cysecpython.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "cysecpython.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/sidneypepo/cysecpython/blob/master/cysecpython.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iV2_BT7bcVMl",
        "colab_type": "text"
      },
      "source": [
        "# **CySecPython**\n",
        "<img src=\"https://s7.gifyu.com/images/introf3009454ed68c0ef.gif\" width=\"650\" align=\"right\"/>\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dvugUvu8D2NO",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "87400df5-2fed-487f-e18d-847e8c1a7407"
      },
      "source": [
        "#Imprimindo banner\n",
        "print(\"\\033[0;37;40m.s5SSSs.          .s5SSSs.                      .s5SSSs.                                                 \\nsS    SS. .s5 s.  sS    SS. .s5SSSs.  .s5SSSs.  sS    SS. .s5 s.  .s5SSSSs. .s    s.  .s5SSSs.  .s    s. \\nsS    `:;     SS. sS    `:;       SS.       SS. sS    S%S     SS.    SSS          SS.       SS.       SS.\\nSS        ssS SSS SS        sS    `:; sS    `:; SS    S%S ssS SSS    S%S    sS    S%S sS    S%S sSs.  S%S\\nSS         SSSSS  `:;;;;.   SSSs.     SS        SS .sS::'  SSSSS     S%S    SSSs. S%S SS    S%S SS `S.S%S\\nSS          SSS         ;;. SS        SS        SS          SSS      S%S    SS    S%S SS    S%S SS  `sS%S\\nSS          `:;         `:; SS        SS        SS          `:;      `:;    SS    `:; SS    `:; SS    `:;\\nSS    ;,.   ;,.   .,;   ;,. SS    ;,. SS    ;,. SS          ;,.      ;,.    SS    ;,. SS    ;,. SS    ;,.\\n`:;;;;;:'   ;:'   `:;;;;;:' `:;;;;;:' `:;;;;;:' `:          ;:'      ;:'    :;    ;:' `:;;;;;:' :;    ;:'\")\n",
        "print(\"\\n---------------------> Coded by Euclides Neto, Jonathan Andriel e & Sidney 'PEPO' <----------------------\\033[0;37;40m\")"
      ],
      "execution_count": 1337,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\u001b[0;37;40m.s5SSSs.          .s5SSSs.                      .s5SSSs.                                                 \n",
            "sS    SS. .s5 s.  sS    SS. .s5SSSs.  .s5SSSs.  sS    SS. .s5 s.  .s5SSSSs. .s    s.  .s5SSSs.  .s    s. \n",
            "sS    `:;     SS. sS    `:;       SS.       SS. sS    S%S     SS.    SSS          SS.       SS.       SS.\n",
            "SS        ssS SSS SS        sS    `:; sS    `:; SS    S%S ssS SSS    S%S    sS    S%S sS    S%S sSs.  S%S\n",
            "SS         SSSSS  `:;;;;.   SSSs.     SS        SS .sS::'  SSSSS     S%S    SSSs. S%S SS    S%S SS `S.S%S\n",
            "SS          SSS         ;;. SS        SS        SS          SSS      S%S    SS    S%S SS    S%S SS  `sS%S\n",
            "SS          `:;         `:; SS        SS        SS          `:;      `:;    SS    `:; SS    `:; SS    `:;\n",
            "SS    ;,.   ;,.   .,;   ;,. SS    ;,. SS    ;,. SS          ;,.      ;,.    SS    ;,. SS    ;,. SS    ;,.\n",
            "`:;;;;;:'   ;:'   `:;;;;;:' `:;;;;;:' `:;;;;;:' `:          ;:'      ;:'    :;    ;:' `:;;;;;:' :;    ;:'\n",
            "\n",
            "---------------------> Coded by Euclides Neto, Jonathan Andriel e & Sidney 'PEPO' <----------------------\u001b[0;37;40m\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IC-AZcSCWoNA",
        "colab_type": "text"
      },
      "source": [
        "# **Sobre o projeto**\n",
        "\n",
        "CySecPython é um projeto que visa a análise e compreensão dos três tipos de ataques cibernéticos de engenharia social mais utilizados na atualidade, criado por: \n",
        "*   Euclides Neto\n",
        "*   Jonathan Andriel\n",
        "*   Sidney Pedro\n",
        "\n",
        "O projeto foi orientado pelo professor \n",
        "*   Carlos Artur Guimarães, através do Integra School do Instituto Metrópole Digital da Universidade Federal do Rio Grande do Norte (IMD-UFRN). \n",
        "\n",
        "Além disso, foi desenvolvido para critérios avaliativos do curso Introdução à Programação com Python, seguindo o nono objetivo da Organização das Nações Unidas para o ano de 2030 (ONU 2030), \"construir infraestruturas resilientes, promover a industrialização inclusiva e sustentável e fomentar a inovação\". \n",
