Pryingdeep – New dark web OSINT tool

Hacker News

Pryingdeep is an OSINT dark web tool that aims to extract intelligence specifically from the dark web. However you can also use it to crawl clearnet websites if you wish. Quick overview of the current features: - Email Search - Wordpress Search - PGP keys and Certificate Search - 3 different cryptowallets (XMR, BTC, ETH) - Built in exproter (JSON) with features like built in criteria (e.g LIKE keyword) offset, limit, and etc - Install command - Tor docker container and docker-compose for the whole project - Highly customizable crawler as it is based of the goColly framework(e.g multiple urls as an entrypoint, maxdepth, etc) That is currently it. I want to say that, the tool is not perfect, but i want to find some community members who will actually find the tool useful and get some feedback on what should be improved, so I really hope that by posting it here, somebody out there might find this project useful. Thank you guys, if anybody reads this.

Visit product View on Hacker NewsDec 5, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: dock, new, email · Missing: mac, agents, macos

71%71% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

62%62% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

55%55% 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

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released

32%32% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: crypto · Missing: web3, chat, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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