Bu

Built a Botnet Using Node JavaScript

Hacker News

Built a Botnet Using Node JavaScript

Hello HN. So about half a year ago, I started taking programming more seriously, and I've decided to learn Node JS and work on some projects to sharpen my skills. I found such a topic (Botnets and C&C) very interesting, and I decided to make my own one. It is nothing that impressive; it currently cannot perform any kind of DDOS attack, which is kind of the main reason Botnets exist, but regardless, I am fairly happy with it. The reason I am posting about it here is that I have been finding it very hard to find somebody to criticize it or to give me some feedback, as I am concerned about the quality of the code and if I am even doing things correctly here. So, let me know what you guys think.

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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
84%84% 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: using, code · Missing: mac, agents, macos
73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, ide, io · Missing: https docs, excited, just released
69%69% 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 · Missing: plus, platform, intuitive
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
30%30% 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
17%17% 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.

Incorrect prediction on native model

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