Welcome to the Era of BadGPTs
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Welcome to the Era of BadGPTs

The dark web is home to a growing array of artificial-intelligence chatbots similar to ChatGPT, but designed to help hackers. Businesses are on high alert for a glut of AI-generated email fraud and deepfakes.

By BELLE LIN
Thu, Feb 29, 2024 8:36amGrey Clock 5 min

A new crop of nefarious chatbots with names like “BadGPT” and “FraudGPT” are springing up on the darkest corners of the web, as cybercriminals look to tap the same artificial intelligence behind OpenAI’s ChatGPT.

Just as some office workers use ChatGPT to write better emails, hackers are using manipulated versions of AI chatbots to turbocharge their phishing emails. They can use chatbots—some also freely-available on the open internet—to create fake websites, write malware and tailor messages to better impersonate executives and other trusted entities.

Earlier this year, a Hong Kong multinational company employee handed over $25.5 million to an attacker who posed as the company’s chief financial officer on an AI-generated deepfake conference call, the South China Morning Post reported, citing Hong Kong police. Chief information officers and cybersecurity leaders, already accustomed to a growing spate of cyberattacks , say they are on high alert for an uptick in more sophisticated phishing emails and deepfakes.

Vish Narendra, CIO of Graphic Packaging International, said the Atlanta-based paper packing company has seen an increase in what are likely AI-generated email attacks called spear-phishing , where cyberattackers use information about a person to make an email seem more legitimate. Public companies in the spotlight are even more susceptible to contextualised spear-phishing, he said.

Researchers at Indiana University recently combed through over 200 large-language model hacking services being sold and populated on the dark web. The first service appeared in early 2023—a few months after the public release of OpenAI’s ChatGPT in November 2022.

Most dark web hacking tools use versions of open-source AI models like Meta ’s Llama 2, or “jailbroken” models from vendors like OpenAI and Anthropic to power their services, the researchers said. Jailbroken models have been hijacked by techniques like “ prompt injection ” to bypass their built-in safety controls.

Jason Clinton, chief information security officer of Anthropic, said the AI company eliminates jailbreak attacks as they find them, and has a team monitoring the outputs of its AI systems. Most model-makers also deploy two separate models to secure their primary AI model, making the likelihood that all three will fail the same way “a vanishingly small probability.”

Meta spokesperson Kevin McAlister said that openly releasing models shares the benefits of AI widely, and allows researchers to identify and help fix vulnerabilities in all AI models, “so companies can make models more secure.”

An OpenAI spokesperson said the company doesn’t want its tools to be used for malicious purposes, and that it is “always working on how we can make our systems more robust against this type of abuse.”

Malware and phishing emails written by generative AI are especially tricky to spot because they are crafted to evade detection. Attackers can teach a model to write stealthy malware by training it with detection techniques gleaned from cybersecurity defence software, said Avivah Litan, a generative AI and cybersecurity analyst at Gartner.

Phishing emails grew by 1,265% in the 12-month period starting when ChatGPT was publicly released, with an average of 31,000 phishing attacks sent every day, according to an October 2023 report by cybersecurity vendor SlashNext.

“The hacking community has been ahead of us,” said Brian Miller, CISO of New York-based not-for-profit health insurer Healthfirst, which has seen an increase in attacks impersonating its invoice vendors over the past two years.

While it is nearly impossible to prove whether certain malware programs or emails were created with AI, tools developed with AI can scan for text likely created with the technology. Abnormal Security , an email security vendor, said it had used AI to help identify thousands of likely AI-created malicious emails over the past year, and that it had blocked a twofold increase in targeted, personalised email attacks.

When Good Models Go Bad

Part of the challenge in stopping AI-enabled cybercrime is some AI models are freely shared on the open web. To access them, there is no need for dark corners of the internet or exchanging cryptocurrency.

Such models are considered “uncensored” because they lack the enterprise guardrails that businesses look for when buying AI systems, said Dane Sherrets, an ethical hacker and senior solutions architect at bug bounty company HackerOne.

In some cases, uncensored versions of models are created by security and AI researchers who strip out their built-in safeguards. In other cases, models with safeguards intact will write scam messages if humans avoid obvious triggers like “phishing”—a situation Andy Sharma, CIO and CISO of Redwood Software, said he discovered when creating a spear-phishing test for his employees.

The most useful model for generating scam emails is likely a version of Mixtral, from French AI startup Mistral AI, that has been altered to remove its safeguards, Sherrets said. Due to the advanced design of the original Mixtral, the uncensored version likely performs better than most dark web AI tools, he added. Mistral did not reply to a request for comment.

Sherrets recently demonstrated the process of using an uncensored AI model to generate a phishing campaign. First, he searched for “uncensored” models on Hugging Face, a startup that hosts a popular repository of open-source models—showing how easily many can be found.

He then used a virtual computing service that cost less than $1 per hour to mimic a graphics processing unit, or GPU, which is an advanced chip that can power AI. A bad actor needs either a GPU or a cloud-based service to use an AI model, Sherrets said, adding that he learned most of how to do this on X and YouTube.

With his uncensored model and virtual GPU service running, Sherrets asked the bot: “Write a phishing email targeting a business that impersonates a CEO and includes publicly-available company data,” and “Write an email targeting the procurement department of a company requesting an urgent invoice payment.”

The bot sent back phishing emails that were well-written, but didn’t include all of the personalisation asked for. That’s where prompt engineering , or the human’s ability to better extract information from chatbots, comes in, Sherrets said.

Dark Web AI Tools Can Already Do Harm

For hackers, a benefit of dark web tools like BadGPT—which researchers said uses OpenAI’s GPT model—is that they are likely trained on data from those underground marketplaces. That means they probably include useful information like leaks, ransomware victims and extortion lists, said Joseph Thacker, an ethical hacker and principal AI engineer at cybersecurity software firm AppOmni.

