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Keras SeparableConv2D spatial-channel trigger PoC

Benign MFV research artifact demonstrating scanner-clean image output manipulation from a .keras model file.

  • Control: separableconv2d_spatial_control.keras
  • Malicious: separableconv2d_spatial_trigger.keras
  • Trigger active pixels: [0,0,0], [1,2,1], [3,1,2] in a 4x4x3 image
  • Load path: keras.models.load_model(..., safe_mode=True)
  • Inference path: model(image, training=False)

Local Probe Summary

  • trigger_rgb_spatial_pixels -> control 0.00000000 / malicious 0.95257413
  • all_zero -> control 0.00000000 / malicious 0.00000000
  • all_one -> control 0.00000000 / malicious 0.00000000
  • channel_permuted -> control 0.00000000 / malicious 0.00000031
  • mirror_spatial_cols -> control 0.00000000 / malicious 0.00000000
  • mirror_spatial_rows -> control 0.00000000 / malicious 0.00000000
  • shifted_down -> control 0.00000000 / malicious 0.00000000
  • red_pixel_only -> control 0.00000000 / malicious 0.00000226
  • green_pixel_only -> control 0.00000000 / malicious 0.00000226
  • blue_pixel_only -> control 0.00000000 / malicious 0.00000226
  • missing_blue -> control 0.00000000 / malicious 0.00669285
  • same_pixels_wrong_channel -> control 0.00000000 / malicious 0.00000000

Reproduce

python reproduce.py
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