adtree-viz
Project description
adtree-viz
Intro
An Attack-Defense Tree modelling lib that allows user to model attack-defense scenarios using an internal DSL.
Project inspired by https://github.com/hyakuhei/attackTrees and https://github.com/tahti/ADTool2.
The main goals are:
- add support for AND nodes
- be able to break down a large tree into multiple subtrees.
- keep it simple, only Attack and Defense nodes
Usage
Requirements:
Graphviz
Python 3.9
Install the library
pip install adtree-viz
Quick start
from adtree.models import Attack, Defence, AndGate, ADTree
from adtree.renderer import Renderer
from adtree.themes import RedBlueFillTheme
tree = ADTree("REFS.01", Attack("the goal", [
Attack("path1", [
Defence("defend path1", [
Attack("path1 defence defeated")
])
]),
Attack("path2", [
Attack("path2.1"),
AndGate([
Attack("path3.1"),
Attack("path3.2"),
]),
]),
]))
theme = RedBlueFillTheme()
renderer = Renderer(theme=theme, output_format="png", view=True)
renderer.render(tree=tree, filename="my-adtree")
The above should produce an attack-defence tree like this:
Composing trees
Trees can be composed of multiple subtrees.
Which of the subtrees get expanded is decided at render time based on the subtrees_to_expand
variable.
from adtree.models import Attack, ADTree, ExternalADTree
from adtree.renderer import Renderer
from adtree.themes import NoFormatTheme
some_external_ref = ExternalADTree("EXT.01", "External resource covered by other docs")
some_internal_ref1 = ADTree("INT.01", root_node=Attack("internal path1", [
Attack("path 1.1", [
ADTree("INT.01.A", Attack("nested path 1.1A"))
])
]))
some_internal_ref2 = ADTree("INT.02", root_node=Attack("internal path2", [
Attack("path 2.1")
]))
tree = ADTree("REFS.01", Attack("node1", [
some_external_ref,
some_internal_ref1,
some_internal_ref2
]))
theme = NoFormatTheme()
renderer = Renderer(theme=theme, output_format="png", view=False)
# Default is to not expand
renderer.render(tree=tree, filename="default")
# Optionally expand some nodes
renderer.render(tree=tree, subtrees_to_expand=[some_internal_ref1], filename="partially_expanded")
The above will render two files.
One with all the subtrees collapsed (the default):
And another file with one subtree expanded:
Analysing trees
Currently, there is only one analyser available, the IsDefendedAnalyser. Traverse the tree and mark each nodes as either defended or undefended A node is considered defended if:
- is a Defence node and has no children
- is an Attack node and has a direct defended Defence node as child
- is an Attack or Defence node and all child nodes are defended nodes
- is an AndGate and at least one child node is defended
Example with custom rendering of the defended nodes
from adtree.models import NodeType, Node, Attack, ADTree, Defence, AndGate
from adtree.analysers import IsDefendedAnalyser
from adtree.renderer import Renderer
from adtree.themes import NoFormatTheme
class CustomIsDefendedTheme(NoFormatTheme):
def get_node_attrs_for(self, node: Node):
metadata_attrs = {
"style": "filled"
}
if node.get_node_type() == NodeType.DEFENCE:
metadata_attrs |= {
"shape": "box",
}
if node.get_node_type() == NodeType.AND_GATE:
metadata_attrs |= {
"shape": "triangle",
}
if node.has_metadata(IsDefendedAnalyser.METADATA_KEY):
fillcolor = "#C8FFCB" if node.get_metadata(IsDefendedAnalyser.METADATA_KEY) else "#FFD3D6"
metadata_attrs |= {
"fillcolor": fillcolor,
}
return metadata_attrs
tree = ADTree("REFS.01", Attack("the goal", [
Attack("path1", [
Defence("defend path1", [
Attack("path1 defence defeated")
])
]),
Attack("path2", [
Attack("path2.1", [
Defence("def2.1"),
Attack("path2.1.1")
]),
AndGate([
Attack("path3.1"),
Attack("path3.2", [
Defence("defended")
]),
]),
]),
]))
analyser = IsDefendedAnalyser()
analyser.analyse_tree(tree)
theme = CustomIsDefendedTheme()
renderer = Renderer(theme=theme, output_format="png", view=False)
# Default is to not expand
renderer.render(tree=tree, filename="default")
The above should produce an attack-defence tree like this:
Development
Create a venv
python3.9 -m venv venv
Activate
. venv/bin/activate
Install deps
pip install -r requirements.txt
Run tests
PYTHONPATH=src python -m pytest
Run individual test file
PYTHONPATH=src python -m pytest ./test/adtree/test_theme.py
Run individual test methods
PYTHONPATH=src python -m pytest --capture=no ./test/adtree/test_theme.py -k "metadata"
Release to Github and PyPi
Create tag and push
./release.sh
Manually build and release
Run the below to generate a distributable archive:
python3 -m build
The adtree-viz-x.xx.x.tar.gz
archive can be found in the dist
folder.
Deploy to PyPi
python3 -m twine upload -r pypi dist/*
# Use __token__ as username
# Use PyPi API TOKEN as password
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file adtree-viz-0.0.10.tar.gz
.
File metadata
- Download URL: adtree-viz-0.0.10.tar.gz
- Upload date:
- Size: 11.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.11.1
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 752ca90acdedf81faaeb218b5fecfed7dd11abc0091066c96ebd542696648643 |
|
MD5 | a6d83f9dd7365d35c24ffdbb7dcf25ed |
|
BLAKE2b-256 | 3766cb169f0f739369ffce799e7907b657495402f6a2ac78720952372f6edb92 |
File details
Details for the file adtree_viz-0.0.10-py3-none-any.whl
.
File metadata
- Download URL: adtree_viz-0.0.10-py3-none-any.whl
- Upload date:
- Size: 10.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.11.1
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | f7aeacd303b2a2c43fd7a2099ebed74c0b66dad7c99f992a269d1e1c82712dba |
|
MD5 | 31516ad7add401cd4c562fb03b001019 |
|
BLAKE2b-256 | e1140a620a0e1dc0ecf347b717be1cb0b7d6808013759c8e2e32b4afb925c384 |