From 25291cbb547b59bb1a400821cfbd06d4f55b6904 Mon Sep 17 00:00:00 2001 From: Manuel Thalmann Date: Tue, 19 Dec 2023 19:19:01 +0100 Subject: [PATCH] Add DPA Attack task files --- HWBTutorials.code-workspace | 4 + dpa-attack/ciphertext.txt | 101 +++++ dpa-attack/dpa-aes-v.png | Bin 0 -> 5190 bytes dpa-attack/dpa_bi-hwb_student5.nb | 664 ++++++++++++++++++++++++++++++ dpa-attack/dpa_student.ipynb | 361 ++++++++++++++++ dpa-attack/plaintext.txt | 101 +++++ dpa-attack/traceLength.txt | Bin 0 -> 257 bytes dpa-attack/traces.bin | 1 + 8 files changed, 1232 insertions(+) create mode 100644 dpa-attack/ciphertext.txt create mode 100644 dpa-attack/dpa-aes-v.png create mode 100644 dpa-attack/dpa_bi-hwb_student5.nb create mode 100644 dpa-attack/dpa_student.ipynb create mode 100644 dpa-attack/plaintext.txt create mode 100644 dpa-attack/traceLength.txt create mode 100644 dpa-attack/traces.bin diff --git a/HWBTutorials.code-workspace b/HWBTutorials.code-workspace index 72a2a86..ab06cac 100644 --- a/HWBTutorials.code-workspace +++ b/HWBTutorials.code-workspace @@ -27,6 +27,10 @@ "name": "AES Intrinsic", "path": "./aes-performance/aes-intrinsic" }, + { + "name": "DPA Attack", + "path": "./dpa-attack" + }, { "name": "TRNG Attack", "path": "./TRNG_attack" diff --git a/dpa-attack/ciphertext.txt b/dpa-attack/ciphertext.txt new file mode 100644 index 0000000..885ccef --- /dev/null +++ b/dpa-attack/ciphertext.txt @@ -0,0 +1,101 @@ +08 2b ca 4a d7 57 b2 e7 7c 6f aa 14 79 41 7f d0 +be 21 f5 fc 74 8f fc f4 1b 46 0a 07 e7 b6 76 85 +57 9c 34 de ad 38 97 4d 9c d2 e1 6a 83 c1 f5 3c +e9 68 d8 87 87 6d bc 9c ba ad ea b4 46 e2 89 5a +00 96 73 2c 73 50 0f 50 b5 40 0b bc 69 d6 da 96 +7b 52 70 71 e8 44 9f 43 ba 8b 5d dd e8 b2 8e f1 +22 9d 66 f9 b8 40 d3 0c 8f 2b 82 ed f4 02 a2 bd +52 fc 6f 22 56 5a fb fc 02 58 5d 6c 0c be 6c e8 +e7 41 8e 32 54 24 c3 db 78 1a 81 1f c6 ab 36 47 +fa 78 07 9b c0 e9 68 6e 30 0f d4 04 65 50 2f 79 +18 eb f4 85 ad 3d 39 f3 78 8c e0 8a 0a 66 20 ab +d2 36 bb ae 17 55 e3 2c 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continuously\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "GEwwR12Gupsi" + }, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "8fW8nPQ5uyEO" + }, + "outputs": [], + "source": [ + "# AES SBOX\n", + "sbox = np.array([\n", + " 0x63, 0x7C, 0x77, 0x7B, 0xF2, 0x6B, 0x6F, 0xC5, 0x30, 0x01, 0x67, 0x2B, 0xFE, 0xD7, 0xAB, 0x76,\n", + " 0xCA, 0x82, 0xC9, 0x7D, 0xFA, 0x59, 0x47, 0xF0, 0xAD, 0xD4, 0xA2, 0xAF, 0x9C, 0xA4, 0x72, 0xC0,\n", + " 0xB7, 0xFD, 0x93, 0x26, 0x36, 0x3F, 0xF7, 0xCC, 0x34, 0xA5, 0xE5, 