async def _create_detection_operation(self, red_op_name, red_op_id,
red_op_access):
planner = (await self.get_service('data_svc').locate(
'planners', match=dict(name='atomic')))[0]
adversary_id = self.get_config(prop='adversary', name='gameboard')
adversary = (await self.data_svc.locate(
'adversaries', match=dict(adversary_id=adversary_id)))[0]
obj = (await self.data_svc.locate('objectives',
match=dict(name='default')))[0]
agent = Agent(0, 0, 0, paw='gameboard_detection')
access = self.Access.BLUE
detection_operation = Operation(name=red_op_name + '_' +
str(red_op_id) +
self.blue_op_name_modifier,
agents=[agent],
adversary=adversary,
access=access,
planner=planner,
group='blue')
detection_operation.objective = obj
detection_operation.set_start_details()
return [await self.data_svc.store(detection_operation)]
def op_with_learning_and_seeded(ability, adversary, operation_agent,
parse_datestring):
sc = Source(id='3124',
name='test',
facts=[Fact(trait='domain.user.name', value='bob')])
op = Operation(id='6789',
name='testC',
agents=[],
adversary=adversary,
source=sc,
use_learning_parsers=True)
# patch operation to make it 'realistic'
op.start = parse_datestring(OP_START_TIME)
op.adversary = op.adversary()
op.planner = Planner(planner_id='12345',
name='test_planner',
module='not.an.actual.planner',
params=None)
op.objective = Objective(id='6428', name='not_an_objective')
t_operation_agent = operation_agent
t_operation_agent.paw = '123456'
op.agents = [t_operation_agent]
return op
