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from transformers import pipeline
import openai
# Initialize the exploit detection model
exploit_detector = pipeline("text-classification", model="Canstralian/CySec_Known_Exploit_Analyzer")
# Initialize OpenAI API (or Replit's API)
openai.api_key = "your-openai-api-key" # Replace with your actual API key
def detect_and_remediate(exploit_input):
"""
Detects an exploit in the input and generates remediation code if an exploit is found.
Args:
exploit_input (str): The code or log input that might contain an exploit.
Returns:
str: The remediation code or a message indicating no exploit was detected.
"""
# Step 1: Detect the exploit
exploit_result = exploit_detector(exploit_input)
if exploit_result[0]['label'] == "EXPLOIT_DETECTED":
print("Exploit detected!")
# Step 2: Generate remediation code
remediation_prompt = f"Generate Python code to fix the following exploit: {exploit_input}"
remediation_response = openai.Completion.create(
engine="code-davinci-002", # Or Replit's equivalent code model
prompt=remediation_prompt,
max_tokens=150
)
# Extracting the generated remediation code
remediation_code = remediation_response.choices[0].text.strip()
return remediation_code
else:
return "No exploit detected."
if __name__ == "__main__":
# Example input: a piece of code or log indicating a vulnerability
input_code = "Vulnerable code snippet here"
remediation = detect_and_remediate(input_code)
print("Remediation Code:", remediation)
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