FlowStrider automates data flow-based threat modeling
FlowStrider is an architectural threat modeling tool designed to support the identification, mitigation, documentation, and management of threats in a given software system.
Why use FlowStrider?
🛠 Refine System Representation: Assists in adding relevant information to the system representation to enhance the quality of analysis.
🛡 Identification of Threats: Uses two built-in threat catalogs to identify threats based on the system representation.
📊 Reporting: Supports the documentation and management of identified threats in a structured report.
For the full documentation of the FlowStrider tool, please visit the GitLab page or build the documentation locally (using tox -e docs
).
As a prerequisite, FlowStrider requires Python (tested with versions 3.10 and 3.12) and Graphviz, which can be installed via apt install graphviz
or as described on their website.
Install the tool directly using pip install flowstrider
or clone this repository and install it (using git clone
and pip install
).
Dependencies are handled automatically during the installation process as defined in setup.cfg
.
FlowStrider takes a system representation as input in the form of a data flow graph in json file format (example see below).
This data flow graph is then used to identify potential threats.
flowstrider elicit dataflow_graph.json [--output (off|pdf)]
[--management-path management-file-path]
[--fail-on-threat (off|undecided|todo|all)]
[--out-lang (en|de)]
The results can be saved as a PDF file using [--output pdf] (default=off)
. The PDF
includes a visual representation of the graph generated with GraphViz and details about the identified threats.
The [--management-path]
gives the path to a json file where information about the
management state of each existing threat can be modified. If the file doesn't exist
yet, it will be created.
If [--fail-on-threat] (default=off)
is set to off, the tool will not fail if it
finds threats. If set to other options, the tool will fail if there is a threat with
an unsufficient management state to explain its presence with the set fail option.
By default, each found threat is asigned the management state Undecided
. The
management state can be modified in the management file indicated by the
[--management-path]
option. There are seven different states each threat can take
on as seen in the left column in the table below. The table also shows which state
will fail the tool if run with a specific option for the [--fail-on-threat]
argument.
off | undecided | todo | all | |
---|---|---|---|---|
Undecided | pass | fail | fail | fail |
Delegate | pass | pass | fail | fail |
Mitigate | pass | pass | fail | fail |
Avoid | pass | pass | fail | fail |
Accept | pass | pass | pass | fail |
Delegated | pass | pass | pass | fail |
Mitigated | pass | pass | pass | fail |
The parameter [--out-lang] (default=en)
denotes the output language used for the
threats and the report.
The tool relies on metadata (stored in the attributes property of the nodes and edges) to accurately elicit threats.
An .xlsx file can be generated to get an overview of the attributes stored in the metadata, as well as any relevant attributes that are missing.
flowstrider metadata dataflow_graph.json [--out-lang (en|de)]
The parameter [--out-lang] (default=en)
denotes the output language used for the
threats and the pdf.
After filling out the missing metadata in the xlsx file, that file can be used to
update the existing json file of the dataflow graph. The modified and added
attributes are then being updated as properties to the nodes and edges of the graph.
flowstrider update dataflow_graph.json metadata_overview.xlsx
FlowStrider takes a system representation as input in the form of a data flow graph in json file format.
See the Data Flow Graph section in the documentation for more information on how do define elements and assign attributes.
In the tags of the dfd at the bottom of the json file, one can define the threat catalogs the tool is checking against.
Currently, there are the threat catalogs stride and bsi_rules.
Here is a minimal example of such a dataflow graph in .json:
{
"dfd": {
"id": "Example",
"nodes": {
"node1": {
"id": "node1",
"name": "User",
"tags": [
"STRIDE:Interactor"
],
"attributes": {}
},
"node2": {
"id": "node2",
"name": "Application",
"tags": [
"STRIDE:Process"
],
"attributes": {}
}
},
"edges": {
"edge1": {
"id": "edge1",
"source_id": "node1",
"sink_id": "node2",
"name": "http_request",
"tags": [
"STRIDE:Dataflow"
],
"attributes": {}
}
},
"clusters": {
"cluster1":{
"id": "cluster1",
"node_ids": [
"node2"
],
"name": "Internet",
"tags": [
"STRIDE:TrustBoundary"
],
"attributes": {}
}
},
"name": "",
"tags": [
"bsi_rules"
],
"attributes": {}
}
}
All files in this repository fall under the stated license in LICENSE.txt. The full licensing
terms of used dependencies can be found in LICENSE-3RD-PARTY.txt
Please make sure to read CONTRIBUTING.rst and follow the preparations before making any
changes to the project.
The paper "FlowStrider: Low-friction Continuous Threat Modeling" was accepted at the Tool Track of ASE25.
This work was done as part of the AVATAR competence cluster, funded by the Federal Ministry of Research, Technology and Space (funding code: 16KISA021).