Data breach in ChatGPT: personal information and credit card details exposed to other users

The first data breach was discovered in the artificial intelligence-powered chatbot ChatGPT. OpenAl has announced that it has detected a bug that has exposed some ChatGPT users’ personal information and credit card information to other users.

The American company OpenAl, which received $ 10 billion in support from Microsoft, announced that a data breach had occurred in ChatGPT, which it developed itself.
The leak was discovered this week when users were able to see chat threads that didn’t belong to them in their conversation history.
Users shared images of their chat history, which they said were not theirs, on social media sites Reddit and Twitter.
Sam Altman, CEO of OpenAI, said the company felt bad about the bugs, but important bugs have been fixed.
“It was possible for some users to see the first and last name, email address, payment address, (only) the last four digits of the credit card number, and credit card expiration date of another active user,” OpenAI said in a statement. it was said.
The statement said that 1.2 percent of ChatGPT Plus subscribers were affected by the situation. However, ChatGPT has about 100 million users worldwide, although it is unknown how many of them pay for the service.
ChatGPT is a prototype conversational AI chatbot that can understand natural human language and produce impressively detailed, human-like written text. This chatbot, pretending to be a human, is able to give such precise answers in its answers, thanks to the deep learning based language model GPT-3.5.
Trained by artificial intelligence and machine learning, the system is designed to provide information and answer questions through a chat interface. “The dialogue format allows ChatGPT to answer follow-up questions, admit errors, challenge false premises and reject inappropriate requests,” the research organization said in a statement last week.
-Question-answer -Writing texts (basic academic articles, literary texts, film scripts, etc.) -Solving mathematical equations -Debugging and correcting (e.g. finding and correcting errors in each block of code) -Translation between languages ​​-Text summary and detect text within text keywords -Make recommendations -Rating -Describe what something does (e.g. explain what a block of code does)

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