The Claude Code Source Leak: fake tools, frustration regexes, undercover mode (alex000kim.com)
Related ongoing thread: Claude Code's source code has been leaked via a map file in their NPM registry - https://news.ycombinator.com/item?id=47584540
Also related: https://www.ccleaks.com
117 comments
[ 3.1 ms ] story [ 86.8 ms ] threadInteresting based on the other news that is out.
I don’t get it. What does this mean? I can use Claude code now without anyone knowing it is Claude code.
On that note, this article is also pretty obviously AI-generated and it's unfortunate the author didn't clean it up.
So much for langchain and langraph!! I mean if Anthropic themselves arent using it and using a prompt then what’s the big deal about langchain
Edit: Everyone is responding "comments are good" and I can't tell if any of you actually read TFA or not
> “BQ 2026-03-10: 1,279 sessions had 50+ consecutive failures (up to 3,272) in a single session, wasting ~250K API calls/day globally.”
This is just revealing operational details the agent doesn't need to know to set `MAX_CONSECUTIVE_AUTOCOMPACT_FAILURES = 3`
[0]: https://github.com/chatgptprojects/claude-code/blob/642c7f94...
They would either need to lie about consuming the tokens at one point to use in another so the token counting was precise.
But that does not make sense because if someone counted the tokens by capturing the session it would certainly not match what was charged.
Unless they would charge for the fake tools anyway so you never know they were there
Plot twist: Chinese competitors end up developing real, useful versions of Claude's fake tools.
How much approximate savings would this actually be?
Does this mean `huggingface.co/Jackrong/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled` is unusable? Had anyone seen fake tool calls working with this model?
I’d argue that in this case, it isn’t. Exhibit 1 (from the earlier thread): https://github.com/anthropics/claude-code/issues/22284. The user reports that this caused their account to be banned: https://news.ycombinator.com/item?id=47588970
Maybe it would be okay as a first filtering step, before doing actual sentiment analysis on the matches. That would at least eliminate obvious false positives (but of course still do nothing about false negatives).
>Is it ironic? Sure. Is it also probably faster and cheaper than running an LLM inference just to figure out if a user is swearing at the tool? Also yes. Sometimes a regex is the right tool.
I'm reading an LLM written write up on an LLM tool that just summarizes HN comments.
I'm so tired man, what the hell are we doing here.
> This was one of the first things people noticed in the HN thread.
> The obvious concern, raised repeatedly in the HN thread
> This was the most-discussed finding in the HN thread.
> Several people in the HN thread flagged this
> Some in the HN thread downplayed the leak
when the original HN post is already at the top of the front page...why do we need a separate blogpost that just summarizes the comments?
The pet you get is generated based off your account UUID, but the algorithm is right there in the source, and it's deterministic, so you can check ahead of time. Threw together a little app to help, not to brag but I got a legendary ghost https://claudebuddychecker.netlify.app/
The more code gets generated by AI, won’t that mean taking source code from a company becomes legal? Isn’t it true that works created with generative AI can’t be copyrighted?
I wonder if large companies have throught of this risk. Once a company’s product source code reaches a certain percentage of AI generation it no longer has copyright. Any employee with access can just take it and sell it to someone else, legally, right?