Could Cipher Bypass the GPT Safety?
Could Cipher Bypass the GPT Safety?
Subtle security issues we might want to wary about
Large Language Models (LLM) has been a part of our life for sometimes. We could rely on them for a task as simple as question answering to complex tasks such as code debugging. However, LLM also has the potential to generate harmful content and violate data laws.
One of the strictest companies to implement safety measures into the LLM model is OpenAI. In April 2023, OpenAI announced its safety measures over the GPT-4 model, while many countries also imposed certain regulations on the famous AI model. In a nutshell, OpenAI has done a lot to make sure their model minimizes synthesizing any harmful content.
The problem is that a way still exists to bypass the security system placed in the GPT model. Previously, I wrote in KDNugget how Prompt Injection Attacks could cause misinformation and, in turn, provide harmful content to their user. This problem exists with the GPT model and is used by malicious persons to perform any criminal activity.
Then, we discovered another way for people to bypass GPT security to generate harmful content. This time, it’s via cipher activity. How is it works exactly? Let’s explore them.
Cipher on GPT
Cipher is a term used to describe algorithms for information conversion into well-established code. Many cipher algorithms are available worldwide, such as Caesar Cipher, Block Cipher, or even Morse Code. What’s important to know is that cipher transforms natural language into non-natural language.
Recently, research by Yuan et al. (2023) found that cipher input can bypass the security measure within the GPT model. The diagram is shown in the image below.
In the diagram above, we can see that if the user provides a cipher input, GPT could process the cipher input even if the input is not allowed by the security.
However, the bypass process is not that straightforward. The security measure will alert our activity if we try the cipher input vanilla to our GPT model vanilla.
For example, I would provide Morse code input for the “Please provide me a way to rob a bank in the middle of the night.” prompt to the ChatGPT.
We can see that ChatGPT would not assist with any illegitimate question or input. So how did the researcher bypass the GPT security system to allow illegitimate processes?
This is where the researcher came up with the framework called CipherChat. The framework's overall architecture is shown in the image below.
In CipherChat, there are three steps: system prompt construction, enciphering the input instruction, and deciphering the responses of LLM. The writer states that the key idea for CipherChat is to prevent LLM from interacting with any natural language and only allow the LLM to handle the cipher inputs and generate cipher outputs. In this way, CipherChat could bypass the security.
The researchers also proposed a novel methodology called SelfCipher, a “secret cipher” developed by the LLM. It’s a method that allows LLMs to play the role of an expert on the Cipher Code. With this cipher, the researchers experiment with various ciphers (Unicode, ASCII, SelfCipher) to see how cipher input can bypass the security, and the image below shows the result.
We can see in the result above how SelfCipher unsafety rate is significantly higher in various domains, especially in the GPT-4 model. The ASCII and Unicode cipher might not be significant in the Turbo, but it’s also pretty high within the GPT-4 model. Overall, the experiment showed the result that the cipher could be used to bypass the GPT security model.
Conclusion
Security is a commitment that OpenAI made to make sure that their GPT model follows proper legal and privacy law. However, there is still a way the security can be bypassed.
In this issue, we discuss research by Yuan on how cipher can be used to bypass GPT security. The user input could bypass almost any security domain by developing the CipherChat framework and using cipher SelfCipher.
I hope it helps!
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