PD

PDFs that are readable by human eyes only

Hacker News

PDFs that are readable by human eyes only

Hi, OP here. A friend was involved in a custody battle and was afraid his ex was going to leak all of his discovery documents on the internet and he asked if there was something I could do to make it harder for bots/crawlers to find sensitive information. Originally I was going to turn all of his docs to image based PDFs, but those get large fast and are easy to OCR. So I found a post musing about altering fonts/glyphs so that it looks like english, but the actual character being seen by the pdf reader is a non-english character. As such, when you try to OCR these files, it doesn't see any images and can't convert it. I figured it had some potential uses and maybe you fine folks can identify other use cases. I'll be monitoring this post most of the day.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
92%92% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
65%65% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: using · Missing: mac, agents, macos
56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

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