threat_extraction.py

import json
import openai
import requests
from os import environ as env
from transformers import Tool

class FirewallManager:
    def update_rule(self, ip: str, action: str):
        # This is a placeholder. You would implement this to interact with your actual firewall.
        print(f"Updated firewall rule for IP {ip} with action {action}")

class PacketFilter:
    def drop_packet(self, ip: str):
        # This is a placeholder. You would implement this to interact with your actual packet filter.
        print(f"Dropped packet from IP {ip}")

class ThreatIntelExtractorTool(Tool):
    name = "threat_intel_extractor_tool"
    description = """
    This tool scrapes a hypothetical threat intelligence feed, uses OpenAI API to extract structured information, and takes defensive actions based on the information.
    Input is a URL of threat intel feed. Output is a structured response as a string with threat information.
    """
    inputs = ["text"]
    outputs = ["text"]

    def __init__(self):
        self.openai_api_key = env.get("OPENAI_API_KEY")
        openai.api_key = self.openai_api_key
        self.firewall_manager = FirewallManager
        self.packet_filter = PacketFilter

    def __call__(self, threat_intel_feed_url: str):
        # Scrape threat intelligence feed
        response = requests.get(threat_intel_feed_url)
        threat_info_raw = response.text

        # Send data to OpenAI API for text extraction
        example_json = {
            "Threats": [
                {"Threat": "Threat 1", "IP": "192.0.2.0", "Description": "This is a hypothetical threat."},
                {"Threat": "Threat 2", "IP": "192.0.2.1", "Description": "This is another hypothetical threat."}
            ]
        }
        prompt = f"Extract structured information from the following threat intelligence:\n{threat_info_raw}\nExample of the expected format:\n{json.dumps(example_json, indent=2)}"
        extraction_response = openai.Completion.create(engine="text-davinci-003", prompt=prompt, max_tokens=100)

        # Format extracted information into a structured response
        extracted_info = self.format_extraction(extraction_response.choices[0].text.strip())

        # Take defensive actions based on the extracted information
        self.take_defensive_actions(extracted_info)

        return extracted_info

    def format_extraction(self, extraction: str) -> dict:
        # This method would depend on the format of the extracted information
        # For this example, let's assume the extraction is a list of threats, each one formatted as "Threat: <threat>, IP: <ip>, Description: <description>"
        structured_info = []
        for line in extraction.split('\n'):
            parts = line.split(',')
            structured_info.append({
                'Threat': parts[0].split(':')[1].strip(),
                'IP': parts[1].split(':')[1].strip(),
                'Description': parts[2].split(':')[1].strip(),
            })
        return json.dumps({'Threats': structured_info})

    def take_defensive_actions(self, threat_info: dict):
        for threat in threat_info['Threats']:
            ip = threat['IP']
            # For the purposes of this example, let's assume that we want to block all traffic from the IP and drop any incoming packets.
            self.firewall_manager.update_rule(ip, 'block')
            self.packet_filter.drop_packet(ip)