- Generative AI tools present significant data security risks if sensitive information is entered, but these can be mitigated through intentional policy, education, and technology integration.
- Balancing risk management with innovation allows organizations to safely leverage the benefits of GenAI tools without compromising security or compliance.
Does ChatGPT Leak Data?
An intentional, balanced approach across people, process, and technology is the only way to truly mitigate the risk of data leaking via a GenAI tool.
By The Mimecast Cyber Insights Blog Team
Key Points
In November 2022, OpenAI released ChatGPT, a generative artificial intelligence (GenAI) tool, which has since taken the world by storm. Only two months after its launch, it had over 100 million users, making it “the fastest-growing consumer application in history.” And ChatGPT is not alone.
While any new technology presents risks, it doesn’t mean the risks are all brand new. In fact, companies might find that they already have many of the people, processes, and technology in place to mitigate the risks of GenAI tools but need to fine-tune them to include this new technology category.
That being said, companies should not assume they are already protected from these risks; instead, they should be intentional in their risk mitigation.
Employees love GenAI. Shadow AI loves your data. With 90% of Shadow AI data loss happening through simple copy-paste actions, your confidential info could be slipping away unnoticed. Mimecast monitors risky GenAI use in real time so you can enable innovation without compromising security.
How might GenAI tools like ChatGPT pose risks to sensitive information?
Most GenAI tools are designed to take a “prompt” from the user, which might be entered/pasted text, a text file, an image, live or recorded audio, a video, or some combination of them and then perform some action based on the prompt used. ChatGPT, for example, can summarize the content of a prompt (“summarize these meeting notes…”) and debug source code (“identify what’s wrong with this code…”).
The risk is that these prompts can be reviewed by the GenAI tool developers and might be used to train a future version of the tool. In the case of public tools, the prompts become part of the language model itself, feeding it content and data it would not otherwise have. If these prompts only include information that’s already public, there may be little risk; however, in the example above, if the meeting notes included sensitive information or the source code was proprietary, this confidential data has now left the control of the security team and potentially put compliance obligations and intellectual property protections at risk.
In the most extreme situation, someone’s input might become someone else’s output.
And that’s not only theoretical.
In January 2023, Amazon issued an internal communication restricting ChatGPT use after it discovered ChatGPT results “mimicked internal Amazon data.” And while the initial data used to train ChatGPT stopped being collected in 2021, ChatGPT isn’t done training. In fact, in the future, when an engineer asks for help optimizing their source code it might look just like the proprietary data from Samsung’s semiconductor division.
Related Tags
- Artificial Intelligence