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import os |
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os.environ["KERAS_BACKEND"] = "tensorflow" |
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from tensorflow.keras.models import load_model |
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from sentence_transformers import SentenceTransformer |
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from huggingface_hub import hf_hub_download |
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def load_modeler(): |
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local_model_path = hf_hub_download( |
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repo_id="noobpk/web-attack-detection", |
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filename="model.h5" |
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) |
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return load_model(local_model_path) |
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model = load_modeler() |
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def load_encoder(): |
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model_name_or_path = os.environ.get("model_name_or_path", "sentence-transformers/all-MiniLM-L6-v2") |
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return SentenceTransformer(model_name_or_path) |
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encoder = load_encoder() |
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if __name__ == "__main__": |
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payload = input("Enter payload: ") |
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print("Processing...") |
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embeddings = encoder.encode(payload).reshape((1, 384)) |
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prediction = model.predict(embeddings) |
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accuracy = float(prediction[0][0] * 100) |
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print(f"Accuracy: {accuracy}") |
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