Class Workflow

python/workflow.py:246–594

``class Workflow`` in Binary Ninja defines the set of analyses to perform on a binary, including their dependencies and execution order. Workflows are represented as Directed Acyclic Graphs (DAGs), where each node corresponds to an :class:`Activity` (an individual analysis or action). Workflow

class Workflow(metaclass=_WorkflowMetaclass):
	"""
	``class Workflow`` in Binary Ninja defines the set of analyses to perform on a binary,
	including their dependencies and execution order.

	Workflows are represented as Directed Acyclic Graphs (DAGs), where each node corresponds to
	an :class:`Activity` (an individual analysis or action). Workflows are used to tailor the
	analysis process for :class:`BinaryView` or :class:`Function` objects, providing granular
	control over analysis tasks at module or function levels.

	A Workflow starts in an unregistered state, either by creating a new empty Workflow or by
	cloning an existing one. While unregistered, it is possible to add and remove :class:`Activity`
	objects, as well as modify the execution strategy. To apply a Workflow to a binary, it must be
	registered. Once registered, the Workflow becomes immutable and is available for use.

	:Example:

.. code-block:: python

		# Define the custom activity configuration
		configuration = json.dumps({
			"name": "analysis.plugins.xorStringDecoder",
			"title": "XOR String Decoder",
			"description": "This analysis step transforms XOR-encoded strings within the current function.",
			"eligibility": {
				"auto": {
					"default": False
				}
			}
		})

		# Clone the meta function workflow for customization
		workflow = Workflow("core.function.metaAnalysis").clone()

		# Register a new activity
		workflow.register_activity(Activity(
			configuration,
			action=lambda analysis_context: log_warn(
				f"Decoder running for function: {hex(analysis_context.function.start)}"
				# Insert decoder logic here :P
			)
		))

		# Insert the new activity before the "generateHighLevelIL" step
		workflow.insert("core.function.generateHighLevelIL", ["analysis.plugins.xorStringDecoder"])

		# Register the modified meta function workflow
		workflow.register()
	"""
	def __init__(self, name: str = "", handle: core.BNWorkflowHandle = None, query_registry: bool = True, object_handle: Union[core.BNFunctionHandle, core.BNBinaryViewHandle] = None):
		if handle is None:
			if query_registry:
				_handle = core.BNWorkflowInstance(str(name))
			else:
				_handle = core.BNCreateWorkflow(name)
		else:
			_handle = handle
		assert _handle is not None