Stateless, system-wide Transparent Tor Proxy for Linux (v0.1.0)

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Hi, I made this transparent proxy because I wanted to make a tool that felt easy to use. You just have to turn it on and forget it, and as soon as you turn it off your computer will go back to the previous state. In a few words, TTP intercepts all TCP traffic and DNS queries (using nftables) and redirects them to respectively Tor's TransPort and DNSPort. When turned off, it destroys its dedicated table atomically, without breaking your network configuration on your machine. It also implements a kill-switch for connections established before TTP starts (outgoing traffic is rejected, doing so the connection gets automatically re-estrablished using the secure connection). In the end, it offers SELinux custom policies and it is crash safe (using a lock file in /var/lib/ttp). Disclaimer: this tool is not meant for high-risk activities. I DO NOT recommend it for further purpose rather than privacy and/or for testing/developing it. Finally, this is just a v0.1.0 by an undergraduate cs student. I made this to learn, so, please, help me out! Thank you all. Github link: https://github.com/onyks-os/TransparentTorProxy Documentation: https://onyks-os.github.io/ttp/

Visit product View on Hacker NewsApr 29, 2026

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77%77% 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: mac, computer, using · Missing: agents, macos, agent

54%54% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

47%47% 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: soon · Missing: plus, platform, intuitive

44%44% 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

38%38% 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

11%11% 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.

Correct prediction on native model

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