Last week, Anthropic introduced a new system prompt designed to stop its Claude models from re-creating specific, existing video games. While that move could help shield Anthropic from some liability, it's unlikely to slow much of the massive wave of AI-assisted game porting and copying that has emerged in recent months.

A social media user and AI decompilation enthusiast going by the name "chasm" was among the first to note the prompt change late last week, saying a new rule seemed to be added to the Claude Code prompt on or around October 27. That rule—included in a json file under the name "tengu_heron_brook"—reads as follows:

Do build original games, games in a genre, and games from the user’s own designs and assets. Don’t build a recreation of a specific existing game, even if it is renamed or called original.

XDA later independently verified that the new rule appears in version 2.1.314 of the Claude Code binary, which was released on October 30. XDA also reported that the "tengu_heron_brook" rule had been used for other purposes in earlier versions and that the Claude Opus 5.5 model specifically seemed to have its own distinct and independent instructions restricting game recreations as part of its system prompt bundle.

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An official extension for Anthropic’s Claude model was backdoored and threatened as many as 5,000 developers' machines, multiple sources reported Friday. Anthropic so far has yet to warn customers of the incident.

The compromised package was a VS Code extension available in the marketplace of Cursor, a maker of AI-assisted developer tools, the company said Friday. The malicious version, 2.1.313, subsequently affected “at most 5,000 users,” presumably when they either downloaded it or their systems automatically fetched and installed it. Anthropic pushed version 2.1.314 several hours after the previous version became available on Cursor, according to independent researcher Kevin Beaumont. Both Beaumont and the CTO and co-founder of security firm Phorion said that version 2.1.313 was distributed through Anthropic’s official account on Cursor. So far, neither Cursor nor Anthropic has explained how the attackers gained control of the account.

In search of cloud credentials

“It was a supply-chain compromise where the attacker gained access to the official distribution channel,” Phorion CTO and co-founder Luke Roberts told Ars. “The malicious version 2.1.313 was posted to the official Anthropic account, effectively superseding 2.1.312. Extensions auto-update in Cursor by default, but users can configure this in settings.” Phorion has more details here.

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The Securities and Exchange Commission's publication on Monday of Anthropic's S-1 form—ahead of a heavily anticipated initial public offering—has led to plenty of discussion of whether the company's quickly ballooning revenues will be able to overcome its even higher costs. But amid the numbers and forward-looking optimism about AI "rapidly transform[ing] every sector of the global economy in ways greater than the impact of industrialization, electricity, semiconductors, and the internet," Anthropic also spends an inordinate amount of time in its S-1 laying out the myriad risk factors that could bring the company down.

Across 93 pages and over 70,000 words, Anthropic's S-1 "Risk Factors" section discusses literally hundreds of potential problems that could negatively impact its business in the coming years. Many of these potential risks are the kind of standard worries about competition, costs, customer acquisition, and potential regulation that almost any business must worry about. But some risks highlight interesting potential points of failure for Anthropic specifically and the hype-filled AI bubble more generally.

After wading through Anthropic's book-length treatise on its greatest risks, we've narrowed the list to the seven most surprising, interesting, or thought-provoking potential problems. Consider this a far-from-comprehensive look at what potential Anthropic investors should keep in mind.

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Anthropic has granted external evaluators “employee-like access” to assess the risks of its models, following through on a commitment to increase safeguards over concerns the technology could run catastrophically out of control.

METR, a nonprofit that has worked with leading labs including OpenAI, Anthropic, Google, and Meta, now has a team embedded in the Claude maker’s office with access to its hardware and internal systems.

A greater role for third-party evaluators is among the main concrete steps the labs have proposed in response to rising concern about the dangers more capable AI systems could pose to the economy, cyber security, and humanity at large.

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