Great project! I'm looking for something like this but for code: an app that runs locally and obfuscates variables & strings into generic things, so you don't leak code/db structure to LLM companies. Couldn't find anything though so I'm using an LLM to write one.
Interesting.<p>1. Suggestion: Personally I love when projects mention whether they’ve found other existing software that does something similar, and if so how this app compares.<p>2. On iOS when I click into the project it opens into the GitHub iOS app but there’s a big empty box below the big logo. Clicking the box opens the video in my browser. Maybe it’s a GitHub app issue? I didn’t spend any time further on that.<p>3. Minor but I couldn’t be sure what pisi stands for - the page seems to use “personal and sensitive information” (PASI?) but maybe it stands for “personal information sensitive information” even if the page doesn’t use that phrase?
Hey, thanks for the feedback!<p>1. Correct. Honestly I haven't found any (I'd use it if I did). After release I was told enterprises have smth similar under the category Data Loss Prevention (DLP).<p>2. It's on me the logo is huge, I made it smaller. Video display is better on browser (not desktop app). If you scroll past the big box (the video) you can find the rest of the documentation.<p>3. Spot on, I added the full name to README and made the logo smaller. The name btw is "Personally Identifiable & Sensitive Information Guard"
I don't understand this, what's the point?<p>How does anyone <i>accidentally</i> give personal information to an LLM? Because either you don't in the first place (eh, I guess, most people?) or you do but for some specific, weird reason (I can't think of any but I guess these exist).
It could be useful more as a labor saving device to enable censoring while allowing the human to engage in easy copy-paste. Examples I think of are inclusion of internal DNS names, usernames and human names and email addresses that may be intermixed with log or command output needed to debug some issue.<p>That said, if these strings are really sensitive and I'm too lazy (or not trusting the human user) to self-censor, I'd not rely on this particular kind of tool for censoring. I'd use local LLMs or cloud LLMs where privacy is part of the contract.
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