        "\n",
        "<img src=\"https://hongkong.imd.ufrn.br/filemanagerportal/source/2020/Integra_School.png\" width=\"600\"/>\n",
        "\n",
        "## O que é engenharia social?\n",
        "Esta é a técnica mais utilizada por hackers, crackers e criminosos em geral, na qual consiste em um atacante manipular, persuadir ou enganar uma vítima de tal forma que a mesma forneça informações pessoais, credenciais de acesso ou até mesmo acesso lícito ou ilícito de seus dispositivos informáticos sem ter consciência de tal ato."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fPNzSUenA66f",
        "colab_type": "text"
      },
      "source": [
        "# **Malwares via spam**\n",
        "\n",
        "Spam é qualquer tipo de comunicação digital indesejada e não solicitada, muitas vezes um e-mail, que é enviado em massa, trazendo assim um certo desconforto para o usuário que vizualizar a página ou mesmo trazendo informações chamativas para o mesmo, como ofertas ilegítimas, produtos \"milagrosos\" ou até mesmo apelo sexual. Tudo isso com o principal intuito de fazer o usuário clicar naquele spam. Muitas vezes, spam's são apenas publicidades de algo, mas o que muitos não sabem é que aquela pequena mensagem pode conter um programa malicioso (malware) que, se executado, pode causar grandes problemas para o usuário e seus dispositivos. \n",
        "\n",
        "* ##   Spyware:\n",
        "Este tipo de malware é um programa malicioso que infiltra-se em seu dispositivo e espiona (spy), coleta arquivos, furta informações confidenciais armazenadas no dispositivo da vítima e dados pessoais, como emails, senhas e dados bancários. O spyware, após infectar algo, monitora toda a atividade de aparelhos e faz o envio dos mesmos para o atacante responsável pelo ataque.\n",
        "\n",
        "* ##   Ransomware:\n",
        "Como os spywares, este é um tipo de programa malicioso que furta arquivos e dados pessoais dos usuários, mas no caso dos ransomwares, ele criptografa todos os arquivos do dispositivo e exige um pagamento para resgate (ransom) dos arquivos para recuperar o acesso a eles.\n",
        "\n",
        "Segundo uma das maiores empresas de segurança da informação, a Kaspersky Lab, foi analisado que no panorama mundial das ameaças cibernéticas no primeiro trimestre deste ano, o Brasil está em oitavo lugar no ranking de países que mais recebem spam's diários, como podemos ver no gráfico a seguir:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "T7i4GE5eFOFz",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 395
        },
        "outputId": "3fe3af20-d288-4ca6-fd63-51362d3ad117"
      },
      "source": [
        "#Importando bibliotecas utilizadas\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "#Importando dados\n",
        "total_de_spams = pd.read_csv('https://raw.githubusercontent.com/sidneypepo/cysecpython/master/files/dados-spam.csv', usecols=['Total de spams diários'])\n",
        " \n",
        "#Plotando gráfico\n",
        "plt.style.use('dark_background')\n",
        "plt.style.context('dark_background')\n",
        "total_de_spams.plot(color=\"#ff2929\")\n",
        " \n",
        "#Configurações do gráfico\n",
        "plt.title('Ataques por spam no Brasil da primeira quinzena de Junho\\n')\n",
        "plt.xlabel('Dias')\n",
        "plt.ylabel('Número de spam\\'s (em milhões)')\n",
        "plt.xlim(1, 15)\n",
        "plt.ylim(0, 40000000)\n",
        "plt.grid(True)\n",
        "plt.show()\n",
        " \n",
        "#Fonte\n",
        "print(\"\\nFONTE: \\n<ESTATÍSTICAS | Mapa em tempo real de ameaças cibernéticas da Kaspersky. \\n[S. l.]: Kaspersky Lab, 2020. Disponível em: https://cybermap.kaspersky.com/pt/stats/#country=215&type=kas&period=m. \\nAcesso em: 18 jun. 2020.>\")"
      ],
      "execution_count": 1337,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "FONTE: \n",
            "<ESTATÍSTICAS | Mapa em tempo real de ameaças cibernéticas da Kaspersky. \n",
            "[S. l.]: Kaspersky Lab, 2020. Disponível em: https://cybermap.kaspersky.com/pt/stats/#country=215&type=kas&period=m. \n",
