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First-token-only flaw in Claude Code permissions (triage bot too)

Hacker News

First-token-only flaw in Claude Code permissions (triage bot too)

I filed GH issues, and PR fixed on claude-code. I submitted a report on Hackerone, but the triage bot has the SAME category error problem. I got dismissed as "informatiional" because your bot saw my 'rm -rf' example, and dismissed it as an OS problem. But that is exactly wrong. Allow and deny lists allow DANGEROUS actions like "git cleanup" Some human needs to read this HN post and my blog post. I've written a bash-guard fix that I use locally, but I CAN'T help everyone else until Anthropic takes my bug report seriously https://github.com/anthropics/claude-code/issues/36637 https://github.com/anthropics/claude-code/pull/36645

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Actual performance

3points
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: claude, code · Missing: mac, agents, macos
80%80% 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.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
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.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
30%30% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
18%18% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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