risk_tag_frequency.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3676e649-f8f3-45b8-85fa-dbdbb38b831a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8d1e032a-3273-4fcd-aa2e-c0bbadd610ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>project_name</th>\n",
       "      <th>Smart contract address</th>\n",
       "      <th>Blog post link</th>\n",
       "      <th>Audit website</th>\n",
       "      <th>Chain</th>\n",
       "      <th>Is_closed_source</th>\n",
       "      <th>hidden_owner</th>\n",
       "      <th>anti_whale_modifiable</th>\n",
       "      <th>Is_anti_whale</th>\n",
       "      <th>Is_honeypot</th>\n",
       "      <th>...</th>\n",
       "      <th>centralized_risk_high</th>\n",
       "      <th>centralized_risk_low</th>\n",
       "      <th>event_setter</th>\n",
       "      <th>external_dependencies</th>\n",
       "      <th>immutable_states</th>\n",
       "      <th>reentrancy_without_eth_transfer</th>\n",
       "      <th>incorrect_inheritance_order</th>\n",
       "      <th>shadowing_local</th>\n",
       "      <th>events_maths</th>\n",
       "      <th>Summary/rationale of risk tags marked true</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Data Analytics</td>\n",
       "      <td>384571416209d08623c6ace9422613fc8970475d</td>\n",
       "      <td>https://chainsecurity.com/security-audit/circl...</td>\n",
       "      <td>https://chainsecurity.com</td>\n",
       "      <td>Ethereum</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>Bad Contract: Assigned for flaws that indicate...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Data Analytics</td>\n",
       "      <td>0xAb5801a7D398351b8bE11C439e05C5B3259ae9B</td>\n",
       "      <td>https://stackoverflow.com/questions/75030483/w...</td>\n",
       "      <td>https://studygroup.moralis.io/t/compilation-er...</td>\n",
       "      <td>Ethereum</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>Summary/rationale of risk tags marked true: Th...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Data Analytics</td>\n",
       "      <td>0x4B20993Bc481177ec7E8f571ceCaE8A9e22C02db</td>\n",
       "      <td>https://stackoverflow.com/questions/71115106/s...</td>\n",
       "      <td>https://ethereum.stackexchange.com/questions/1...</td>\n",
       "      <td>Ethereum</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Data Analytics</td>\n",
       "      <td>0x78731D3Ca6b7E34aC0F824c42a7cC18A495cabaB</td>\n",
       "      <td>https://stackoverflow.com/questions/75030483/w...</td>\n",
       "      <td>https://studygroup.moralis.io/t/compilation-er...</td>\n",
       "      <td>Ethereum</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Data Analytics</td>\n",
       "      <td>0x617F2E2fD72FD9D5503197092aC168c91465E7f2</td>\n",
       "      <td>https://stackoverflow.com/questions/69466137/h...</td>\n",
       "      <td>https://ethereum.stackexchange.com/questions/1...</td>\n",
       "      <td>Ethereum</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>The smart contract is marked with risks such a...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 38 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     project_name                      Smart contract address  \\\n",
       "0  Data Analytics    384571416209d08623c6ace9422613fc8970475d   \n",
       "1  Data Analytics   0xAb5801a7D398351b8bE11C439e05C5B3259ae9B   \n",
       "2  Data Analytics  0x4B20993Bc481177ec7E8f571ceCaE8A9e22C02db   \n",
       "3  Data Analytics  0x78731D3Ca6b7E34aC0F824c42a7cC18A495cabaB   \n",
       "4  Data Analytics  0x617F2E2fD72FD9D5503197092aC168c91465E7f2   \n",
       "\n",
       "                                      Blog post link  \\\n",
       "0  https://chainsecurity.com/security-audit/circl...   \n",
       "1  https://stackoverflow.com/questions/75030483/w...   \n",
       "2  https://stackoverflow.com/questions/71115106/s...   \n",
       "3  https://stackoverflow.com/questions/75030483/w...   \n",
       "4  https://stackoverflow.com/questions/69466137/h...   \n",
       "\n",
       "                                       Audit website     Chain  \\\n",
       "0                          https://chainsecurity.com  Ethereum   \n",
       "1  https://studygroup.moralis.io/t/compilation-er...  Ethereum   \n",
       "2  https://ethereum.stackexchange.com/questions/1...  Ethereum   \n",
       "3  https://studygroup.moralis.io/t/compilation-er...  Ethereum   \n",
       "4  https://ethereum.stackexchange.com/questions/1...  Ethereum   \n",
       "\n",
       "   Is_closed_source  hidden_owner  anti_whale_modifiable  Is_anti_whale  \\\n",
       "0             False         False                  False          False   \n",
       "1             False         False                   True           True   \n",
