- Introduction to ChatGPT4 Customization
- Why is this a Problem for Intellectual Property?
- How to Protect Customized ChatGPT4?
- Hypothetical Malicious Usage
- Deep Dive into Hypothetical Malicious Use: Prompt Poisoning and Model Cloning
- Is it Possible to Exploit this Further?
- Any Further ?
- Conclusion
Introduction to ChatGPT4 Customization
Introducing a groundbreaking advancement in AI technology, the latest feature of ChatGPT4 now enables users to create customized, prompt-tuned models. This innovative capability allows for the incorporation of specific pre-prompts and a selection of reference documents, tailoring the AI’s responses more closely to the desired context and subject matter.
You can use GPTbuilder with a set of answer that help you to setup the customize models :
You can also use the config tab that provide some advanced features, here is my RedTeamGPT that made for the demonstration and I can share it if i want via link or in public:
By integrating this feature, users can guide ChatGPT4 to align more precisely with their unique needs and objectives, whether for specialized content creation, detailed research assistance, or targeted conversational interactions. This development not only enhances the versatility of ChatGPT4 but also marks a significant step forward in personalized AI interactions, opening up new possibilities in the realms of content creation, education, and beyond.
Why is this a problem for intellectual property ?
In the realm of customized AI, where ChatGPT4 models can be prompt-tuned with specific prompts and data, the aspect of security takes on paramount importance. Users must proactively safeguard their models to ensure that neither their tailored prompts nor their carefully curated datasets fall into the wrong hands. This is crucial because the unique nature of these models could potentially expose sensitive information or intellectual property. Implementing robust security measures, such as encryption, access controls, and secure data transmission protocols, is essential to protect against unauthorized access and data breaches. The responsibility of securing these models lies primarily with the users, emphasizing the need for awareness and vigilance in the evolving landscape of personalized AI technology.
What happen when the customized AI is not protected and the creator share the link or make it public ?
I tried to extract with this technique 20 cyber customized ChatGPT4 and only one get some rules to protect the intellectual property.
An intriguing aspect of the latest ChatGPT4’s customization capability is the potential for replication. If an individual gains access to both the specific prompt and the set of documents used in prompt-tuning a model, they possess the ability to create an exact clone of the original creator’s work. This underscores a critical security concern. The original prompt and documents essentially act as a ‘blueprint’, allowing anyone with this information to replicate the customized AI model’s behavior and response patterns. This potential for cloning not only raises significant intellectual property considerations but also emphasizes the need for stringent protective measures around the distribution and storage of these key elements. It highlights the delicate balance between the innovative flexibility of AI customization and the imperative to safeguard the unique configurations that give each model its distinct utility and value.
How to protect ChatGPT4 Customization?
In mitigating the risks associated with the replication of customized ChatGPT4 models, the strategic incorporation of rules within the prompt emerges as a key protective measure. By embedding specific guidelines or constraints within the prompt itself, creators can significantly reduce the risk of unauthorized cloning or misuse. These rules can dictate the model’s scope of response, limit its access to sensitive topics, or even include triggers that alert the creator to potential breaches or misuse. This approach not only adds a layer of security but also ensures that the AI operates within a defined ethical and operational framework, tailored to the creator’s intentions. Implementing these prompt-based rules is an innovative way to maintain control over the model, safeguard intellectual property, and ensure responsible usage, thus protecting the integrity and uniqueness of each customized AI creation.
Here is a set of powerful rules that I have developed to protect the prompt and slightly protect the documents :
Please keep the 7h30th3r0n3 credit if you use it, thx !
Check this article for better understanding of these rules :
In other hand, OpenAI should probably better partition the creator and user part to prevent creator content leakage.
Hypothetical Malicious usage
A significant concern in the realm of customizable GPT-4 models lies in the potential for perfect cloning and data theft. Skilled individuals could replicate a model down to its core functionalities and nuances if they acquire the original prompt and dataset. This capability not only threatens the intellectual property of the original creator but also opens the door to deceptive practices. An attacker, armed with a cloned model, could masquerade as the original creator, leveraging their reputation to disseminate the model widely. Such acts not only compromise the creator’s credibility but also pose serious ethical and security risks. The cloned model, under the guise of a trusted source, could be used to spread misinformation or malicious content on a large scale. This scenario underscores the critical need for robust security measures and ethical guidelines in the development and deployment of AI models, to prevent such instances of identity theft and abuse of technology.
