[Advanced] Don’t Press the Run Button! 🚫 How to Predict the Future of Malware with AI 🔮 (The Flower of Static Analysis, Behavior Prediction)

Jul 19, 2026

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Hello, security analysts who dig deep to the end! 🕵️‍♂️

Until last time, we decrypted obfuscated code and even added neat comments. Now we have a rough idea of what the code means.

At this point, your fingers might be itching.

“Should I just double-click and run it? If I run it in a sandbox, I’ll get the results right away, won’t I?”

But wait a minute! ✋

Malware is more cunning than you think.

Virtual Environment Detection: “Oh? This is a sandbox, isn’t it? I’ll just pretend to be good and stay still.” 😇
Logic Bomb: “It will only detonate on December 25, 2025.” 💣
C2 Server Unreachable: The hacker’s C2 server might already be closed, so nothing might happen even if you run it.

The advanced technique needed in such cases is ‘Predicting Behavior Without Execution (Emulation)’.

It’s like playing Go in your head, using AI as a virtual CPU to simulate the future of the code.

Today, we will conduct an advanced practical exercise where we tell AI, “From now on, you are a computer. Run this code in your head!” 🧠⚡️

1. Why ‘Predict’ in the first place? (Dynamic vs Static)

Dynamic analysis (actual execution) is convenient, but as mentioned above, it’s easy to fall into traps. On the other hand, static analysis (just looking at the code) is safe but makes it difficult to know specific data (e.g., generated filenames, URLs to connect to).

AI-based behavior prediction combines the advantages of both.

It’s a technique that doesn’t execute the code (safe) but obtains the same results as if it were executed (specific information).

2. [Practical Scenario] Predicting DGA (Domain Generation Algorithm) 🎲

Malware, especially botnets, changes connection addresses daily to avoid blocking. This is called a DGA (Domain Generation Algorithm).

Let’s assume we found a date-based URL generation function like the one below in the malware we are analyzing.

📄 [Code] DGA Function for Analysis (Python Pseudo-code)

Python

# Decrypted DGA function
def generate_c2_url(year, month, day):
    base_string = "malware"
    # 1. Add year, month, and day
    seed = year + month + day
    # 2. Complex operation with seed value (simplified here)
    magic_number = (seed * 0x41) % 25
    # 3. Convert to ASCII code to generate character
    suffix_char = chr(97 + magic_number) # 97 is 'a'
    # 4. Combine final domain
    final_domain = f"http://{base_string}-{suffix_char}.com"
    return final_domain

To run this code, you need to install Python and transfer the code. It’s troublesome, right? Let’s ask AI to do it.

3. Making AI a ‘Virtual Interpreter’ 🤖

You shouldn’t just tell AI “interpret this,” but rather “simulate the execution results.”

🗣️ [Prompt] Input Prediction Prompt

[Role] You are a Python Code Interpreter.

[Situation] I want to know what C2 server domain a piece of malware generates on a specific date.

[Request]

1. Step-by-step trace the logic of the generate_c2_url function provided below.

2. When the input is Year=2025, Month=12, Day=25, show the calculation process of how the variables seed, magic_number, and suffix_char change.

3. Output the final_domain string that will be generated.

4. Caution: Since the code cannot be actually executed, you must derive accurate values through logical operations.

[Code]

(Paste the DGA function code above)

4. [Result] AI’s Future Prediction Hits the Mark! 🎯

AI calculates and displays variable values as if it were a computer itself.

🤖 AI Simulation Result

1. Input Value Settings:

– year = 2025

– month = 12

– day = 25

2. Step-by-step Execution Trace:

– Line 4 (Seed Calculation):seed = 2062

– seed = 2025 + 12 + 25

– Line 6 (Magic Number Calculation):2062 * 65 = 134030magic_number = 5

– 134030 % 25 = 5

– magic_number = (2062 * 65) % 25 (0x41 is 65 in decimal)

– Line 8 (Suffix Char Generation):ASCII code 102 is the character ‘f’.

– chr(97 + 5) -> chr(102)

3. Final Result:

– final_domain = ““

🔮 Prediction Conclusion:

On December 25, 2025, this malware will attempt to connect to .

5. Applications of This Technology 🛠️

This ‘virtual execution’ technology is used not only for simple calculations but also in various scenarios.

Decryption Key Prediction: “If the first 4 bytes of the file header are 0xDEADBEEF, what XOR key should be used for decryption?”
Anti-Debugging Evasion: “Assuming the IsDebuggerPresent() function returns True, show where the code flow jumps.”
Ransomware Behavior Confirmation: “After this loop finishes, what will the file extension change to?” (.enc? .lock?)

6. Caution: AI is not a Calculator! ⚠️

This is a really important tip.

LLMs (Large Language Models) are ‘language’ models, not ‘calculators’.

If you ask them to perform complex bitwise operations or large number divisions, they sometimes brazenly give incorrect answers (Hallucination).

Tip 1: If the calculation process is complex, asking AI to “write Python code to calculate it” (using the Code Interpreter feature) is much more accurate.
Tip 2: For important indicators (IoC), you should write a simple script yourself based on the logic predicted by AI and cross-verify it.

🎉 Practical Exercise Complete: “Solving a Problem Without Lifting a Finger” Success!

Today, we found out the hacker’s server address that will be accessed on Christmas 2025 without actually executing the malware or connecting to a dangerous server. This is the AI version of ‘Brain Emulation’ used by experts. 😎

Now you have:

Chunked the code
Cleaned it
Deobfuscated it
Commented it
And predicted the execution results.

The analysis is practically over. What’s left?

Yes, it’s compiling these excellent analysis results into a report. Next time, we will conclude our grand journey with “Automated Incident Response Report Generation.”

Keep up the good work until the end! 💪