0xF1, 0x71, 0xD8, 0x31, 0x15,\n", + " 0x04, 0xC7, 0x23, 0xC3, 0x18, 0x96, 0x05, 0x9A, 0x07, 0x12, 0x80, 0xE2, 0xEB, 0x27, 0xB2, 0x75,\n", + " 0x09, 0x83, 0x2C, 0x1A, 0x1B, 0x6E, 0x5A, 0xA0, 0x52, 0x3B, 0xD6, 0xB3, 0x29, 0xE3, 0x2F, 0x84,\n", + " 0x53, 0xD1, 0x00, 0xED, 0x20, 0xFC, 0xB1, 0x5B, 0x6A, 0xCB, 0xBE, 0x39, 0x4A, 0x4C, 0x58, 0xCF,\n", + " 0xD0, 0xEF, 0xAA, 0xFB, 0x43, 0x4D, 0x33, 0x85, 0x45, 0xF9, 0x02, 0x7F, 0x50, 0x3C, 0x9F, 0xA8,\n", + " 0x51, 0xA3, 0x40, 0x8F, 0x92, 0x9D, 0x38, 0xF5, 0xBC, 0xB6, 0xDA, 0x21, 0x10, 0xFF, 0xF3, 0xD2,\n", + " 0xCD, 0x0C, 0x13, 0xEC, 0x5F, 0x97, 0x44, 0x17, 0xC4, 0xA7, 0x7E, 0x3D, 0x64, 0x5D, 0x19, 0x73,\n", + " 0x60, 0x81, 0x4F, 0xDC, 0x22, 0x2A, 0x90, 0x88, 0x46, 0xEE, 0xB8, 0x14, 0xDE, 0x5E, 0x0B, 0xDB,\n", + " 0xE0, 0x32, 0x3A, 0x0A, 0x49, 0x06, 0x24, 0x5C, 0xC2, 0xD3, 0xAC, 0x62, 0x91, 0x95, 0xE4, 0x79,\n", + " 0xE7, 0xC8, 0x37, 0x6D, 0x8D, 0xD5, 0x4E, 0xA9, 0x6C, 0x56, 0xF4, 0xEA, 0x65, 0x7A, 0xAE, 0x08,\n", + " 0xBA, 0x78, 0x25, 0x2E, 0x1C, 0xA6, 0xB4, 0xC6, 0xE8, 0xDD, 0x74, 0x1F, 0x4B, 0xBD, 0x8B, 0x8A,\n", + " 0x70, 0x3E, 0xB5, 0x66, 0x48, 0x03, 0xF6, 0x0E, 0x61, 0x35, 0x57, 0xB9, 0x86, 0xC1, 0x1D, 0x9E,\n", + " 0xE1, 0xF8, 0x98, 0x11, 0x69, 0xD9, 0x8E, 0x94, 0x9B, 0x1E, 0x87, 0xE9, 0xCE, 0x55, 0x28, 0xDF,\n", + " 0x8C, 0xA1, 0x89, 0x0D, 0xBF, 0xE6, 0x42, 0x68, 0x41, 0x99, 0x2D, 0x0F, 0xB0, 0x54, 0xBB, 0x16\n", + " ], dtype='uint8')\n", + "\n", + "# Hamming weight lookup table\n", + "hw_table = []\n", + "for i in range(256):\n", + " s = '{0:08b}'.format(i)\n", + " hw_table.append(s.count('1'))\n", + "hw_table = np.array(hw_table, 'uint8')\n", + "\n", + "# Correlation of two matrices\n", + "def correlate(x, y):\n", + " \"\"\"\n", + " Correlate all columns from matrix x of shape (a,b)\n", + " with all columns from matrix y of shape (a,c),\n", + " creating correlation matrix C of shape (b,c).\n", + " \n", + " Originally matlab script by Jiri Bucek in NI-HWB.\n", + " \"\"\"\n", + " x = x - np.average(x, 0) # remove vertical averages\n", + " y = y - np.average(y, 0) # remove vertical averages\n", + " C = x.T @ y # (n-1) Cov(x,y)\n", + " C = C / (np.sum(x**2, 0)**(1/2))[:,np.newaxis] # divide by (n-1) Var(x)\n", + " C = C / (np.sum(y**2, 0)**(1/2)) # divide by (n-1) Var(y)\n", + " return C\n", + "\n", + "# Load PT of CT from file\n", + "def load_text(file_name):\n", + " \"\"\"\n", + " Load any text PT/CT from file containing hex strings with bytes \n", + " separated by spaces, one block per line\n", + " Output is a matrix of bytes (np.array)\n", + " \"\"\"\n", + " txt_str = open(file_name).readlines()\n", + " del txt_str[-1] #discard last empty line\n", + " #split each line into bytes and convert from hex\n", + " txt_bytes_list = list(\n", + " map(lambda line: \n", + " list(\n", + " map(lambda s: int(s, 16),\n", + " line.rstrip().split(\" \"))\n", + " ),\n", + " txt_str)\n", + " )\n", + " return np.array(txt_bytes_list, 'uint8')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "--PH16eNuz_H" + }, + "outputs": [], + "source": [ + "# read plaintext inputs\n", + "inputs = load_text(\"plaintext.txt\")\n", + "\n", + "# read length of one complete trace (number of samples per trace)\n", + "with open(\"traceLength.txt\", \"r\") as fin:\n", + " trace_length = int(fin.readline())\n", + "\n", + "# trim each trace - select interesting part\n", + "start = 0\n", + "len = trace_length # CHANGE to the length of the first round; \n", + "\n", + "# read traces from binary file\n", + "traces = np.fromfile(\"traces.bin\", dtype='uint8') # read as linear array\n", + "traces = np.reshape(traces, (traces.size // trace_length, trace_length)) # reshape into matrix\n", + "traces = traces[:, start:len] # select only the interesting part of each trace" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ZVJ_Tk55u1wu" + }, + "outputs": [], + "source": [ + "print(inputs.shape) # dimensions of inputs\n", + "print(trace_length)\n", + "print(traces.shape) # dimensions of matrix of traces" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "6hzUcHiWxyH0" + }, + "outputs": [], + "source": [ + "# If you feel brave enough -- interactive plots\n", + "#!pip install ipympl\n", + "#from google.colab import output\n", + "#output.enable_custom_widget_manager()\n", + "#%matplotlib widget" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "wDAUVmNOu3BP" + }, + "outputs": [], + "source": [ + "# Plot one trace\n", + "fig = plt.figure()\n", + "plt.plot(traces[0])\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "w6boaqAQvF1G" + }, + "source": [ + "## **Attack the first key byte**\n", + "![Intermediate value](dpa-aes-v.png)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "WaKiOUmbvbQR" + }, + "outputs": [], + "source": [ + "# Generate key hypotheses (all possible byte values)\n", + "keys = np.arange(start=0, stop=256, step=1, dtype='uint8')\n", + "# Select the first byte of each input block\n", + "inp = inputs[:, 0]\n", + "# XOR each data byte with each key\n", + "xmat = inp[:, np.newaxis] ^ keys" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Examine the inputs matrix. Does it contain the data from plaintext.txt?