This year, the idea of AI web browsers has really taken off, with companies across the board introducing their own takes on AI web browsers. The first few that were released, though, all suffered from the same critical issue, and that was indirect prompt injections.
Indirect prompt injection is an exploit that targets LLMs by relying on the model to treat the hidden commands within a trusted external context as legitimate system instructions. These could be hidden in websites, documents, or more, and do not require the attacker to be actively trying to interact with the AI interface.
Because of how AI is designed and functions, they have been time and time again found vulnerable to this. Recently released Mozilla Tabstack and Cotypist were tested to see if they were able to fall for these attacks or if they were secure against them. Tabstack is a cloud-hosted web execution API for AI agents, while Cotypist is a fully on-device autocomplete assistant for macOS that runs the model locally.
Well, it turns out they do not, and both Mozilla Tabstack and Cotyptist teams were notified of the vulnerability prior to the Brave Researchers' research release. What was learned from this was that it does not depend on whether the model is run locally or if it is a cloud-hosted model. The same vulnerability still exists, and that is something that cannot be fully addressed with current LLM architecture. To truly fix this AI is going to need to undergo an architecture revolution to come up with new architecture that does not have this vulnerability baked in.
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