       "2              True         False                  False           True   \n",
       "3              True         False                  False          False   \n",
       "4              True         False                   True          False   \n",
       "\n",
       "   Is_honeypot  ...  centralized_risk_high  centralized_risk_low  \\\n",
       "0        False  ...                  False                 False   \n",
       "1        False  ...                  False                  True   \n",
       "2        False  ...                  False                  True   \n",
       "3         True  ...                  False                  True   \n",
       "4         True  ...                  False                 False   \n",
       "\n",
       "   event_setter  external_dependencies  immutable_states  \\\n",
       "0          True                   True              True   \n",
       "1         False                   True             False   \n",
       "2         False                   True             False   \n",
       "3         False                  False              True   \n",
       "4          True                   True             False   \n",
       "\n",
       "   reentrancy_without_eth_transfer  incorrect_inheritance_order  \\\n",
       "0                             True                        False   \n",
       "1                            False                         True   \n",
       "2                            False                        False   \n",
       "3                             True                        False   \n",
       "4                             True                        False   \n",
       "\n",
       "   shadowing_local  events_maths  \\\n",
       "0            False         False   \n",
       "1            False          True   \n",
       "2             True          True   \n",
       "3            False          True   \n",
       "4            False          True   \n",
       "\n",
       "          Summary/rationale of risk tags marked true  \n",
       "0  Bad Contract: Assigned for flaws that indicate...  \n",
       "1  Summary/rationale of risk tags marked true: Th...  \n",
       "2                                                NaN  \n",
       "3                                                NaN  \n",
       "4  The smart contract is marked with risks such a...  \n",
       "\n",
       "[5 rows x 38 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_excel('compiled_risk_data.xlsx')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "963487bf-6e89-45f7-ac3b-91b33504553b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1093 entries, 0 to 1092\n",
      "Data columns (total 38 columns):\n",
      " #   Column                                      Non-Null Count  Dtype \n",
      "---  ------                                      --------------  ----- \n",
      " 0   project_name                                1093 non-null   object\n",
      " 1   Smart contract address                      1093 non-null   object\n",
      " 2   Blog post link                              1093 non-null   object\n",
      " 3   Audit website                               1093 non-null   object\n",
      " 4   Chain                                       1093 non-null   object\n",
      " 5   Is_closed_source                            1093 non-null   bool  \n",
      " 6   hidden_owner                                1093 non-null   bool  \n",
      " 7   anti_whale_modifiable                       1093 non-null   bool  \n",
      " 8   Is_anti_whale                               1093 non-null   bool  \n",
      " 9   Is_honeypot                                 1093 non-null   bool  \n",
      " 10  buy_tax                                     1093 non-null   bool  \n",
      " 11  sell_tax                                    1093 non-null   bool  \n",
      " 12  slippage_modifiable                         1093 non-null   bool  \n",
      " 13  Is_blacklisted                              1093 non-null   bool  \n",
      " 14  can_take_back_ownership                     1093 non-null   bool  \n",
      " 15  owner_change_balance                        1093 non-null   bool  \n",
      " 16  is_airdrop_scam                             1093 non-null   bool  \n",
      " 17  selfdestruct                                1093 non-null   bool  \n",
      " 18  trust_list                                  1093 non-null   bool  \n",
      " 19  is_whitelisted                              1093 non-null   bool  \n",
      " 20  is_fake_token                               1093 non-null   bool  \n",
      " 21  illegal_unicode                             1093 non-null   bool  \n",
      " 22  exploitation                                1093 non-null   bool  \n",