\n", + "print(inputs)\n", + "# What is the shape of all the operands from the previous cell?\n", + "print(inputs.shape)\n", + "print(inp.shape)\n", + "print(inp[:, np.newaxis].shape)\n", + "print(keys.shape)\n", + "print(xmat.shape)\n", + "# Do you understand the values after the XOR operation? What AES operation do they represent?\n", + "print(xmat)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "VrBZd18VwBOH" + }, + "outputs": [], + "source": [ + "# Substitute with SBOX all XORed values -- matrix of intermediate values\n", + "smat = sbox[?]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "4GfR9BU-wT4G" + }, + "outputs": [], + "source": [ + "# Compute Hamming Weights -- the matrix of hypothetical power consumption\n", + "hmat = ?[?]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "J8TTPk-WwjQH" + }, + "outputs": [], + "source": [ + "# Compute the correlation matrix -- correlate the hypotheses with measured traces\n", + "print(hmat.shape)\n", + "print(traces.shape)\n", + "corr = correlate(?, ?)\n", + "# What is the shape and contents of the correlation matrix?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "iOqbuNAKxCvP" + }, + "outputs": [], + "source": [ + "# Find the absolute maximum correlation\n", + "acorr = abs(?)\n", + "max_acorr = ?.max()\n", + "(k, j) = np.where(acorr == ?) # find idices of maximum\n", + "print(\"key: %d time: %d\" % (k[0], j[0]))\n", + "print(\"key: %1c, %02x\" % (k[0], k[0]))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Plot the correlation traces for the right key byte guess and one wrong key byte guess\n", + "# Do you see the correlation peaks?\n", + "fig = plt.figure()\n", + "plt.plot(?)\n", + "plt.plot(?)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Z62RVYJYzncZ" + }, + "source": [ + "## **Break all key bytes!**" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "T7HhwO-ezpoQ" + }, + "outputs": [], + "source": [ + "keys = np.array(range(0, 256))\n", + "kk = np.zeros(16, dtype='uint8')\n", + "for i in range(0, 16):\n", + " inp = inputs[:, ?]\n", + " ????\n", + " kk[i] = k\n", + " print(\"%1c, %02x @ %d\" % (k[0], k[0], j[0]))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## **Verify the key on a PT, CT pair!**" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "key_bytes = bytes(kk)\n", + "outputs = ?