feat: analysis

Author: Trup3s

analyze_fuzzing.ipynb

@@ -0,0 +1,19 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4dd067df",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

estk_playground.ipynb

@@ -0,0 +1,172 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ISDR not found on card\n"
+     ]
+    },
+    {
+     "ename": "SystemExit",
+     "evalue": "1",
+     "output_type": "error",
+     "traceback": [
+      "An exception has occurred, use %tb to see the full traceback.\n",
+      "\u001b[0;31mSystemExit\u001b[0m\u001b[0;31m:\u001b[0m 1\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/niklas/Documents/documents/uni/master_thesis/resimulate/.venv/lib/python3.13/site-packages/IPython/core/interactiveshell.py:3587: UserWarning: To exit: use 'exit', 'quit', or Ctrl-D.\n",
+      "  warn(\"To exit: use 'exit', 'quit', or Ctrl-D.\", stacklevel=1)\n"
+     ]
+    }
+   ],
+   "source": [
+    "import logging\n",
+    "import math\n",
+    "import operator\n",
+    "from collections import Counter\n",
+    "from pprint import pprint\n",
+    "\n",
+    "import numpy as np\n",
+    "import scipy.stats as stats\n",
+    "from pySim.euicc import CardApplicationISDR, GetEuiccChallenge\n",
+    "from pySim.transport.pcsc import PcscSimLink\n",
+    "from statsmodels.sandbox.stats.runs import runstest_1samp\n",
+    "from tqdm.notebook import tqdm\n",
+    "\n",
+    "from resimulate.card import Card\n",
+    "from resimulate.util.enums import ISDR_AID\n",
+    "\n",
+    "logger = logging.getLogger()\n",
+    "logger.setLevel(logging.CRITICAL)\n",
+    "\n",
+    "received_challenges: list[str] = []\n",
+    "\n",
+    "with PcscSimLink(apdu_tracer=None) as link:\n",
+    "    card = Card(link)\n",
+    "    initialized_card = card.init_card(target_isd_r=ISDR_AID.DEFAULT)\n",
+    "    isd_r = card.runtime_state.mf.applications.get(ISDR_AID.DEFAULT.value.lower(), None)\n",
+    "\n",
+    "    if not isd_r:\n",
+    "        print(\"ISDR not found on card\")\n",
+    "        raise SystemExit(1)\n",
+    "\n",
+    "    card.runtime_state.lchan[0].select_file(isd_r)\n",
+    "    card.runtime_state.identity[\"EID\"] = CardApplicationISDR.get_eid(\n",
+    "        card.sim_card_commands\n",
+    "    )\n",
+    "    for _ in tqdm(range(50000)):\n",
+    "        challenge = CardApplicationISDR.store_data_tlv(\n",
+    "            card.sim_card_commands, GetEuiccChallenge(), GetEuiccChallenge\n",
+    "        ).to_dict()[\"get_euicc_challenge\"][0][\"euicc_challenge\"]\n",
+    "        received_challenges.append(challenge)\n",
+    "\n",
+    "\n",
+    "def entropy(data):\n",
+    "    \"\"\"Calculate Shannon entropy for byte sequences\"\"\"\n",
+    "    counts = Counter(data)\n",
+    "    total = len(data)\n",
+    "    return -sum((count / total) * math.log2(count / total) for count in counts.values())\n",
+    "\n",
+    "\n",
+    "def test_randomness(byte_strings) -> tuple[np.float64, np.float64, np.float64, float]:\n",
+    "    # Convert hex/base64/raw strings to bytes\n",
+    "    byte_arrays = [\n",
+    "        bytes.fromhex(s)\n",
+    "        if all(c in \"0123456789abcdefABCDEF\" for c in s)\n",
+    "        else s.encode()\n",
+    "        for s in byte_strings\n",
+    "    ]\n",
+    "\n",
+    "    # Flatten to a single byte sequence\n",
+    "    all_bytes = np.concatenate([np.frombuffer(b, dtype=np.uint8) for b in byte_arrays])\n",
+    "\n",
+    "    # Chi-Square Test for Byte Uniformity\n",
+    "    byte_counts = np.bincount(\n",
+    "        all_bytes, minlength=256\n",
+    "    )  # Count occurrences of each byte (0-255)\n",
+    "    expected = np.full_like(byte_counts, np.mean(byte_counts))\n",
+    "    chi2_stat, p_chi2 = stats.chisquare(byte_counts, expected)\n",
+    "\n",
+    "    # Shannon Entropy\n",
+    "    byte_counts = np.bincount(all_bytes, minlength=256)\n",
+    "    probabilities = byte_counts / all_bytes.size\n",
+    "    entropy_value = stats.entropy(probabilities, base=2)  # entropy(all_bytes)\n",
+    "\n",
+    "    # Monobit Test (Balance of 0s and 1s)\n",
+    "    bit_string = \"\".join(format(byte, \"08b\") for byte in all_bytes)\n",
+    "    ones = bit_string.count(\"1\")\n",
+    "    zeros = bit_string.count(\"0\")\n",
+    "    monobit_p = stats.binomtest(ones, len(bit_string), p=0.5)\n",
+    "\n",
+    "    # Runs Test on Byte Sequences\n",
+    "    z_stat, p_runs = runstest_1samp(all_bytes)\n",
+    "\n",
+    "    return (\n",
+    "        round(p_chi2, 6),\n",
+    "        round(entropy_value, 6),\n",
+    "        round(monobit_p.pvalue, 6),\n",
+    "        round(p_runs, 6),\n",
+    "    )\n",
+    "\n",
+    "\n",
+    "def within_margin(value, target, margin, op: operator) -> bool:\n",
+    "    lower_bound = target - margin\n",
+    "    upper_bound = target + margin\n",
+    "    return op(value, lower_bound) or op(value, upper_bound)\n",
+    "\n",
+    "\n",
+    "p_chi2, entropy_value, pvalue, p_runs = test_randomness(received_challenges)\n",
+    "\n",
+    "if within_margin(p_chi2, 0.05, 0.01, operator.lt):\n",
+    "    print(f\"Chi-Square Test: Non-uniform distribution of bytes! ({p_chi2})\")\n",
+    "if entropy_value < 8:\n",
+    "    print(f\"Shannon Entropy: Low randomness! ({entropy_value})\")\n",
+    "if within_margin(pvalue, 0.05, 0.01, operator.lt):\n",
+    "    print(f\"Monobit Test: Bias in bits! ({pvalue})\")\n",
+    "if within_margin(p_runs, 0.05, 0.01, operator.lt):\n",
+    "    print(f\"Runs Test: Sequential patterns! ({p_runs})\")\n",
+    "\n",
+    "pprint(\n",
+    "    {\n",
+    "        \"Chi-Square Test p-value\": str(p_chi2),  # <0.05 means not uniform/random\n",
+    "        \"Shannon Entropy\": str(entropy_value),  # ~8 means high randomness\n",
+    "        \"Monobit Test p-value\": str(pvalue),  # <0.05 means bias in bits\n",
+    "        \"Runs Test p-value\": str(p_runs),  # <0.05 means sequential patterns\n",
+    "    }\n",
+    ")\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "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": "3.13.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}