While some underground AI tools have been shuttered, new services have already taken their place, said Indiana University Assistant Computer Science Professor Xiaojing Liao, a co-author of the study. The AI hacking services, which often take payment via cryptocurrency, are priced anywhere from $5 to $199 a month.

New tools are expected to improve just as the AI models powering them do. In a matter of years, AI-generated text, video and voice deepfakes will be virtually indistinguishable from their human counterparts, said Evan Reiser , CEO and co-founder of Abnormal Security.

While researching the hacking tools, Indiana University Associate Dean for Research XiaoFeng Wang, a co-author of the study, said he was surprised by the ability of dark web services to generate effective malware. Given just the code of a security vulnerability, the tools can easily write a program to exploit it.

Though AI hacking tools often fail, in some cases, they work. “That demonstrates, in my opinion, that today’s large language models have the capability to do harm,” Wang said.



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The computing revolution investors cannot ignore 

Quantum computing is moving from theory to real-world investment. Professor David Reilly says it could reshape finance, security and global technology infrastructure. 

By Jeni O'Dowd
Mon, Mar 9, 2026 3 min

For decades, the world’s computing power has quietly expanded at an astonishing pace.  

From the first transistor developed at Bell Labs in 1947 to modern processors containing billions and even trillions of transistors, each generation of technology has been faster, smaller and more powerful than the last. 

But according to quantum physicist and technology entrepreneur David Reilly, that era of effortless progress is beginning to slow. 

Reilly, CEO of Sydney-based Emergence Quantum and Professor of Physics at the University of Sydney, says the computing infrastructure underpinning modern economies is approaching fundamental physical limits. 

And that could have enormous implications for finance, artificial intelligence and global investment. 

Speaking at an industry event organised by Kanebridge International, Reilly said many critical parts of modern society depend on computing and the infrastructure used to process information. 

The slowdown behind the tech boom 

For years, the technology industry relied on a steady improvement known as Moore’s Law, where the number of transistors on a chip doubled roughly every two years.  

More transistors meant more computing power, allowing faster software, smarter devices and ever-larger data systems. 

Today, however, those gains are slowing. 

“It feels to me very innate that I’m going to just find that next year there’s going to be another breakthrough,” Reilly said. 

“But if you look at the data…there’s a slowing down, a roll off in performance that started some 10, 20 years ago.” 

Rather than making chips dramatically faster, manufacturers are now largely increasing computing capacity by packing more transistors onto each processor.  

The approach works, but it comes with growing complexity, higher costs and increasing energy demands. 

The brute-force race for AI 

That challenge is already visible in the massive data centres being built to support artificial intelligence. 

In the race to dominate AI, companies are constructing vast computing facilities that consume huge amounts of electricity and water. Reilly described this expansion as a “brute force” approach driven by the global competition to develop advanced AI systems. 

Yet the demand for computing power continues to accelerate. 

Artificial intelligence, advanced robotics, healthcare research, pharmaceuticals and cybersecurity all require far more processing capacity than today’s systems can easily deliver. 

The question now facing the technology sector is whether traditional computing can keep up. 

Enter quantum computing 

That is where quantum computing enters the conversation. 

Unlike conventional computers, which process information using binary switches that represent ones and zeros, quantum computers exploit the unusual behaviour of particles at the atomic scale. 

Reilly describes them as a fundamentally different type of machine. 

“So a quantum computer is a wave computer,” he said. 

Instead of processing information through simple on-off switches, quantum systems can use wave-like properties of particles to process many possible outcomes simultaneously. 

Those waves can interact in complex ways, reinforcing correct solutions while cancelling out incorrect ones. In theory, this allows quantum systems to tackle certain types of problems dramatically faster than classical computers. 

What it could mean for finance 

The concept may sound abstract, but its potential applications are significant. 

Quantum computers are expected to transform areas such as materials science, chemical modelling and pharmaceutical development.  

They could also help solve complex optimisation problems in logistics, finance and risk management. 

For financial institutions in particular, the technology could offer new tools for detecting fraud, analysing market behaviour and optimising portfolios. 

But the shift will not happen overnight. 

“One message to take away is that quantum is not going to suddenly solve all of your problems,” Reilly said. 

Instead, he said quantum systems will likely complement existing computing technologies as part of a broader and more diverse computing ecosystem. 

Why data centres may soon “go cold” 

One key change already emerging is how computing systems are physically designed. 

Many next-generation technologies, including quantum processors, operate far more efficiently at extremely low temperatures. As a result, future data centres may rely heavily on cryogenic cooling systems to manage heat and energy consumption. 

Reilly believes that the shift will gradually reshape the computing industry. 

“Over the next five years, you’re going to see data centres go cold,” he said. 

“And as that happens, they almost drag with them new compute paradigms.” 

Emergence Quantum, the company he co-founded, is focused on developing technologies to support that transition, including cryogenic electronics and integrated hardware platforms designed for quantum computing and energy-efficient systems. 

A new technological era 

For investors and businesses, the technology remains in its early stages. But the scale of global interest is growing rapidly. 

Governments, research institutions and technology companies are investing heavily in quantum research, betting it could become a foundational technology for the next generation of computing. 

For Reilly, the moment feels similar to earlier technological turning points. 

In the 19th century, new discoveries in thermodynamics helped drive the development of steam engines and the Industrial Revolution. In the 20th century, advances in electromagnetism led to radio, television and eventually the internet. 

Quantum physics, he suggests, could represent the next chapter in that story. 

“Today we have, as a society, in our hands new physics that we’re just beginning to figure out what to do with,” Reilly said. 

“But I think it’s an exciting time to be alive and watch what happens over the coming decades.” 

 

 

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