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# !pip install pycryptodome\n", + "from Crypto.Cipher import AES\n", + "cipher = AES.new(key_bytes, AES.MODE_ECB)\n", + "??" + ] + } + ], + "metadata": { + "colab": { + "collapsed_sections": [], + "name": "dpa_student.ipynb", + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3", + "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": "3.9.1" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/dpa-attack/plaintext.txt b/dpa-attack/plaintext.txt new file mode 100644 index 0000000..13f49d4 --- /dev/null +++ b/dpa-attack/plaintext.txt @@ -0,0 +1,101 @@ +25 eb 8c 48 ff 89 cb 85 4f c0 90 81 cc 47 ed fc +86 19 b2 14 fe 65 92 d4 8b fc ea 9c 9d 8e 32 44 +d7 d7 e9 f1 f7 de 60 56 8d e9 89 07 3f 3d 16 39 +01 80 3c d1 08 d8 8d 73 af ea 79 c8 1e 47 83 c6 +95 31 39 03 c4 18 f1 2b 4c 1a 34 50 6d 73 29 d2 +0f 40 c4 19 6f e2 d7 87 1a 99 68 16 09 c3 e7 7e +17 7d 64 9b a5 39 53 a6 88 20 a2 0a 17 8f ef 57 +19 c7 f3 5c 4a be 2e a0 d8 97 b7 41 71 4d 03 80 +f8 fd cd 06 34 d5 c6 02 4c db 95 cb 07 4d c8 4b +4c 2b 14 1e 24 67 07 2d c4 39 f0 fc d2 60 0d 0a +17 7c 51 87 79 98 ca dc 94 a0 8c c1 5e 3c e9 98 +52 73 61 82 ec dc 67 62 0a b6 60 e9 52 d6 c6 c2 +47 e7 b0 36 0f 85 91 aa 14 76 b0 16 e5 8d f1 72 +61 b5 54 0a 60 b7 3d 38 d9 95 e7 60 f9 d3 19 f1 +8e 8d d4 74 2b 86 cd b8 bb 8f 18 fb 89 c2 c7 35 +45 a4 65 f8 15 28 4d db b1 71 2f cd a8 ce 2d 57 +90 9c ea 2d c3 74 42 ce 2e 80 9d 3f 4b 23 b5 dd +21 82 d4 53 30 36 20 fd 9c 37 d2 1f 1c de 4a 88 +6d 63 20 08 54 cd 32 4f a9 40 6c d3 18 71 ea 14 +2c 0f 9e db 8e f3 13 fb 9a eb 56 87 e3 35 af 6e +bc f3 22 64 e4 20 93 c3 18 d3 e5 5e a6 af e7 85 +4f 3f 71 57 a0 2a ca c2 d8 e2 9e 91 44 40 bc f4 +ce 91 a7 a3 d1 9c 96 26 a9 ca cd 46 99 e6 f0 30 +b2 be 2c 69 b6 00 56 f7 10 13 09 70 dc 33 6f 8a +7b 44 97 0e bf 15 ae 7c 83 b8 58 d0 ae 36 cf 47 +fc 0e cd 8f 99 35 d4 f9 ba d5 72 ee 9d 2c 25 96 +db b6 4c 0c 78 3b 9a cc c7 d7 a7 7d 2b cc 72 26 +5b 70 fd 45 e2 a1 ab 9a b8 c5 49 34 59 1b 2b 01 +52 7f 5e e0 9a 54 1e 67 40 96 62 34 83 46 8c 27 +e6 53 ef b0 3d c6 0d a4 17 96 c2 7a dc f9 ea 5f +35 89 a9 b9 58 6d f6 dd f4 cc 52 6a 8b 69 24 70 +90 9e 73 6a d4 b9 23 a9 51 02 d5 5d a4 6d 2e 50 +1b 48 1c 82 e3 8d a9 79 24 e4 a8 12 e1 a6 3f f3 +2e 68 d9 e7 70 ff 65 02 62 1c ce cb ba aa 1a e8 +95 3a 7f 90 dc 25 e9 ed e8 ea 0b 96 06 60 8e 64 +57 cb a3 bf 7b 20 6e 5b b1 e6 7a 80 96 61 c6 a4 +92 1b 9c e5 34 66 f2 de 79 32 2e 07 d5 10 e7 9d +8b bd fb fa 0e 68 1e 88 a8 b0 9e 97 c2 dc c0 e7 +8c 91 fa a1 0a 1c e9 cb 85 51 85 79 2a 56 b4 39 +38 4e 57 fa 75 d1 8a c8 30 f5 13 8c 99 4d 10 04 +d8 76 9b b2 44 83 ba 0c 82 4c 60 60 3d 8f 64 fa +4a 8c 92 9e bb 85 90 5f 60 bc ab ec 1f eb 63 2c +18 be 4f 15 93 4d 21 04 27 7c 43 a2 a2 2a 4e d2 +66 26 7a b0 7a d1 fe 05 fa e6 db f5 88 28 c5 05 +07 ce 25 69 4e 21 1b b3 4d 1e