Fi
File carver in the browser (Rust and WebAssembly)
Hacker NewsFile carver in the browser (Rust and WebAssembly)
An experimental file carver [1], currently extracting only JPGs, written in Rust and compiled to WebAssembly. Files that the user provides are searched inside the browser, there's no server upload. The extraction of JPGs works using their magic numbers. I'd love to get ideas on possibly more sophisticated extraction methods and the Rust code in general. [1]: https://en.wikipedia.org/wiki/File_carving
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2points
Did not reach leaderboard
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: user, using, code · Missing: mac, agents, macos61%61% 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 released61%61% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive33%33% 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, revenue16%16% 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, crypto11%11% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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