Penclaw.ai hire OpenClaw tenant for pentesting

Hacker News

This idea flashed to me when someone wanted to hire me as a pentester by falsely thinking that I was an expert at pentesting on Reddit. Then I revealed to him that I am not a pentester, my AI is. Previously, I shared an ablated closed-source LLM on Show HN. https://pingu.audn.ai/ Penclaw is basically OpenClaw + the best abliterated model + unlimited tokens ( you share a 1 GPU VM H100 locally with 40 tenants ) It also affors a filesystem UI, Cursor like edit options, console access, one-click MCP deploy and connect, MCP marketplace that lists new pentesting and red teaming MCPs (MCPs that has objectionable actions that Claude or OpenAI models refuse) constantly. This is an experiment to share 1 GPU VMs rather than buying mac studios for openclaw. Feel free to give feedback obviously that's why I share it here.

Visit product View on Hacker NewsFeb 25, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, cursor, claude · Missing: agents, macos, agent

96%96% 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 · Strong signals: ios · Missing: supports, reddit linkedin, podcasting

68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: ios · Missing: mobile apps, personal, entrepreneurs

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

36%36% 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

24%24% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

23%23% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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