            "Acesso em: 18 jun. 2020.>\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UDJe_gnCT9kJ",
        "colab_type": "text"
      },
      "source": [
        "## **Roubo de dados via phishing**\n",
        "\n",
        "Phishing é um termo originado do inglês que se trata de uma maneira de \"pescar\" (phishing) dados. Essa ação é caracterizada pela tentativa de adquirir ilicitamente informações de um pessoa, sejam senhas, dados financeiros, dados bancários, números de cartões de crédito ou simplesmente informações pessoais. O fraudador utiliza e-mail, aplicativos e sites que são projetados especificamente para roubar dados pessoais.\n",
        "\n",
        "Segundo a gigante da tecnologia, Trend Micro, o phishing está em ascensão. Segundo dados da empresa, os países que mais sofreram por esse tipo de ataque em 2019, foram os Estados Unidos, Japão e Holanda. Confira no gráfico abaixo a proporção desses ataques:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZDs5NwKkX9r8",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 398
        },
        "outputId": "43ab5161-a622-4ad9-85d8-0f481ccfe7b3"
      },
      "source": [
        "#Importando bibliotecas utilizadas\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "#Importando dados\n",
        "pais_total = [204653, 179869, 38376]\n",
        " \n",
        "#Plotando gráfico\n",
        "plt.style.use('dark_background')\n",
        "plt.style.context('dark_background')\n",
        "fig, ax = plt.subplots()\n",
        " \n",
        "#Configurações do gráfico\n",
        "ax.set_title('Países com maior número ataques de phishing para roubo de credenciais\\n')\n",
        "paises = ['Holanda', 'EUA', 'Japão']\n",
        "width = 0.35\n",
        "ax.bar(paises, pais_total, width, color=\"#ff2929\")\n",
        "ax.set_ylabel('Total de ataques')\n",
        "plt.grid(True)\n",
        "plt.show()\n",
        " \n",
        "#Fonte\n",
        "print(\"\\nFONTE: \\n<The Rising Tide of Credential Phishing: 2.4 Million Attacks Blocked by Trend Micro Cloud App Security in 2019 1H. \\n[S. l.]: Trend Micro, 2019. Disponível em: \\nhttps://www.trendmicro.com/vinfo/us/security/news/cybercrime-and-digital-threats/the-rising-tide-of-credential-phishing. \\nAcesso em: 19 jun. 2020.>\")"
      ],
      "execution_count": 1337,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "FONTE: \n",
            "<The Rising Tide of Credential Phishing: 2.4 Million Attacks Blocked by Trend Micro Cloud App Security in 2019 1H. \n",
            "[S. l.]: Trend Micro, 2019. Disponível em: \n",
            "https://www.trendmicro.com/vinfo/us/security/news/cybercrime-and-digital-threats/the-rising-tide-of-credential-phishing. \n",
            "Acesso em: 19 jun. 2020.>\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DovXU1B987FK",
        "colab_type": "text"
      },
      "source": [
        "# **Redes Wi-Fi públicas**\n",
        "\n",
        "Atualmente, ataques cibernéticos não são mais exclusivamente realizados a grande distâncias, mas sim em locais públicos e movimentados, através da rede Wi-Fi local do ambiente. Um bom exemplo desse vetor de ataque é a primeira cena do primeiro episódio da série MR. ROBOT, [em que o protagonista (Elliot) intercepta o tráfego de uma rede e denuncia o dono de um site de pornografia infantil](https://youtu.be/7e0dexhYWls).\n",
        "\n",
        "Ataques em redes Wi-Fi públicas possuem várias vertentes, que variam da criação de redes Wi-Fi falsas, até interceptação de dados de usuários conectados a esta rede. \n",
        "\n",
        "* ##   Man-In-The-Middle: \n",
        "O tipo de ataque em rede mais famoso é o Man-In-The-Middle (MITM), em que o atacante \"envenena\" a rede e a partir disso consegue obter toda a informação que está sendo recebida e enviada pelas vítimas, como demonstrado na figura a seguir: \n",
        "<img src=\"https://www.geekzilla.com.br/wp-content/uploads/2014/10/man-in-the-middle.png\" width=\"400\"/>\n",
        "\n",
        "* ##   Fake AP's:\n",
