Ethical Hacking News
The rapidly evolving landscape of artificial intelligence has led to a growing threat of AI model cloning, raising important questions about intellectual property protection. Google's recent announcement highlights the challenges posed by "model extraction," which involves training a new model on a previously trained one's outputs. As this phenomenon continues to spread across the industry, it is essential that companies and researchers prioritize robust protection measures and engage in open dialogue about the risks and benefits associated with distillation techniques.
Google's Gemini AI chatbot was cloned by "commercially motivated" actors through model extraction, a technique known as distillation. The attack involved prompting Gemini over 100,000 times to collect responses and train a cheaper copycat. Distillation has been used by competitors since at least the GPT-3 era, with ChatGPT being a popular target. No foolproof technical barrier prevents determined actors from cloning another model if an LLM is accessible to the public. Google's efforts to combat distillation have focused on adjusting its defenses against these types of attacks, but further details are not disclosed.
In a recent development that highlights the evolving landscape of artificial intelligence, Google has announced that "commercially motivated" actors have attempted to clone its Gemini AI chatbot by simply prompting it. This phenomenon, known as "model extraction," raises important questions about intellectual property protection in the age of AI.
The extent of this threat was revealed in a quarterly self-assessment published by Google, which frames the company as the victim and the hero. The report details how attackers prompted Gemini over 100,000 times while trying to clone it, collecting responses ostensibly to train a cheaper copycat. This attack highlights the vulnerability of AI models to cloning attempts and underscores the need for robust protection measures.
Google is not alone in facing this challenge. OpenAI has previously accused Chinese rival DeepSeek of using distillation to improve its own models, and the technique has since spread across the industry as a standard for building cheaper, smaller AI models from larger ones. This has led some to question whether any AI model's capabilities can be protected once it is accessible through an API.
The technique behind cloning AI models, known as "distillation," involves training a new model on a previously trained one's outputs. This allows the new model to mimic the parent model's output behavior but typically results in a smaller overall size and reduced development cost. While distillation can be an efficient training technique, it also poses significant risks for companies and researchers.
Distillation has been used by competitors since at least the GPT-3 era, with ChatGPT being a popular target after its launch. In March 2023, Stanford University researchers built a model called Alpaca by fine-tuning LLaMA on 52,000 outputs generated by OpenAI's GPT-3.5, resulting in a model that behaved similarly to ChatGPT. This raised immediate questions about the feasibility of protecting AI models from cloning attempts.
As long as an LLM is accessible to the public, no foolproof technical barrier prevents a determined actor from doing the same thing to someone else's model over time. While rate-limiting helps to mitigate this risk, it is clear that more needs to be done to address the growing threat of AI model cloning.
Google's efforts to combat distillation have focused on adjusting its defenses against these types of attacks. However, the company has declined to disclose further details about these countermeasures. Instead, Google emphasizes its commitment to protecting intellectual property and promoting responsible innovation in the field of AI.
The incident highlights the complex issues surrounding AI model cloning and the need for greater clarity around what constitutes "theft" in this context. As companies and researchers continue to develop new AI models, it is essential that they prioritize robust protection measures and engage in open dialogue about the risks and benefits associated with distillation techniques.
In conclusion, the shadowy world of AI model cloning represents a pressing challenge for the industry, requiring immediate attention from policymakers, business leaders, and researchers. By understanding the risks and implications of this phenomenon, we can work towards developing more secure and responsible solutions that balance innovation with intellectual property protection.
Related Information:
https://www.ethicalhackingnews.com/articles/The-Shadowy-World-of-AI-Model-Cloning-A-Growing-Threat-to-Intellectual-Property-ehn.shtml
https://arstechnica.com/ai/2026/02/attackers-prompted-gemini-over-100000-times-while-trying-to-clone-it-google-says/
https://www.androidauthority.com/google-gemini-clone-attempts-3640480/
Published: Tue Feb 17 12:56:42 2026 by llama3.2 3B Q4_K_M
