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Pākiki Proxy – An intercepting proxy for penetration testing

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Pākiki Proxy – An intercepting proxy for penetration testing

Hey HN, I've been working on an intercepting proxy for penetration testing over the last few years in my spare time. Some points of difference from the existing tools: * The UIs are built using the native platform frameworks, meaning they look and behave like other applications on the desktop. * It has a fully embedded and integrated Python scripting engine. * It’s fully native meaning it’s nicer on system resources. * It has a number of built in scripts to automate reconnaissance, content discovery, authorisation checks, etc. * The core of it is open source. I'm really keen to get any feedback!

Visit productView on Hacker NewsOct 27, 2023
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: using, open · Missing: mac, agents, macos
87%87% 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
66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, open source, existing · Missing: https docs, excited, just released
62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
42%42% 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
20%20% 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.

Correct prediction on native model

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