        "Este vetor de ataque ocorre de maneira semelhante ao MITM, porém ao invés do atacante apenas se infiltrar em uma rede e \"escutar\" o trafego da mesma, ele cria uma rede wireless identica a ela e compromete o acesso dos usuários a rede original, dando a ele o acesso total às informações que trafegam na rede falsa.\n",
        "\n",
        "* ##   Páginas Fake:\n",
        "Esta forma de ataque não se limita apenas a redes locais, porém é muito mais fácil para o atacante criar uma página fake em uma Wi-Fi local. Seu objetivo é interceptar conexões a determinado site e fazer com que a vítima navegue na página e forneça informações pessoais para o atacante imaginando está no website original.\n",
        "\n",
        "Atualmente não existem muitas informações prejuízos ou danos causado por estes três ataques internos em redes Wi-Fi, por isso são tão perigosos. As melhores formas de evitar ser vítima de qualquer um deles são:\n",
        "\n",
        "*   Evitar ao máximo se conectar a redes Wi-Fi abertas/públicas;\n",
        "*   Sempre utilizar senhas para proteger sua rede wireless residencial;\n",
        "*   Evitar entrar, navegar e logar em sites que não possuam certificado SSL (cadeado verde fechado ao lado da URL de um site);\n",
        "*   Evitar fazer compras online através de uma rede Wi-Fi e sempre optar por utilizar as redes móveis de telefonia (LTE/4G/3G);\n",
        "*   Sempre desconfiar de comportamentos estranhos de todo e qualquer site;\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "J4vb9RRIcI22",
        "colab_type": "text"
      },
      "source": [
        "# **Conclusão**\n",
        "\n",
        "A Internet, na atualidade, possui diversos riscos, porém os maiores são os ataques de engenharia social, sejam os direcionados para infectar dispositivos ou para roubar dados, pois é quase impossível se defender de um ataque deste tipo, que é elaborado para comprometer a maior de todas as falhas de segurança: a mente humana.\n",
        "\n",
        "Realizando a média do total de cada uma das três categorias de ataques analisadas neste projeto, Malwares via spam, Roubo de dados via phishing e Redes Wi-Fi públicas, podemos comparar qual é o tipo de ataque mais utilizado atualmente, conforme o gráfico abaixo:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aJRFcWdn_kPh",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 382
        },
        "outputId": "699785cf-3843-41ad-b796-06636ecba005"
      },
      "source": [
        "#Importando bibliotecas utilizadas\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "#Importando dados\n",
        "sizes = [4668987, 6732, 775678]\n",
        "\n",
        "#Plotando gráfico\n",
        "fig1, ax1 = plt.subplots()\n",
        "plt.style.use('dark_background')\n",
        "plt.style.context('dark_background')\n",
        "cores = [\"#f00000\",\"#ff2929\",\"#ff5959\"]\n",
        "\n",
        "#Configurações do gráfico\n",
        "ax1.set_title('Ataques de engenharia social mais utilizados diariamente (estimativa)\\n')\n",
        "labels = 'Malwares via spam', 'Roubo de dados via phishing', 'Redes Wi-Fi públicas'\n",
        "explode = (0, 0, 0)\n",
        "ax1.pie(sizes, explode=explode, autopct='%1.1f%%', labels=labels, shadow=True, startangle=45, colors=cores)\n",
        "ax1.axis('equal')\n",
        "plt.legend(labels, bbox_to_anchor=(1, 0),loc='upper right')\n",
        "plt.axis('equal')\n",
        "plt.tight_layout()\n",
        "plt.show()\n",
        "\n",
        "#Fonte\n",
        "print(\"\\nFONTE: \\n<ESTATÍSTICAS | Mapa em tempo real de ameaças cibernéticas da Kaspersky. \\n[S. l.]: Kaspersky Lab, 2020. Disponível em: https://cybermap.kaspersky.com/pt/stats/#country=215&type=null&period=m. \\nAcesso em: 18 jun. 2020.>\")"
      ],
      "execution_count": 1337,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "FONTE: \n",
            "<ESTATÍSTICAS | Mapa em tempo real de ameaças cibernéticas da Kaspersky. \n",
            "[S. l.]: Kaspersky Lab, 2020. Disponível em: https://cybermap.kaspersky.com/pt/stats/#country=215&type=null&period=m. \n",
            "Acesso em: 18 jun. 2020.>\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}