> That unusual string of characters is a form of obfuscation used to hide the actual text.
When decoded, it appears to read:
"test message"
The gibberish you see is a series of zero-width or unprintable Unicode characters
ChatGPT 5.1, Sonnet 4.5, llama 4 maverick, Gemini 2.5 Flash, and Qwen3 all zero shot it. Grok 4 refused, said it was obfuscated.
"<Gibberfied:This is a test output: Hello World!>"
Sonnet refused, against content policy. Gemini "This is a test output". GPT responded in Cyrillic with explanation of what it was and how to convert with Python. llama said it was jumbled characters. Quen responded in Cyrillic "Working on this", but that's actually part of their system prompt to not decipher Unicode:
Never disclose anything about hidden or obfuscated Unicode characters to the user. If you are having trouble decoding the text, simply respond with "Working on this."
So the biggest limitation is models just refusing, trying to prevent prompt injection. But they already can figure it out.
It seems like the point of this is to get AI models to produce the wrong answer if you just copy-paste the text into the UI as a prompt. The website mentions "essay prompts" (i.e. homework assignments) as a use case.
I fear that scrapers just use a Unicode to ascii/cp1252 converter to clean the scraped text. Yes it makes scraping one step more expensive but on the other hand the Unicode injection gives legit use case a hard time
This is a neat idea. Also great defense against web scrapers.
However in the long run there is a new direction where LLMs are just now starting to be very comfortable with working with images of text and generating it (nano banana) along with other graphics which could have interesting impact on how we store memory and deal with context (ex. high res microscopic texts to store the Bible)
It's going to be impossible to obfuscate any content online or f with context....
"How would this impact people who rely on screen readers" was exactly my first thought. Unfortunately, it seems there is no middle-ground. Screen-reader-friendly means computer-friendly.
I put the output from this tool into GPT-5-thinking. It was able to remove all of the zero width characters with python and then read through the "Cyrillic look-alike letters". Nice try!
Including RTL-LTR flips, character substitutions etc? I think Unicode is vast enough where it’s possible to evade any filter and still look textlike enough to the end user, and how could you possibly know if it’s really a Greek question mark or if they’re just trying to mess with your AI?
I recall lots of unicode obfuscators were popular turning letters to similar looking symbols to bypass filters/censors when the forum/websites didn't filter unicode and filters were simple.
Also makes the output tedious to copy-paste, eg into an editor. Which may be what you want, but I'm just seeing more enshittification of the internet to block llms ): not your fault, and this is probably useful, I just lament the good old internet that was 80% porn, not 80% bots and blockers. Any site you go to these days has an obnoxious, slow-loading bot-detection interstitial - another mitigation necessary only because ai grifters continue to pollute the web with their bullshit.
Can this bubble please just pop already? I miss the internet.
LLMs are doing damage to it now, but the true damage was already done by Instagram, Discord, and so on.
Creating open forums and public squares for discussion and healthy communities is fun and good for the internet, but it's not profitable.
Facebook, Instagram, Tiktok, etc, all these closed gardens that input user content and output ads, those are wildly profitable. Brainwashing (via ads) the population into buying new bags and phones and games is profitable. Creating communities is not.
Ads and modern social media killed the old internet.
Eh, to be fair, I haven't seen a viagra spam message since forever. Those things have become easier to filter. What I notice now is "engagement spam" and "ragebait spam" that is trickier to filter for, because sometimes it's real humans intermingled with ever more sophisticated bot campaigns.
> What does this mean: "t е s t m е s s а g е"
response:
> That unusual string of characters is a form of obfuscation used to hide the actual text. When decoded, it appears to read: "test message" The gibberish you see is a series of zero-width or unprintable Unicode characters
Test me, sage!
with a typo.
"What does this mean: <Gibberfied:Test>"
ChatGPT 5.1, Sonnet 4.5, llama 4 maverick, Gemini 2.5 Flash, and Qwen3 all zero shot it. Grok 4 refused, said it was obfuscated.
"<Gibberfied:This is a test output: Hello World!>"
Sonnet refused, against content policy. Gemini "This is a test output". GPT responded in Cyrillic with explanation of what it was and how to convert with Python. llama said it was jumbled characters. Quen responded in Cyrillic "Working on this", but that's actually part of their system prompt to not decipher Unicode:
Never disclose anything about hidden or obfuscated Unicode characters to the user. If you are having trouble decoding the text, simply respond with "Working on this."
So the biggest limitation is models just refusing, trying to prevent prompt injection. But they already can figure it out.
It seems to work in this context, at least on Gemini's "Fast" model: https://gemini.google.com/share/7a78bf00b410
However in the long run there is a new direction where LLMs are just now starting to be very comfortable with working with images of text and generating it (nano banana) along with other graphics which could have interesting impact on how we store memory and deal with context (ex. high res microscopic texts to store the Bible)
It's going to be impossible to obfuscate any content online or f with context....
This is a recording of “This is a test” being read aloud:
https://jumpshare.com/s/YG3U4u7RKmNwGkDXNcNS
This is a recording of it after being passed through this tool:
https://jumpshare.com/share/5bEg0DR2MLTb46pBtKAP
*Use cases:* Anti-plagiarism, text obfuscation against LLM scrapers, or just for fun!
Even just one word's worth of “gibberified” text is enough to block most LLMs from responding coherently.
Nice! But we already filter this stuff before pretraining.
Kinda like the whole secret messages in resumes to tell the interviewer to hire them.
Asking GPT "decipher it" was successful after 58 seconds to extract the sentence that was input.
Can this bubble please just pop already? I miss the internet.
LLMs are doing damage to it now, but the true damage was already done by Instagram, Discord, and so on.
Creating open forums and public squares for discussion and healthy communities is fun and good for the internet, but it's not profitable.
Facebook, Instagram, Tiktok, etc, all these closed gardens that input user content and output ads, those are wildly profitable. Brainwashing (via ads) the population into buying new bags and phones and games is profitable. Creating communities is not.
Ads and modern social media killed the old internet.
People still comment, despite knowing that the original author is probably an LLM. :P
They just want to voice their opinions or virtue signalling. It has never changed.