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A python library for serialising and deserialising SISL (Simple Information Serialization Language)

Project description


A Python library for serialising and deserialising SISL (Simple Information Serialization Language). SISL is a simple structured text format designed for use in the NCSC Safely Importing Data Pattern. This library provides the ability to serialise and deserialise SISL as well as perform semantic verification of the SISL.

Hardware enforced syntatic verification may be carried out by the OakdoorTM family of data diodes.

Also provides the functionality to wrap and unwrap files with an XOR scrambling technique used on the OakdoorTM data diodes which is designed to render files inert if they fail the syntatic verification allowing the file to be safely transported or stored for later unwrapping and inspection.


Encoding basic Python object to SISL:

>>> import pysisl
>>> pysisl.dumps({"hello": "world"}) 
'{hello: !str "world"}'
>>> pysisl.dumps({"name": "helpful_name", "flag": False, "count": 3}) 
'{name: !str "helpful_name", flag: !bool "false", count: !int "3"}'

Decoding SISL to Python:

>>> import pysisl
>>> pysisl.loads('{name: !str "helpful_name", flag: !bool "false", count: !int "3"}') 
{'name': 'helpful_name', 'flag': False, 'count': 3}

Basic Usage


Serialise a basic Python object into a SISL formatted str.

pysisl.loads(sisl, schema=None)  

Deserialise SISL str to a basic Python object. Optionally, verify the SISL schema using a json schema.


Applies an XOR data scrambling technique to wrap and render data inert, equivalent to the OakdoorTM data diode hardware. The data must be bytes() or bytearray(). The XOR key is internally generated and prepended as part of a header.


Unwraps data scrambled with the above XOR data scrambling technique. The data must be bytes() or bytearray().

See the conversion table on this page for more details.

Splitting large objects into multiple SISL files

pySISL supports a maximum length in bytes for SISL files. If the input Python object exceeds this max length it is split into multiple SISL files. A Python list is returned where each item is a SISL string.

Split an object into SISL with max bytes as 20

>>> import pysisl
>>> pysisl.dumps({"abc": 2, "def": 3}, max_length=20)
['{abc: !int "2"}', '{def: !int "3"}']

Joining multiple SISL files to form a single Python object

If a SISL file has been split in the way described above, pySISL supports joining the split files into a single Python object. When a list of SISL strings is passed to pySISL.loads(), this joining is done by default. A single Python dictionary is returned. Joining is done by merging nesting structures of arbitrary depth, while maintaining order.

>>> import pysisl
>>> pysisl.loads(['{abc: !list {_0: !str "I", _1: !list {_0: !str "am"}}}', 
                  '{abc: !list {_1: !list {_1: !str "a"}, _2: !str "list"}}'])

{"abc": ['I', ['am', 'a'], 'list']}

>>> pysisl.loads(['{abc: !list {_0: !str "I", _1: !list {_0: !str "am"}}}',
                  '{abc: !list {_2: !list {_0: !str "a"}, _3: !str "list"}}'])

{"abc": ['I', ['am'], ['a'], 'list']}

Semantic Verification with a Schema

The jsonschema library is used to optionally verify the parsed SISL data structure. See JSON Schema for details on the json schema syntax. For example

Successful Parsing

>>> import pysisl
>>> my_schema = {
        "properties": {
            "name": {
                "type": "string"
            "flag": {
                "type": "boolean" 
            "count": {
                "type": "number"
>>> decode_example = '{name: !str "helpful_name", flag: !bool "false", count: !int "3"}'
>>> pysisl.loads(decode_example, my_schema)
{'name': 'helpful_name', 'flag': False, 'count': 3}

Schema Verification Fails

>>> import pysisl
>>> my_schema = {
        "properties": {
            "name": {
                "type": "string"
            "flag": {
                "type": "boolean" 
            "count": {
                "type": "string"
>>> decode_example = '{name: !str "helpful_name", flag: !bool "false", count: !int "3"}'
>>> pysisl.loads(decode_example, my_schema)
Traceback (most recent call last):
    File "/home/vagrant/pysisl/pysisl/", line 31, in _verify_schema_if_required
        json_validator(flattened_sisl, schema=schema, format_checker=FormatChecker())
    File "/home/vagrant/pysisl/venv/lib64/python3.6/site-packages/jsonschema/", line 934, in validate
raise error
        jsonschema.exceptions.ValidationError: 3 is not of type 'string'

