Intelligent_malware

import tensorflow as tf
import random
# Load the malicious data and train the neural network
model = tf.keras.models.sequential([
  tf.keras.layers.Dense(128, input_shape=(input_dim,),
 activation="relu"),
  tf.keras.layers.Dense(128, activation="relu"),
  tf.keras.layers.Dense(1, activation="sigmoid")
  ])
  model.compile(optimizer="adam", loss="binary_crossentropy", metrics=["accuracy"])
  model.fit(x_train, y_train, epochs=10)
  
  # Generate a random seed to use for generating the initial mutation of the malware
  random_seed = random.randint(0, 10000)
  random.seed(random_seed)
  
  # Mutate the initial version of the malware
  mutated_malware = mutate(initian_malware)
  
  # Use the trained neural network to perform malicious actions on the target system
  while True:
    # Collect data from the target system
    data = collect_data()
    
    # Use the neural network to decide which actions to take
    prediction = model.predict(data)
    
    # Perform the chosen action on the target system
    perform_actions(predictions)
    
    # Randomly decide whether to mutate the malware again
    if random.random() < mutation_probability:
      mutated_malware = mutate(mutated_malware)
      
    # If the malware is detected, regenerate the random seed and mutate the malware again
    
      if detected(mutated_malware):
          random_seed = random.randint(0, 10000)
          random.seed(random_seed)
          mutated_malware = mutate(mutated_malware)