labs/Lab-2/Lab-2-Practical/02_Control_Flow_Functions_Lab.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d9c31a26",
   "metadata": {},
   "source": [
    "# Module 2 — Lab 2: Control Flow and Functions\n",
    "\n",
    "**Topics:** if/elif/else, for, while, break, continue, function\n",
    "\n",
    "\n",
    "> **Instructions:** Run the cells in order. Complete every `TODO`, then run the **Self-check** cell. Do not open the Solution notebook before attempting the tasks yourself.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e060cb80",
   "metadata": {},
   "source": [
    "## Scenario\n",
    "\n",
    "You need to build small rules that classify login alerts and automatically review a list of IP addresses. All activity is simulated with local data; this notebook does not connect to or scan any real system.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d919cf5",
   "metadata": {
    "tags": [
     "exercise"
    ]
   },
   "source": [
    "## 1. Classify failed login attempts\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ef271740",
   "metadata": {
    "tags": [
     "exercise"
    ]
   },
   "outputs": [],
   "source": [
    "failed_attempts = 7\n",
    "\n",
    "# TODO 1: assign severity using the thresholds 10, 5, 1, and 0\n",
    "severity = None\n",
    "\n",
    "print(severity)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92cd839f",
   "metadata": {
    "tags": [
     "exercise"
    ]
   },
   "source": [
    "## 2. Review IP addresses with `for`, `continue`, and `break`\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c1b87cad",
   "metadata": {
    "tags": [
     "exercise"
    ]
   },
   "outputs": [],
   "source": [
    "blocked_ips = {\"10.0.0.5\", \"10.0.0.12\"}\n",
    "targets = [f\"10.0.0.{i}\" for i in range(1, 16)]\n",
    "reviewed = []\n",
    "\n",
    "for ip in targets:\n",
    "    last_octet = int(ip.split(\".\")[-1])\n",
    "\n",
    "    # TODO 2: skip IP addresses whose final octet is odd\n",
    "    pass\n",
    "\n",
    "    # TODO 3: append the IP address to reviewed\n",
    "    pass\n",
    "\n",
    "    # TODO 4: if the IP is in blocked_ips, print an alert and stop the loop\n",
    "    pass\n",
    "\n",
    "print(\"Reviewed:\", reviewed)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2128332a",
   "metadata": {
    "tags": [
     "exercise"
    ]
   },
   "source": [
    "## 3. Limit retry attempts with `while`\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4fb4787e",
   "metadata": {
    "tags": [
     "exercise"
    ]
   },
   "outputs": [],
   "source": [
    "attempt = 0\n",
    "max_attempts = 3\n",
    "service_responded = False\n",
    "\n",
    "# TODO 5: loop while max_attempts has not been reached and the service has not responded.\n",
    "# Simulate the service responding on the second attempt.\n",
    "while False:\n",
    "    pass\n",
    "\n",
    "print(f\"Service responded: {service_responded}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9fc142dd",
   "metadata": {
    "tags": [
     "exercise"
    ]
   },
   "source": [
    "## 4. Package a rule in a function\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "63e40cf6",
   "metadata": {
    "tags": [
     "exercise"
    ]
   },
   "outputs": [],
   "source": [
    "def classify_login_risk(failed_attempts, is_admin=False, is_off_hours=False):\n",
    "    # Return LOW, MEDIUM, HIGH, or CRITICAL for a login event.\n",
    "    # TODO 6: calculate the score and return a label using thresholds 100, 60, and 30\n",
    "    pass\n",
    "\n",
    "\n",
    "print(classify_login_risk(2))\n",
    "print(classify_login_risk(7, is_off_hours=True))\n",
    "print(classify_login_risk(8, is_admin=True))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a10e84bf",
   "metadata": {},
   "source": [
    "## Self-check\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b1d43daf",
   "metadata": {},
   "outputs": [],
   "source": [
    "assert severity == \"HIGH\"\n",
    "assert reviewed == [\"10.0.0.2\", \"10.0.0.4\", \"10.0.0.6\", \"10.0.0.8\", \"10.0.0.10\", \"10.0.0.12\"]\n",
    "assert attempt == 2 and service_responded is True\n",
    "assert classify_login_risk(2) == \"LOW\"\n",
    "assert classify_login_risk(7, is_off_hours=True) == \"HIGH\"\n",
    "assert classify_login_risk(8, is_admin=True) == \"CRITICAL\"\n",
    "print(\"✓ Lab 2 completed\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f5385ff",
   "metadata": {},
   "source": [
    "## Extension challenge\n",
    "\n",
    "Modify the function to add 20 points when `source_ip` belongs to a set of blocked IP addresses. Write at least two `assert` statements for the new rule.\n"
   ]
  }
 ],
 "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": "3.11.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}