Initial commit

services/blinkpdf/solution/lab.py

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+from src.module.decdsa import *
+import random
+import hashlib
+from sage.all import matrix, Integer, Zmod, vector
+from ecdsa import NIST256p
+curve = NIST256p
+order = int(curve.order)
+
+def case1():
+    ecdsa = DECDSA()
+    inc = 0
+    for i in range(100):
+        temp = random.randbytes(10)
+        signature = ecdsa.sign(temp)
+        hasil = ecdsa.verify(temp+b'1', signature)
+        if(not hasil): 
+            inc += 1
+    print("Different message Failed:",inc)
+    # checking true
+    inc = 0
+    for i in range(100):
+        temp = random.randbytes(10)
+        signature = ecdsa.sign(temp)
+        hasil = ecdsa.verify(temp, signature)
+        if(not hasil): 
+            inc += 1
+    print("Same message Failed:",inc)
+
+# def Babai_closest_vector(B, target):
+#     # Babai's Nearest Plane algorithm
+#     M = B.LLL()
+#     G = M.gram_schmidt()[0]
+#     small = target
+#     for _ in range(1):
+#         for i in reversed(range(M.nrows())):
+#             c = ((small * G[i]) / (G[i] * G[i])).round()
+#             small -= M[i] * c
+#     return target - small
+
+def case2():
+    ecdsa = ECDSA()
+    dataset = []
+    inc = 80
+    for i in range(inc):
+        temp = random.randbytes(10)
+        signature = ecdsa.sign(temp)
+        r1, r2, s = ecdsa.bytes_to_sign(signature)
+        message = temp
+        m1, m2 = message[:len(message)//2], message[len(message)//2:]
+        h1 = hashlib.sha256(m1).digest()
+        h2 = hashlib.sha256(m2).digest()
+        z1 = int.from_bytes(h1, byteorder='big') % order
+        z2 = int.from_bytes(h2, byteorder='big') % order
+        dataset.append([temp, z1, z2, r1, r2, s])
+
+    # B = 2**247
+    B = 2**201
+    p = order
+    Zn = Zmod(p)
+
+    m = [[order,0] + [-Integer((pow(dataset[i-1][5], -1, order)*(dataset[i-1][1]+dataset[i-1][2])-pow(dataset[i][5], -1, order)*(dataset[i][1]+dataset[i][2]))%order) for i in range(1, inc)]]
+    m += [[0,Integer(B)/order] + [Integer((pow(dataset[i-1][5], -1, order)*(dataset[i-1][3]+dataset[i-1][4])-pow(dataset[i][5], -1, order)*(dataset[i][3]+dataset[i][4]))%order) for i in range(1, inc)]]
+    inc -= 1
+    m += [[0,0]+[0]*i+[order]+[0]*(inc-i-1) for i in range(inc)]
+
+    Mat = matrix(m)
+    # W = Babai_closest_vector(Mat, Y)
+    # x = W[1] * (p-1) / 2
+    # print(x)
+    for line in Mat.LLL():
+        if(line[0]==order):
+            key = Zn(line[1]*p/B)
+            print(order-key, int(order).bit_length())
+    # is_valid = ecdsa.verify(temp, signature)
+
+if __name__ == "__main__":
+    # case1()
+    case2()
+