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Entity

In order to provide a convenient API, Sploitkit defines a central class aimed to declare everything that can be tuned and imported to make a new CLI framework. As explained previously, this central class is called Entity. This holds the generic logic, namely for :

  • registering entity classes (see hereafter: Console, Command, ...)
  • handling requirements, dynamically enabling/disabling entities
  • handling metadata (formatting them for display in the CLI)

Requirements and applicability

Requirements can be defined in order to dynamically enable/disable entities. These are managed through the requirements class attribute. Currently, a few requirement types exist :

Key Description
config Dictionary of Config/Option values to be set (see hereafter).
file List of files that must exist in the current workspace.
python List of Python packages required to be installed in the environment.
state State variables to be set in the Global State (see section Console) ; can be defined in three ways :
  1. List of existing keys, e.g. ['VAR1', 'VAR2'].
  2. Dictionary of state variables (exact match), e.g. {'VAR1': {'key1':'myval1', 'key2':'myval2'}}.
  3. Dictionary of state values, regardless of the key, e.g. {'VAR1': {None:'myval1'}}.
system List of system tools and/or packages to be installed ; can be defined in two ways :
  1. [tool], e.g. ifconfig ; if the system command is missing, it will only tell that this tool is not present.
  2. [package]/[tool], e.g. net-tools/ifconfig ; this allows to be more precise regarding what is missing.

In parallel with the requirements, the applicability is checked, that is, if the entity has a reference with a value that exactly matches the expected one.

Example: Setting a command as applicable only for modules named 'do_something'

Let us consider defining a command that only applies to any module whose name is "do_something". Then defining the applies_to attribute like hereafter allows to limit the scope of the command to only modules named so.

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class DoIt(Command):
    applies_to = [("console", "module", "name", "do_something")]
    [...]
    def run(self):
        [...]


Inheritance and aggregation

Entities can be defined in subclasses as a tree structure so that the leaves share some information from their proxy subclasses. The precedence goes bottom-up, that is, from the leaves to the entity classes. This is especially the case for :

  • config attribute (applies to consoles and modules) : Configurations are agreggated (in a ProxyConfig instance) so that an option that is common to multiple entities can be defined only once and modified for all these entities at once during the execution.
  • Metadata (especially useful for modules) : metadata is aggregated (during entity import only) so that, if multiple modules inheriting from a proxy class have, for instance, the same author, this data can be declared only once in the proxy class and applied to modules.

Metadata parsing

Metadata of entities can be defined in three different ways (can be combined, listed hereafter in inverse order of precedence) :

  1. Docstring : By default, Sploitkit provides a parsing function that follows the convention presented hereafter, resulting in a dictionary of metadata key-values. However, a custom parsing function can be input as an argument when instantiating a parent Console.
  2. meta attribute : A dictionary of metadata key-values that will update the final metadata dictionary.
  3. metadata attribute : Same as for meta (exists for a question of cross-compatibility with plugins of other frameworks).

This leads to a _metadata class attribute holding the metadata dictionary. Note that, when meta and metadata class attributes are use to update _metadata, they are removed to only hold this last one. This is mostly a question of compatibility with modules of other frameworks (e.g. Recon-ng).

Options can even be defined through the meta and/or metadata class attributes (but NOT directly _metadata as it is created/overwritten when parsing the docstring). Their format follows this convention : (name, default_value, required, description). It contains less fields than what is really supported (see the Option class in the next subsection) but, once again, it is mostly a question of compatibility with modules from other frameworks.

The default docstring format (parsed through a dedicated function within Sploitkit's utils) consists of sections separated by double newlines. Parsing occurs as follows :

  1. The first section is always the description.
  2. Next sections are handled this way :

    • If the first line of the section follows the convention hereafter, it is parsed as a separated field (saved in the metadata dictionary as lowercase) up to the next field-value OR section's end.

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      [Field]: [value]
      

      That is, the field name capitalized with no whitespace before the colon and whatever value, multiline.

    • If the first line of the section does not follow the convention, it is parsed as a comment and saved into the comments list of the metadata dictionary. Note that using the field name comments append the value to the comments list of the metadata dictionary.

Example: Writing a docstring for an entity
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class Example(object):
    \"""
    This is a test multi-line long 
     description.

    This is a first comment.

    Author: John Doe
             (john.doe@example.com)
    Version: 1.0
    Comments:
    - subcomment 1
    - subcomment 2

    Something: lorem ipsum
                paragraph

    This is a second comment,
     a multi-line one.
    \"""
    [...]

>>> parse_docstring(Example)
{'author': 'John Doe (john.doe@example.com)',
 'comments': ['This is a first comment.',
              ('subcomment 1', 'subcomment 2'),
              'This is a second comment, a multi-line one.'],
 'description': 'This is a test multi-line long description.',
 'something': 'lorem ipsum paragraph',
 'version': '1.0'}


Config and Option

A configuration object is an instance of the Config class subclassing the common type dict and refining its capabilities to handle special key-value objects called Option's that also have a description and other attributes (e.g. required). This way, it is easier to associate more data than simply a value to a key, i.e. when it comes to providing help text about the option.

A configuration is declared by providing a dictionary as the only positional argument and/or key-values as keyword-arguments. It is important to note that, if options are defined with the keyword-arguments, they won't of course have any other data defined but they will be easilly accessible for further tuning.

Example: Declaring a configuration (entity class attribute)
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from sploitkit import Config, Option, ROption

config = Config({
    Option(...),
    ROption(...),
})


Option and ROption

Two types of option exist (for a question of performance) : Option (the normal one) and ROption (aka Resetting Option) that triggers resetting the entity bindings (e.g. the commands applicability to the current console given the new option). So, beware that, when using the Option class, the modification of its value does not update bindings between entities.

An example of use of the behavior of ROption is when a config requirement is used in another entity which is to be enabled/disabled according to option's value. This way, entity bindings are reset when tuning the option like when starting a console (for more details on this, see section Console).

A configuration option object, that is, an instance of the Option or ROption class, is defined using multiple arguments :

Argument Type Default Description
name str option's name, conventionally uppercase
description str None help text for this option
required bool False whether it shall be defined or not
choices list/lambda None the possible values (as a list or lazily defined through a lambda function that outputs a list), used for validation ; its value can also be bool (the type, not as a string !) for setting choices to false and true
set_callback lambda None a function that is triggered after setting the value
unset_callback lambda None a function that is triggered after unsetting the value
transform lambda None a function transforming the value input as for any dictionary, but for computing a new value
validate lambda None by default, a lambda function that checks for the given choices if defined, but can be tuned accordingly

Each lambda function takes self as the first argument. transform and validate also takes option's value as the second argument.

Config declaration (extract from the FrameworkConsole class)
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config = Config({
    ...,
    ROption(
        'DEBUG',
        "debug mode",
        False,
        bool,
        set_callback=lambda o: o.config.console._set_logging(o.value),
    ): "false",
    ...,
    Option(
        'WORKSPACE',
        "folder where results are saved",
        True,
    ): "~/Notes",
})


Utility class methods