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Enterprise – Silicon Republic

Recovery readiness a missing link in cyber resilience, finds report EU finally gets its hands on Anthropic’s Mythos New Irish dispute body to tackle illegal online content launched Rhysida leaks 5.7TB of sensitive Berlin state data in major hack ‘Keeping OT security up to date is more than patching systems’ HSE fined €645,000 for storing records in decrepit conditions Boston Scientific cyberattack: Cork staff asked to work remotely Report: Only sectors aiding AI adoption sure to grow from it Why connectivity and cybersecurity can't be treated separately French authorities investigating hack of national tax authority Why employee retention is at the heart of the cyber skills gap Levi Strauss corporate data stolen in cyberattack Levi Strauss corporate data stolen in cyberattack How might a system ‘leak secrets’ without being hacked? What is a side-channel attack in cybersecurity? OpenAI agents breach Modal client system after Hugging Face hack OpenAI agents breach Modal client system after Hugging Face hack Report: EMEA businesses not reaping benefits from their AI spend Report: EMEA businesses not reaping benefits from their AI spend Transport for London hackers jailed for five and a half years Transport for London hackers jailed for five and a half years Commission refers Ireland to CJEU for failing to enact cyber rules Commission refers Ireland to CJEU for failing to enact cyber rules Cloudflare to block AI crawlers from ad-supported webpages by default Cloudflare to block AI crawlers from ad-supported webpages by default Google ordered to pay Klarna nearly $2bn in abuse-of-power row Google ordered to pay Klarna nearly $2bn in abuse-of-power row Upcoming iPhone 18 model leaked in Tata Electronics hack New iPhone 18 models reportedly leaked in Tata Electronics hack Data breaches going unreported – Irish compliance survey
Anthropic to reassess Claude Fable 5 AI development restr...
Laura Varley · 2026-06-11 · via Enterprise – Silicon Republic

Anthropic’s AI restrictions caused concern among founders, researchers and developers following the release of the Mythos-like model.

It was just this week that Anthropic launched Claude Fable 5, an AI model that the company described as “Mythos-class”, but with additional significant security restrictions in place to prevent misuse. 

Already, however, the organisation is facing backlash from founders, researchers and developers who find the ‘secretive’ large language model (LLM) policies to be deliberately limiting competitors and users in the development of alternative AI models. 

In its statement announcing the availability of Claude Fable 5, Anthropic explained that the model has barriers designed to block responses that stray into high-risk areas – notably cybersecurity, chemistry and biology. Such interactions, it stated, would instead be rerouted to Opus 4.8, a less powerful model.

This has reportedly drawn some criticism from researchers and developers in the AI space, as there is a concern that work derived this way is deliberately degraded in a manner that is invisible and secretive. 

Anthropic has since responded to the backlash, indicating plans to address the issue by making Claude 5’s safety rails visible to all users. If the company suspects that a user is attempting to develop their own high-powered AI system, it will send a clear prompt informing them that the request is being refused based on policy, or that it is being rerouted to a less capable model. 

It is currently against Anthropic’s terms of service to use Claude technology as a means of training competing AI models. 

In a statement to Wired, a representative for Anthropic said, “We’re changing Fable 5’s safeguards for frontier LLM development to make them visible. We made the wrong trade-off and we apologise for not getting the balance right.”

Among the critics of Anthropic’s decision-making was Dean Ball, a senior fellow at the Foundation for American Innovation and a former adviser to the White House on AI. In a post published on X, Ball described deliberately degrading “ML research” performance without informing the user as a “shockingly hostile and terrible look”. 

He further explained its potential to “silently damage all sorts of work” and “raise the eyebrows of antitrust enforcers worldwide.”

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