notebooks/c2_interactive_interface.ipynb

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  {
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   "source": [
    "Copyright (c) Microsoft Corporation. All rights reserved. Licensed under the MIT License.\n",
    "\n",
    "# Command and Control interface\n",
    "This notebooks shows how to interact with the command&control server to observe the environment and initiate actions on the nodes where the attacker client is installed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
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       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
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       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import networkx as nx\n",
    "from datetime import datetime\n",
    "from tabulate import tabulate\n",
    "import cyberbattle.simulation.model as model\n",
    "import cyberbattle.simulation.actions as actions\n",
    "import cyberbattle.simulation.commandcontrol as commandcontrol\n",
    "import importlib\n",
    "importlib.reload(model)\n",
    "importlib.reload(actions)\n",
    "importlib.reload(commandcontrol)\n",
    "import plotly.offline as plo\n",
    "plo.init_notebook_mode(connected=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We first create a simulation environment from a randomly generated network graph."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "g = nx.erdos_renyi_graph(35,0.05,directed=True)\n",
    "g = model.assign_random_labels(g)\n",
    "env = model.Environment(network=g, vulnerability_library=dict([]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We create the `CommandControl` object used to the environment and execute actions, and plot the graph explored so far.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "c = commandcontrol.CommandControl(env)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nodes disovered so far: [{'id': '16', 'status': 'owned'}]\n"
     ]
    },
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   ],
   "source": [
    "c.plot_nodes()\n",
    "print(\"Nodes disovered so far: \" + str(c.list_nodes()))\n",
    "starting_node = c.list_nodes()[0]['id']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For debugging purpose it's also convient to view the internals of the environment via the `EnvironmentDebugging` object. For instance we can use it to plot the entire graph, including nodes that were not discovered yet by the attacker."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "dbg = commandcontrol.EnvironmentDebugging(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Name: \n",
      "Type: DiGraph\n",
      "Number of nodes: 35\n",
      "Number of edges: 62\n",
      "Average in degree:   1.7714\n",
      "Average out degree:   1.7714\n"
     ]
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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "env.plot_environment_graph()\n",
    "print(nx.info(env.network))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "id  status    local_attacks                 remote_attacks\n",
      "----  --------  ----------------------------  ----------------\n",
      "  16  owned     ['RecentlyAccessedMachines']  []\n"
     ]
    }
   ],
   "source": [
    "print(tabulate(c.list_all_attacks(),{}))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<cyberbattle.simulation.model.LeakedNodesId at 0x2adac5078e0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "outcome = c.run_attack(starting_node, 'RecentlyAccessedMachines')\n",
    "outcome"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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    "c.plot_nodes()"
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  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "id  status\n",
      "----  ----------\n",
      "  16  owned\n",
      "  21  discovered\n"
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   ],
   "source": [
    "print(tabulate(c.list_nodes(),{}))"
   ]
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   "execution_count": 11,
   "metadata": {
    "tags": []
   },
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     "output_type": "stream",
     "text": [
      "id  status      local_attacks                 remote_attacks\n",
      "----  ----------  ----------------------------  ----------------\n",
      "  16  owned       ['RecentlyAccessedMachines']  []\n",
      "  21  discovered                                []\n"
     ]
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   ],
   "source": [
    "print(tabulate(c.list_all_attacks(),{}))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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