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Anthropic Source Code Leaked For Second Time In A Week: Here's What It Means

Anthropic accidentally leaked 500,000 lines of proprietary Claude Code. Developers have already rewritten the exposed codebase to bypass copyright claims.

Anthropic Source Code Leaked For Second Time In A Week: Here's What It Means

Artificial intelligence startup Anthropic is facing a localised crisis yet again, after accidentally leaking the source code for its Claude Code platform, for the second time in a single week.

The security lapse took place on Tuesday during a software update when a debugging file containing over 5 lakh lines of proprietary code was bundled into the update. The error was first identified by a security researcher, Chaofan Shou, who shared the discovery on X. 

Within hours, the post reached 21 million views, leading to a massive surge in unauthorised downloads and mirrors across GitHub.

The incident has sparked a high-stakes digital pursuit as Anthropic's legal team issued a barrage of DMCA takedown notices. However, the leak took a turn when Sigrid Jin, a prominent developer and top user of Claude's API, reportedly rewrote the entire codebase in Python from scratch. Jin's version, titled “claw-code,” reached 30,000 stars on GitHub in record time.

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What's Next For Anthropic?

Because a total rewrite constitutes a new creative work, industry experts suggest it may bypass standard copyright takedown efforts.

The timing of the leak is particularly damaging for the San Francisco-based firm. This marks the second time in a seven-day window that Anthropic has inadvertently exposed internal intellectual property.

The repeated failures come despite the company's implementation of “Undercover Mode,” a system specifically designed to prevent Claude from disclosing sensitive internal secrets.

While Anthropic has attempted to scrub the code from centralised repositories, mirrors have already moved to decentralised platforms, rendering the leak effectively permanent.

Anthropic has not yet commented on the status of its internal investigation or potential disciplinary actions regarding the deployment error. 

ALSO READ: AI Ambitions At Risk? Only 14% Enterprises Have Peak Cloud Maturity: Study

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