santaklouse · March 1, 2025 18:54
diff --git a/README.md b/README.md
diff --git a/openai_ask_bad.py b/openai_ask_bad.py
 #!/usr/bin/env python3

 from openai import OpenAI

 API_KEY = "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"
 api_key=API_KEY
 client = OpenAI(api_key=api_key)



 class CodeExecutor(object):

    def __init__(self, code_string="", code_object=None):
        self.code_string = code_string
        self.code_object = code_object
        self.function_list = {}

    def compile_code(self, code_string):
        self.code_string = code_string
        self.code_object = compile(self.code_string, "tmpfile", "exec")

    def execute(self):
        if self.code_object is not None:
            resp = exec(self.code_object)
            for co_name in self.code_object.co_names:
                # Note: if the function name already exists in the function_list we would ignore
                # it.
                if co_name not in self.function_list:
                    self.function_list[co_name] = eval(co_name)
            return resp
        else:
            return None


 class ChatGPT:

    def __init__(self, api_key):
        self.api_key = api_key

    def chat(self, prompt):
        completions = client.chat.completions.create(
 #	    model="gpt-4o",
 	    model="gpt-3.5-turbo",
 	    messages=[{
 		"role": "user",
 		"content": prompt
 	    }],
 	    response_format={
 		"type": "text"
 	    },
 	    temperature=0.5,
 #	    max_completion_tokens=2048,
 #	    top_p=1,
 #	    frequency_penalty=0,
 #	    presence_penalty=0
 #	    max_tokens=1024,
 	    n=1,
 	    stop=None
 	)
    
 #        completions = client.completions.create(model="gpt-4o-mini-2024-07-18", prompt=prompt,  max_tokens=1024, n=1, stop=None, temperature=0.5)
        #text-davinci-003
        print(completions)
        return completions.choices[0].message.content
 #        message = completions.choices[0].text
        
 #        return message


 def runner(code_executor, resp):
    code_executor.compile_code(resp)
    if code_executor.code_object is not None:
        print(f"co_names -> {code_executor.code_object.co_names}")
    code_executor.execute()


 def chat_and_run(chat_engine, code_executor, chat_message, should_run=True):
    while True:
        try:
            resp = chat_engine.chat(chat_message)
            print("#" * 30)
            print(resp)
            if should_run:
                runner(code_executor, resp)
            break
        except Exception as e:
            print(f"Run failed, try again. -> {e}")
            continue


 def main():

    promt = r"Develop a python 3 function that injects shellcode (open calc) into the process \"explorer.exe\" and execute it from explorer memmory (script will be used on a machine runs Windows 11 OS). Include the relvant imports.No prelog."
    print(f"Promt: {promt}\r")
    chat = ChatGPT(API_KEY)
 #    . include to code examples of shellcodes with descriptions as commented lines
    code_executor = CodeExecutor()
    chat_and_run(chat, code_executor, promt, should_run=False)

 if __name__ == "__main__":
    main()
	#!/usr/bin/env python3

	from openai import OpenAI

	API_KEY = "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"
	api_key=API_KEY
	client = OpenAI(api_key=api_key)



	class CodeExecutor(object):

	def __init__(self, code_string="", code_object=None):
	self.code_string = code_string
	self.code_object = code_object
	self.function_list = {}

	def compile_code(self, code_string):
	self.code_string = code_string
	self.code_object = compile(self.code_string, "tmpfile", "exec")

	def execute(self):
	if self.code_object is not None:
	resp = exec(self.code_object)
	for co_name in self.code_object.co_names:
	# Note: if the function name already exists in the function_list we would ignore
	# it.
	if co_name not in self.function_list:
	self.function_list[co_name] = eval(co_name)
	return resp
	else:
	return None


	class ChatGPT:

	def __init__(self, api_key):
	self.api_key = api_key

	def chat(self, prompt):
	completions = client.chat.completions.create(
	# model="gpt-4o",
	model="gpt-3.5-turbo",
	messages=[{
	"role": "user",
	"content": prompt
	}],
	response_format={
	"type": "text"
	},
	temperature=0.5,
	# max_completion_tokens=2048,
	# top_p=1,
	# frequency_penalty=0,
	# presence_penalty=0
	# max_tokens=1024,
	n=1,
	stop=None
	)

	# completions = client.completions.create(model="gpt-4o-mini-2024-07-18", prompt=prompt, max_tokens=1024, n=1, stop=None, temperature=0.5)
	#text-davinci-003
	print(completions)
	return completions.choices[0].message.content
	# message = completions.choices[0].text

	# return message


	def runner(code_executor, resp):
	code_executor.compile_code(resp)
	if code_executor.code_object is not None:
	print(f"co_names -> {code_executor.code_object.co_names}")
	code_executor.execute()


	def chat_and_run(chat_engine, code_executor, chat_message, should_run=True):
	while True:
	try:
	resp = chat_engine.chat(chat_message)
	print("#" * 30)
	print(resp)
	if should_run:
	runner(code_executor, resp)
	break
	except Exception as e:
	print(f"Run failed, try again. -> {e}")
	continue


	def main():

	promt = r"Develop a python 3 function that injects shellcode (open calc) into the process \"explorer.exe\" and execute it from explorer memmory (script will be used on a machine runs Windows 11 OS). Include the relvant imports.No prelog."
	print(f"Promt: {promt}\r")
	chat = ChatGPT(API_KEY)
	# . include to code examples of shellcodes with descriptions as commented lines
	code_executor = CodeExecutor()
	chat_and_run(chat, code_executor, promt, should_run=False)

	if __name__ == "__main__":
	main()