The rapid expansion of artificial intelligence has led to a surge in new applications, many of which function as “wrappers” that connect users to powerful language models like ChatGPT, Claude, or Gemini. While these platforms offer impressive capabilities, they frequently operate on the “speed-to-market” principle, where security is occasionally neglected in favour of rapid deployment. A recent and significant data exposure has highlighted the severe consequences when these innovative tools lack a solid cybersecurity foundation.
The Chat & Ask AI Data Exposure
A prominent example as reported by 404media (https://www.404media.co/massive-ai-chat-app-leaked-millions-of-users-private-conversations/) of these risks involves the popular application Chat & Ask AI, which claims to have more than 50 million users across major mobile platforms. An independent security researcher recently discovered that hundreds of millions of private messages within the app were left entirely exposed to anyone with the right technical knowledge.
The nature of the leaked data was deeply concerning. The exposed database contained approximately 300 million messages from over 25 million users, including complete chat histories and timestamps. Some of these conversations included highly sensitive and personal queries, such as individuals seeking crisis support or discussing illegal activities. This incident serves as a stark reminder that users often treat artificial intelligence chatbots as confidential confidants, making the protection of this data a critical responsibility for developers.
The Pitfall of Default Configurations
The technical cause of this massive exposure was not a sophisticated external attack but a common misconfiguration of the mobile development platform Google Firebase. Firebase is a widely used backend service that simplifies data storage for mobile applications. However, its default settings can occasionally lead to security gaps if they are not carefully adjusted.
In this instance, the app’s configuration made it possible for anyone to register as an “authenticated” user and subsequently gain access to the backend storage where user data was kept. This highlight a frequent misunderstanding in development: the belief that requiring a login is equivalent to implementing robust access controls. Without specific security rules to restrict data access to the rightful owner, the simple act of “authenticating” can unintentionally grant a user the keys to the entire database.
The Illusion of Inherited Security
Many organisations building artificial intelligence platforms operate under the misconception that because they are using secure APIs from industry leaders like OpenAI or Anthropic, their entire system is inherently protected. This is rarely the case. While the underlying models are heavily secured by their respective providers, the “wrapper” or application layer built around them remains the responsibility of the developer.
As seen in this breach, the vulnerability did not lie in the artificial intelligence itself, but in the infrastructure used to host and manage the user interactions. To achieve a stronger security posture, it is vital to recognise that every component of an application, from the user interface to the backend database, requires its own dedicated protection strategies.
Strategies for a Stronger Defence
To help enhance the security of emerging technology platforms, organisations could consider implementing the following protections:
- Implement Principle of Least Privilege: Access to databases and storage should be restricted to the absolute minimum required for the application to function, ensuring that users can only ever see their own data.
- Conduct Regular Technical Audits: Engaging in professional security audits can help identify misconfigurations and vulnerabilities before they can be exploited by malicious actors.
- Perform Penetration Testing: Manual and automated penetration testing allows experts to ethically challenge your defences, simulating real-world attacks to find hidden access points.
- Hardening Backend Configurations: Moving beyond default settings is essential. Developers should prioritise hardening their cloud and backend environments according to industry best practices.
- Employee Training: Ensuring that development teams are aware of the unique risks associated with third-party platforms and artificial intelligence integration can significantly reduce the likelihood of human error.
How Vertex Can Assist
Building a secure digital product requires expertise that goes beyond simple coding. At Vertex Cyber Security, we believe that “good enough” is not sufficient to protect against modern threats. Our team of expert penetration testers and cyber security experts is experienced in identifying vulnerabilities in complex systems, APIs, and applications.
Whether you are in the early stages of developing an artificial intelligence platform or wish to verify the security of an existing system, we can provide tailored solutions ranging from technical audits to managed security services. We encourage you to contact the team at Vertex for further assistance in ensuring your innovation remains secure and your users’ trust is protected.