AI on the Dark Web: Are Cybercriminals Using ChatGPT Too?

Artificial intelligence is reshaping everything—from healthcare to art to crime. While much of the world is focused on the ethical and commercial applications of AI, a quieter, darker evolution is unfolding in the hidden corners of the internet.

On the dark web, cybercriminals are beginning to harness ChatGPT-style language models and machine learning tools to automate scams, write malicious code, and enhance their operations. This isn’t science fiction—it’s a growing trend that’s shifting how underground actors operate.

Are they really using ChatGPT? Or are they building their own tools? And what does it mean when AI becomes just another weapon in the cybercrime arsenal?

Can Cybercriminals Use ChatGPT Directly?

OpenAI and other AI developers have implemented moderation systems to prevent abuse. If you ask ChatGPT to help build ransomware, it will refuse. But criminals are creative—and determined.

1. Bypassing Restrictions

Some cybercriminals try to trick public AI tools into providing help by:

• Rephrasing prompts (e.g., asking for “a script that encrypts files for backup” instead of “ransomware”)
• Role-playing scenarios to get past safety filters
• Using jailbreak prompts designed to override content moderation

While this works occasionally, it’s inconsistent—and increasingly monitored. So instead of relying on OpenAI, many are building clones or using open-source alternatives.

2. Private AI Models and Local Deployments

Open-source models like GPT-J, LLaMA, and GPT-NeoX allow anyone to run ChatGPT-like systems offline. Dark web actors have:

• Downloaded and fine-tuned these models for malicious use
• Removed ethical guardrails that block dangerous outputs
• Shared AI tools in hacking forums as pre-packaged kits

These models don’t rely on any external servers, meaning no oversight, no restrictions, and full control over how they’re used.

How Cybercriminals Are Using AI on the Dark Web

AI is no longer experimental—it’s actively being integrated into darknet business models, expanding what lone operators and small groups can accomplish.

1. Malware and Phishing Generation

Language models can generate:

• Convincing phishing emails tailored to specific industries or individuals
• Scripts in Python, PowerShell, or JavaScript that steal data or deploy payloads
• Fake websites and scam landing pages that mirror real services

In the past, crafting these required skill. Now, it takes a few well-written prompts.

2. Social Engineering at Scale

AI chatbots are being deployed in:

• Romance scams, where chatbots maintain multiple long-term conversations with victims
• Fraud call centers, where voice cloning and AI-powered scripts manipulate targets
• Telegram-based dark web support bots, which simulate vendor-buyer negotiations or tech support

These tools dramatically reduce the time and labor cost of running scams, making them more scalable than ever.

3. Market Automation and Admin Tools

AI is being used to manage darknet marketplaces, with features such as:

• Auto-responders for vendors handling orders and questions
• Automated dispute resolution systems
• Predictive analytics to flag law enforcement infiltration or vendor fraud

Market admins are treating their platforms like startups—except the product is crime.

Darknet Forums Discussing AI Tools

On forums like Dread, Exploit.in, RAMP, and BreachForums (before takedown), users have openly discussed:

• Custom AI models designed for spear-phishing campaigns
• Language models trained on forum posts, malware code, and vendor logs
• Requests for “ChatGPT without ethics” or “jailbroken GPTs for red teams”

Some posts offer tutorials on how to fine-tune models for cybercrime. Others sell pre-built AI bundles marketed as “HackerGPT” or “DarkGPT”—though many of these are scams themselves.

The Ethical and Security Implications

The rise of AI on the dark web isn’t just a technical issue—it’s a societal one.

1. Lowering the Barrier to Entry

Previously, cybercrime required skill. With AI, almost anyone can:

• Write malicious code without knowing how it works
• Run scams with minimal effort
• Clone online content to impersonate banks, companies, or government services

AI is democratizing crime, which may lead to an explosion of low-skill, high-volume attacks.

2. Harder Detection and Response

AI-generated content is harder to detect than traditional phishing or malware. Emails are grammatically perfect. Scam scripts mimic real conversation. Code is obfuscated.

Security firms now need AI-powered detection tools just to keep up. It’s becoming an arms race.

3. The Ethics of Open Source

Open-source AI was meant to encourage innovation and transparency. But now, forums debate whether these tools should be restricted or licensed, as bad actors exploit them for harm.

Some developers have begun inserting “ethical tripwires” into open-source code. Others argue that’s censorship.

The Road Ahead: AI, Crime, and the Hidden Web

AI won’t replace cybercriminals—it will enhance them. As models grow stronger and easier to deploy, the dark web will host more automated criminal services, AI-generated disinformation, and synthetic fraud operations.

Expect to see:

• Custom AI marketplaces offering tailored criminal tools
• Private language models trained exclusively on darknet data
• AI-powered zero-day exploitation engines
• Dark web forums moderated and staffed by bots

The future of cybercrime isn’t just hidden—it’s automated.