The Tea dating app, designed to help women share safety information about potential male dating partners, suffered a data breach that exposed 72,000 images including users' government IDs, selfies, and direct messages to hackers who posted the data on 4chan.
The Tea app, launched in 2023 by founder Sean Cook, is a dating safety platform that allows women to anonymously share information about men they might date, conduct background checks, and perform reverse image searches. The app gained massive popularity in July 2024, reaching the top of app download charts with over 2 million new user requests in just a few days. On July 25, 2024, the company discovered a major data breach affecting users who signed up before February 2024. Hackers accessed a legacy storage system containing approximately 72,000 images, including 13,000 selfies and government identification documents that had been used for user verification. The breached data also included images from posts, comments, and direct messages. Anonymous users posted this sensitive data, including drivers' licenses containing personal details, to the 4chan message board. Online trolls claimed to have created a map of Tea subscribers' locations using metadata from the leaked photos. The company stated the breached data was stored 'in compliance with law enforcement requirements related to cyberbullying prevention' and had not been moved to newer, more secure systems. Two class action lawsuits have been filed in California in response to the breach, and the incident has sparked broader debates about the safety and ethics of anonymous whisper network platforms.
Domain classification, causal taxonomy, severity scores, and national security assessments were LLM-classified and may contain errors.
Vulnerabilities that can be exploited in AI systems, software development toolchains, and hardware, resulting in unauthorized access, data and privacy breaches, or system manipulation causing unsafe outputs or behavior.
Other
Due to some other reason or is ambiguous
Other
Without clearly specifying the intentionality
Post-deployment
Occurring after the AI model has been trained and deployed