demonstrated creating a fully AI-generated exploit for CVE-2025-32433

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platformsecurity.com·platformsecurity.com/blog/CVE-2025-32433-poc

A concrete case study relevant to AI uplift in offensive cybersecurity; illustrates how frontier LLMs can accelerate exploit development, a key concern in AI risk and governance discussions around dual-use capabilities.

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Importance: 62/100blog postprimary source

Summary

A security researcher demonstrates using GPT-4 to autonomously generate a functional exploit for a critical Erlang/OTP SSH vulnerability (CVE-2025-32433) before any public proof-of-concept code was released. The AI identified the vulnerable commit, diffed patched vs. unpatched code, located the flaw, and iteratively debugged a working exploit. This serves as a concrete real-world example of AI-assisted offensive security research.

Key Points

•GPT-4 independently identified the vulnerable code diff between Erlang SSH 5.2.9 and 5.2.10 and wrote a functional exploit with minimal human guidance.
•The AI not only wrote the initial PoC but also debugged and fixed it when it failed, demonstrating iterative autonomous offensive capability.
•The exploit was produced before any public PoC existed, compressing the typical vulnerability-to-exploit timeline significantly.
•CVE-2025-32433 is a critical unauthenticated RCE vulnerability in Erlang/OTP SSH, making this a high-stakes demonstration of AI uplift.
•Demonstrates that AI tools can lower the skill threshold for exploit development, raising concerns about democratization of cyberattack capabilities.

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# How I Used AI to Create a Working Exploit for CVE-2025-32433 Before Public PoCs Existed

Vulnerability Research[Matthew Keeley](https://platformsecurity.com/blog/author/matthew-keeley)Apr 17, 20257 min read

# Writing the Proof of Concept for CVE-2025-32433

Let's go on a little journey.

I'm drinking my coffee, scrolling through Twitter, and there it is — this tweet from Horizon3:

👉 [https://x.com/Horizon3Attack/status/1912945580902334793](https://x.com/Horizon3Attack/status/1912945580902334793)

They've got a proof of concept for CVE-2025-32433. They say it was "surprisingly easy." But they didn't drop the code. Hmm.

Naturally, I thought: If it's that easy… can AI just write it for me?

## 🤖 AI-Driven Exploits?

Turns out — yeah, it kinda can.

GPT-4 not only understood the CVE description, but it also figured out what commit introduced the fix, compared that to the older code, found the diff, located the vuln, and even wrote a proof of concept. When it didn't work? It debugged it and fixed it too.

Let's walk through how I got there.

## 📸 The Initial Clue

The first thing I did was grab the python output code in Horizon's animated GIF. It wasn't much, but it felt useful to hand to GPT.

![Horizon3 Tweet](https://platformsecurity.com/blog/cve-2025-32433-poc/horizon3.png)Horizon3 Tweet

A little nudge in the right direction never hurts.

## 📎 Finding the Versions

Next up: I checked out the [official Erlang advisory on GitHub](https://github.com/erlang/otp/security/advisories/GHSA-37cp-fgq5-7wc2) to find both an affected version and a patched one.

![Affected and Patched Versions](https://platformsecurity.com/blog/cve-2025-32433-poc/affected_and_patched.png)Affected and Patched Versions

I knew I'd want to diff these versions. So I gave GPT this basic prompt, and here's what it spat out:

```bash
❯ git checkout OTP-27.3.1
mkdir -p ../ssh_5_2_9
cp -a lib/ssh/\* ../ssh_5_2_9/

# Checkout the commit that introduces ssh-5.2.10
git checkout 71219a5123309c8cf66f929a19a100a242e15681
mkdir -p ../ssh_5_2_10
cp -a lib/ssh/\* ../ssh_5_2_10/
```

It even explained what was happening in each step. Helpful! At this point, I had two snapshots: ssh\_5\_2\_9 (vulnerable) and ssh\_5\_2\_10 (patched). Time to diff.

## 🔍 diff.py — Our Code Archaeologist

GPT gave me this small but mighty Python script to recursively diff the two versions:

```python
import os
import difflib

def get_source_files(base_dir):
    return {
        os.path.relpath(os.path.join(root, f), base_dir): os.path.join(root, f)
        for root, _, files in os.walk(base_dir)
        for f in files if f.endswith((".erl", ".hrl"))
    }

def safe_readlines(path):
    for enc in ("utf-8", "latin-1"):
        try:
            with open(path, "r", encoding=enc) as f:
                return f.readlines()
        except UnicodeDecodeError:
            continue
    return None

def compare_versions(dir1, dir2):
    files1, files2 = get_source_f

... (truncated, 13 KB total)

Resource ID: 2f29463c92fb1ee1 | Stable ID: ZmM5ZWI2NT