTag = tag.Tag(tag.tagClassContext, tag.tagFormatSimple, 10)
>>> myTag
Tag(tagClass=128, tagFormat=0, tagId=10)
>>> tuple(myTag)
(128, 0, 10)
>>> myTag[2]
10
>>> myTag == tag.Tag(tag.tagClassApplication, tag.tagFormatSimple, 10)
False
>>>

Default tag, associated with any ASN.1 type, could be extended or replaced to make new type distinguishable from its ancestor. The standard provides two modes of tag mangling - IMPLICIT and EXPLICIT.

EXPLICIT mode works by appending new tag to the existing ones thus creating an ordered set of tags. This set will be considered as a whole for type identification and encoding purposes. Important property of EXPLICIT tagging mode is that it preserves base type information in encoding what makes it possible to completely recover type information from encoding.

When tagging in IMPLICIT mode, the outermost existing tag is dropped and replaced with a new one.

MyIntegerType ::= [12] IMPLICIT INTEGER
MyOctetString ::= [APPLICATION 0] EXPLICIT OCTET STRING

To model both modes of tagging, a specialized container TagSet object (holding zero, one or more Tag objects) is used in pyasn1.

>>> from pyasn1.type import tag
>>> tagSet = tag.TagSet(
...   # base tag
...   tag.Tag(tag.tagClassContext, tag.tagFormatSimple, 10),
...   # effective tag
...   tag.Tag(tag.tagClassContext, tag.tagFormatSimple, 10)
... )
>>> tagSet
TagSet(Tag(tagClass=128, tagFormat=0, tagId=10))
>>> tagSet.getBaseTag()
Tag(tagClass=128, tagFormat=0, tagId=10)
>>> tagSet = tagSet.tagExplicitly(
...    tag.Tag(tag.tagClassContext, tag.tagFormatSimple, 20)
... )
>>> tagSet
TagSet(Tag(tagClass=128, tagFormat=0, tagId=10), 
       Tag(tagClass=128, tagFormat=32, tagId=20))
>>> tagSet = tagSet.tagExplicitly(
...    tag.Tag(tag.tagClassContext, tag.tagFormatSimple, 30)
... )
>>> tagSet
TagSet(Tag(tagClass=128, tagFormat=0, tagId=10), 
       Tag(tagClass=128, tagFormat=32, tagId=20), 
       Tag(tagClass=128, tagFormat=32, tagId=30))
>>> tagSet = tagSet.tagImplicitly(
...    tag.Tag(tag.tagClassContext, tag.tagFormatSimple, 40)
... )
>>> tagSet
TagSet(Tag(tagClass=128, tagFormat=0, tagId=10),
       Tag(tagClass=128, tagFormat=32, tagId=20),
       Tag(tagClass=128, tagFormat=32, tagId=40))
>>>

As a side note: the "base tag" concept (accessible through the getBaseTag() method) is specific to pyasn1 -- the base tag is used to identify the original ASN.1 type of an object in question. Base tag is never occurs in encoding and is mostly used internally by pyasn1 for choosing type-specific data processing algorithms. The "effective tag" is the one that always appears in encoding and is used on tagSets comparation.

Any two TagSet objects could be compared to see if one is a derivative of the other. Figuring this out is also useful in cases when a type-specific data processing algorithms are to be chosen.

>>> from pyasn1.type import tag
>>> tagSet1 = tag.TagSet(
...   # base tag
...   tag.Tag(tag.tagClassContext, tag.tagFormatSimple, 10)
...   # effective tag
...   tag.Tag(tag.tagClassContext, tag.tagFormatSimple, 10)
... )
>>> tagSet2 = tagSet1.tagExplicitly(
...    tag.Tag(tag.tagClassContext, tag.tagFormatSimple, 20)
... )
>>> tagSet1.isSuperTagSetOf(tagSet2)
True
>>> tagSet2.isSuperTagSetOf(tagSet1)
False
>>>

We will complete this discussion on tagging with a real-world example. The following ASN.1 tagged type:

MyIntegerType ::= [12] EXPLICIT INTEGER

could be expressed in pyasn1 like this:

>>> from pyasn1.type import univ, tag
>>> class MyIntegerType(univ.Integer):
...   tagSet = univ.Integer.tagSet.tagExplicitly(
...        tag.Tag(tag.tagClassContext, tag.tagFormatSimple, 12)
...        )
>>> myInteger = MyIntegerType(12345)
>>> myInteger.getTagSet()
TagSet(Tag(tagClass=0, tagFormat=0, tagId=2), 
       Tag(tagClass=128, tagFormat=32, tagId=12))
>>>

Referring to the above code, the tagSet class attribute is a property of any pyasn1 type object that assigns default tagSet to a pyasn1 value object. This default tagSet specification can be ignored and effectively replaced by some other tagSet value passed on object instantiation.

It's important to understand that the tag set property of pyasn1 type/value object can never be modifed in place. In other words, a pyasn1 type/value object can never change its tags. The only way is to create a new pyasn1 type/value object and associate different tag set with it.