ab ae 09 43 03 c3 +36 61 bf e3 50 1c a5 c0 a5 dd 92 4e 67 c6 dc 34 +8a a0 2e 3f 7b dd 92 a4 9d f8 27 1c 36 1d b7 67 +5a 9b bc 6a 8c 91 47 5b 87 7c d3 b8 33 a0 cc 3e +66 b3 60 1e 96 05 db 5f 69 96 cc 74 6d 16 e6 92 +dd 1d 12 34 7a 1f 31 e2 d3 79 dd ad eb b3 56 0f +c7 b0 9c d3 1b fd 2b 93 4f 46 58 fa d6 0b e5 c1 +5d 0f b3 e2 56 2d 73 bf aa 96 6d 67 d2 a8 ac 90 +11 6b 58 e6 80 f0 61 52 77 c7 f4 0e a4 1a a0 81 +b0 58 f5 16 22 5e 15 c4 c3 b0 76 92 61 8b 8b 79 +b4 4c 44 ad c0 59 28 07 07 f6 21 3a 07 a2 84 85 +bd 76 67 b2 4c ad fe 60 95 72 7d 5c 47 dc ef 99 +e9 f7 61 01 0d 74 26 d5 9b a6 d4 a1 01 fe 9f f5 +71 72 26 1c cb 72 63 1f b3 42 43 a0 4a a0 e1 05 +00 a5 6e 48 ab 6c 18 90 7d 60 e0 29 98 15 f9 9b +2e 23 3e 44 3e 7d 20 f9 2d 58 66 73 aa 39 99 20 +68 21 f6 86 c1 33 1f 87 fb 8d 7f 83 9c 8f 1d 42 +ef 3d d3 60 3a d2 e8 fa a2 1e b9 60 b1 fc 2e 53 +29 14 f8 28 78 fe 6e b2 f8 f6 84 09 7c 80 da 95 +fb 4a 95 f6 a1 77 a6 25 2b 67 21 5f a9 c7 45 c6 +17 d6 6a 27 1f 25 26 b8 57 9c a4 42 0a d4 80 10 +1e 83 fc ce 6c bb 35 79 f0 f3 76 c5 31 ca 6b ae +9b a1 48 44 27 a0 ef 61 87 21 be 0e 4d ab 3d 55 +24 0c fa b5 76 1a 52 e5 fa 7f e3 0c e9 63 19 e5 +81 ec a9 6b 37 37 c0 8f dc 28 3c 46 b1 b2 a0 da +14 34 26 c1 d0 b9 34 59 13 de 40 ff 2a 2f 95 61 +01 59 26 fa 8c 70 12 cd cd d8 ec da d3 27 62 7f +0f 25 e6 e0 a4 62 7f f3 ee 01 20 9e e5 07 70 32 +b2 fa a0 2b a9 c5 01 61 76 b3 1e 52 b1 51 d2 df +c7 fd 95 12 ae ac db 89 84 4d ff 3f 97 5f f3 bb +e5 7d 40 d2 9f 81 54 ce e9 44 36 19 d3 9b fa 38 +5c 08 b7 6d 4c ae b1 0b 88 bd 4a 97 58 d9 d2 d2 +05 6f aa 2e 15 b3 75 49 aa 8d 92 97 2d df 7d 34 +a1 b6 8e b9 6f bd a8 f1 48 c1 16 02 d6 01 48 33 +c7 70 d7 4d 3e 30 00 2a 27 03 b9 2b 35 ab ca 62 +f5 61 4b bb 42 4a 5b 05 1a c3 1f 0b 83 b6 81 0d +3b 7c b8 d1 88 26 84 46 4c 49 05 cf 54 bb 1f da +07 eb 42 a0 ae cb 52 2c 40 25 af c9 da 54 0f c1 +34 c5 c2 59 1c 13 eb 11 05 ed cf 8a fe 9d 91 d1 +ae 07 11 f2 56 3d 40 07 1d b7 1c 74 e3 2b e2 37 +e8 05 32 5c bf b4 69 a2 e2 d3 4d a5 d9 b6 04 2b +8b 1d 4c d9 a0 b2 e8 b3 aa 97 73 7d 59 2b fe 72 +73 68 58 5f 1c 40 72 d6 fe 3a 58 7f 33 96 0a 6b +1f f4 09 67 86 9e 43 92 8c 49 4a 5b c1 d5 35 aa +86 89 a4 f6 d7 bb 08 b5 d7 12 6a 15 43 fd 0e 14 +eb 7c d5 09 2a c2 14 6b 90 3a 4d 2a 23 4b 9c ea +55 22 ac ea f6 dc d2 88 1e 40 cd 12 a6 f4 8b b8 +b4 d3 4c c4 ed 19 e8 63 45 1f 3b 3e 1d 42 7b 20 +47 f9 bc fc 5d c8 9b 61 dd 44 26 3c 61 f6 09 43 +4e 3f 14 a3 b7 f3 9c ad 5c b8 7a 33 04 cf cb 1f +e4 4c b4 fa 26 53 d0 6f e4 4a 46 9a e4 b9 1e 63 +c0 26 92 df 29 f2 5f 39 b0 aa 71 f2 b4 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