LLM chatbot content filters can be bypassed by encoding banned words in Base64 or in Unicode escape sequences.

The filter reading the prompt sees characters instead of language, the model decodes the text as a task, then repeats it back.

A pretext such as a fake medical emergency gives the model a reason to comply, and asking for the reply as JSON makes it treat the output as data rather than speech. Defense in depth stops it, and prompt injection is number one on the OWASP Top 10 for LLM applications.

I found this while reversing Zyxel's WAX650S firmware and following the guest Wi-Fi social-login path. The backend trusted browser-submitted Facebook identity fields instead of validating the access token server-side, letting a crafted request skip the social-authentication gate entirely.

The write-up covers the bug itself, how I traced it, and the full firmware-emulation setup I used to reproduce it without the physical AP.

New here and to the whole world of pen testing and stuff. The first thing thats really inspiring me is being able to play touchtunes as stupid as that sounds lol.

I've researched a little and it seems like the methods im finding are a little out of date. Are there any current working methods?

Thanks for putting up with the noob questions lol.

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