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Glyph DLP – a data loss prevention API

Hacker News

Glyph DLP – a data loss prevention API

Hi HN, Glyph DLP is an API that scans or redacts sensitive information (emails, SSNs, credit cards, etc.) from Base64-encoded files/strings. So far I have coverage for text files, JSON, PDF, CSV, DOCX, and XLSX files and may consider adding a few more in the future. I made this app mostly for fun and learning and to scratch the creative itch over the past few months. I am using FastAPI in Docker hosting it on Fly.io. I originally wanted to use SQLite/LiteFS on Fly but ran into some issues with concurrent writers when keeping track of rate-limiting on the API. I am now using managed MySQL on Planetscale which has been awesome and would definitely recommend both Fly and Planetscale to anyone making small hobby projects. Even though the API functions are relatively simple, this is definitely the hardest I have worked on an app. I put a lot more effort into design and getting things how I want them, learning how to write better tests, documenting the API, etc. I also want to mention that Glyph DLP does not store any content from files as they are scanned/redacted or use the information from uploaded content in any way. I have no users to speak of at the moment and appreciate any feedback!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
83%83% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: user, dock, email · Missing: mac, agents, macos
70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: month, users, way · Missing: mobile apps, ios, personal
54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: host, users · Missing: plus, platform, intuitive
41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
18%18% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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