      " 23  bad_contract                                1093 non-null   bool  \n",
      " 24  reusing_state_variable                      1093 non-null   bool  \n",
      " 25  encode_packed_collision                     1093 non-null   bool  \n",
      " 26  encode_packed_parameters                    1093 non-null   bool  \n",
      " 27  centralized_risk_medium                     1093 non-null   bool  \n",
      " 28  centralized_risk_high                       1093 non-null   bool  \n",
      " 29  centralized_risk_low                        1093 non-null   bool  \n",
      " 30  event_setter                                1093 non-null   bool  \n",
      " 31  external_dependencies                       1093 non-null   bool  \n",
      " 32  immutable_states                            1093 non-null   bool  \n",
      " 33  reentrancy_without_eth_transfer             1093 non-null   bool  \n",
      " 34  incorrect_inheritance_order                 1093 non-null   bool  \n",
      " 35  shadowing_local                             1093 non-null   bool  \n",
      " 36  events_maths                                1093 non-null   bool  \n",
      " 37  Summary/rationale of risk tags marked true  701 non-null    object\n",
      "dtypes: bool(32), object(6)\n",
      "memory usage: 85.5+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "252d0f9e-12cd-4f00-a6b3-f1e22e6c69f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "risk_columns = ['Is_closed_source', 'hidden_owner', 'anti_whale_modifiable',\n",
    "       'Is_anti_whale', 'Is_honeypot', 'buy_tax', 'sell_tax',\n",
    "       'slippage_modifiable', 'Is_blacklisted', 'can_take_back_ownership',\n",
    "       'owner_change_balance', 'is_airdrop_scam', 'selfdestruct', 'trust_list',\n",
    "       'is_whitelisted', 'is_fake_token', 'illegal_unicode', 'exploitation',\n",
    "       'bad_contract', 'reusing_state_variable', 'encode_packed_collision',\n",
    "       'encode_packed_parameters', 'centralized_risk_medium',\n",
    "       'centralized_risk_high', 'centralized_risk_low', 'event_setter',\n",
    "       'external_dependencies', 'immutable_states',\n",
    "       'reentrancy_without_eth_transfer', 'incorrect_inheritance_order',\n",
    "       'shadowing_local', 'events_maths']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "44b7932d-b90b-4300-8c8b-7ae5aca7bcb1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Is_closed_source                   146\n",
       "hidden_owner                       164\n",
       "anti_whale_modifiable              122\n",
       "Is_anti_whale                      155\n",
       "Is_honeypot                         94\n",
       "buy_tax                            128\n",
       "sell_tax                           126\n",
       "slippage_modifiable                149\n",
       "Is_blacklisted                      81\n",
       "can_take_back_ownership            194\n",
       "owner_change_balance               222\n",
       "is_airdrop_scam                     69\n",
       "selfdestruct                       116\n",
       "trust_list                         149\n",
       "is_whitelisted                     109\n",
       "is_fake_token                       90\n",
       "illegal_unicode                     62\n",
       "exploitation                       468\n",
       "bad_contract                       373\n",
       "reusing_state_variable             124\n",
       "encode_packed_collision             81\n",
       "encode_packed_parameters            87\n",
       "centralized_risk_medium            283\n",
       "centralized_risk_high              205\n",
       "centralized_risk_low               190\n",
       "event_setter                       149\n",
       "external_dependencies              316\n",
       "immutable_states                   154\n",
       "reentrancy_without_eth_transfer    199\n",
       "incorrect_inheritance_order        100\n",
       "shadowing_local                     88\n",
       "events_maths                       149\n",
       "Name: True, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frequencies = df[risk_columns].apply(lambda x: x.value_counts()).loc[True]\n",
    "frequencies = frequencies.fillna(0)\n",
    "frequencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "7efa3be4-0545-4cbb-bf86-e6fc9ce09769",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style(\"whitegrid\")\n",
    "plt.figure(figsize=(12, 8))\n",
    "sns.barplot(x=frequencies.index, y=frequencies.values, palette='viridis')\n",
    "plt.title('Frequency of True Values for Each Risk Tag')\n",
    "plt.xlabel('Risk Tags')\n",
    "plt.ylabel('Frequency of True')\n",
    "plt.xticks(rotation=90)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1507c7fe-624f-4a46-bb87-aff3dc88a958",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}