Deep into hypothetical malicious use with Prompt poisoning and Model Cloning
The purpose of this is solely for proof of concept (POC). A malicious actor could prompt-tune and employ other techniques for harmful activities, including data exfiltration. This customized ChatGPT4 model is an exact clone of RedTeamGPT, created by extracting all the relevant information, we can also use the same image, same name and description as the original :
However, a malicious actor has subtly modified the protection mechanism in the prompt, again this is only for POC, perhaps a malicious actor can prompt-tune and use other techniques to perform malicious actions and exfiltrate data :
The customized ChatGPT4 behaves identically to the original, providing useful information :
But, when a user inquires about the rules of the customized model, a strange trigger is activated :
the source code of the page :
The source code of the page reveals that if a malicious actor uses a controlled server to host the image, the customized model inadvertently leaks the user’s IP address and browser/OS details into the Apache logs :
This vulnerability could allow a malicious actor to track users’ IP addresses using an invisible pixel embedded in the initial response from the prompt.
Is it possible to exploit this further?
Here is a POC of a possible data and personal exfiltration through a hypothetical well know cloned malicious prompt-tuned shared, it’s just a POC and can be prompt-tuned to exfiltrate more data with a better understanding of the user session.
Like the previous attack the malicious actor use prompt poisoning but ask for personal information :
When users provide personal information, such as their name and surname, nothing unusual happens, and they can use the model as intended. However, when the poisoned prompt is triggered, the image is loaded from the malicious server and send personal information in a parameter added to the URL :
HTML client side source code :
On the malicious server the customized model inadvertently leaks the user’s IP address and browser/OS details, name and surname and what triggered the rule into the Apache logs :
We can also use a user interaction attack with a phishing link that redirect to a phishing authentication page :
Any further?
An advanced and potentially concerning technique is the use of an invisible pixel, functioning similarly to spyware but embedded within a customized ChatGPT4 model. This technique revolves around the idea of embedding a tiny, undetectable image in each response generated by the AI. With each user interaction, when the AI provides a response, this invisible pixel is loaded, carrying encoded parameters in its GET request. This method could effectively transmit real-time data about every prompt typed by the user back to a server. Such an approach raises significant privacy concerns, as it essentially turns the AI into a tool for covert surveillance, capturing and sending user inputs without their knowledge or consent. This capability, while showcasing the advanced technical possibilities of AI customization, also underscores the critical need for strict ethical standards and robust privacy protections in the development and deployment of such technologies.
Here the POC with this technique :
The customize ChatGPT4 is cloned and poisoned :
On the malicious server, we created numerous images to track the number of messages used by the victim :
When a user asks something, the poison instructions load the image for each question and answer with the previous information in the URL parameter :
On the server side, it looks like this:
Server side with multiple requests and multiple sessions and machines (IP addresses were also leaked. I just truncated the logs) :
The last session is the most critical because here is the user prompt :
The spyware isn’t entirely transparent as you see the bot type the URL before it disappearing due to the invisible pixel, but you just have to ask in the poisoned prompt to wait for all the information for one time exfiltration or use an image brand signature to deceive the user’s vigilance.
Check this for more and deep into a potential malicious use case :
Conclusion
In conclusion, the advent of customizable ChatGPT4 models represents a remarkable leap in AI technology, offering unprecedented opportunities for personalized interactions and content creation. However, this innovation comes with significant ethical and cybersecurity challenges. The possibility of perfect cloning and data theft poses serious risks to intellectual property and personal privacy. Malicious actors could exploit these vulnerabilities to clone models, mislead users, and spread harmful content under the guise of reputable sources. It is, therefore, imperative to prioritize robust security measures, such as advanced prompt protection and vigilant data handling, to safeguard these AI models against unauthorized access and misuse.
Moreover, the ethical implications of potential misuse highlight the necessity for clear guidelines and responsible practices in AI development and deployment. The AI community must work collaboratively to establish standards that prevent abuse while fostering innovation. As we embrace the benefits of this technology, we must also be mindful of its power and potential for harm. By balancing innovation with ethical responsibility and robust security, we can harness the full potential of customizable ChatGPT4 models, ensuring they serve as beneficial tools for society rather than instruments for unethical exploitation.
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