Failed validating 'type' in schema['properties']['count']:
        {'type': 'string'}

Conversion table

Python SISL
dict obj
list list
str str
int int
float float
bool bool
None null


The NCSC Safely Importing Data Pattern, an architecture pattern describes a safe mechanism for handling structured data from an external untrusted source. We use a Transform - Verify approach taking our source data, transforming to an intermediate format, inspecting the intermediate format and then transforming back to the original format. SISL was designed to be a simple and easily inspectable intermediate format for just such an approach.

OakdoorTM products enable one- or two-way data transfers between segregated networks, letting organisations safely run services, such as file transfer, protocol exchanges, secure internet browsing and systems management. This is done using a combination of hardware enforced verification and software.

pySISL can form part of the transformation engine sub-system that enables cross-network communication that is compatible with the NCSC Safely importing data pattern. The pySISL encoder can be used to convert complex Python dictionaries into valid SISL that is compatible with the diodes and the decoder will convert the SISL back into the same dictionaries without loss of data.


MIT licence

SISL Specification

For reference, this is ABNF for SISL.

sislfile        = grouping *255wsp
grouping        = "{" ( (*255wsp collection *255wsp ) / *255wsp ) "}"
collection      = element *("," *255wsp element)
element         = name ":" 1*255wsp "!" type 1*255wsp value 
name            = ( "_" / ALPHA ) *( "_" / "-" / "." / ALPHA / DIGIT )
type            = ( "_" / ALPHA ) *254( "_" / "-" / "." / ALPHA / DIGIT )
value           = ( DQUOTE *( printable / escape) DQUOTE ) / grouping
escape          = "\" ( lcr / lct / lcn / DQUOTE / "\" / (lcx 2HEXDIG) / (lcu 4HEXDIG) / (ucu 8HEXDIG) )
wsp             = SP / HTAB / CR / LF
printable       = %x20-21 / %x23-5B / %x5D-7E             ; Printable chars apart from '"' or '\'

lcr             = %x72                                    ; lower case r
lct             = %x74                                    ; lower case t
lcn             = %x6E                                    ; lower case n
lcx             = %x78                                    ; lower case x
lcu             = %x75                                    ; lower case u
ucu             = %x55                                    ; upper case u

; Core rules
ALPHA           = %x41-5A / %x61-7A                       ; A-Z / a-z
DIGIT           = %x30-39                                 ; 0-9
DQUOTE          = %x22                                    ; " (double-quote)
SP              = %x20                                    ; space
HTAB            = %x09                                    ; horizontal tab
CR              = %x0D                                    ; carriage return
LF              = %x0A                                    ; line feed

Getting Help

If you need help using the pySISL module, please contact OakdoorTM at


Type Python SISL
Dictionary {"field_one": {"key_one": "teststring"}} '{"field_one": !obj {"key_one": !str "teststring"}}'
List {"field_one": [1, 2, 3]} '{"field_one": !list {_0: !int "1", _1: !int "2", _2: !int "3"}}'
Anonymous list [1, 2, 3] '{"_": !_list {_0: !int "1", _1: !int "2", _2: !int "3"}}'
String {"field_one": "teststring"} '{"field_one": !str "teststring"}'
Anonymous string "teststring" '{"_": !_str "teststring"}'
Int {"field_one": 1} '{"field_one": !int "1"}'
Anonymous int 1 '{"_": !_int "1"}'
Float {"field_one": 5.3} '{"field_one": !float "5.3"}'
Anonymous float 5.3 '{"_": !_float "5.3"}'
Bool {"field_one": True} '{"field_one": !bool "true"}'
Anonymous bool True '{"_": !_bool "true"}'
None {"field_one": None} '{"field_one": !null ""}'
Anonymous none None '{"_": !_null ""}'

Contributing to pySISL

All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome. If you notice a bug or would like to make an update to pySISL, please contact

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