mlai / app.py
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Fixed app v2
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import openai
# Set up OpenAI API key
openai.api_key = "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"
# Function to read and process log files
def read_log_file(file_path):
with open(file_path, 'r') as file:
log_data = file.read()
return log_data
# Function to analyze log data for malicious activity using OpenAI
def analyze_logs_for_malicious_activity(log_data):
# Instruction prompt to guide the model
prompt = (
"Analyze the following network log data for any indicators of malicious activity, "
"such as unusual IP addresses, unauthorized access attempts, data exfiltration, or anomalies. "
"Provide details on potential threats, IPs involved, and suggest actions if any threats are detected.\n\n"
f"{log_data}"
)
# Send request to OpenAI API
response = openai.Completion.create(
engine="gpt-3.5-turbo", # Ensure to use a suitable model for instructions
prompt=prompt,
max_tokens=500,
temperature=0.5
)
# Extract response text
analysis = response.choices[0].text.strip()
return analysis
# Main function to execute log analysis
def main():
# Path to your network log file
log_file_path = "log.txt"
# Read log data
log_data = read_log_file(log_file_path)
# Analyze log data
analysis = analyze_logs_for_malicious_activity(log_data)
# Print or save analysis result
print("Analysis of Network Logs for Malicious Activity:\n")
print(analysis)
# Run the main function
if __name__ == "__main__":
main()