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AI can't read an investor deck AI as an attorney? Student uses ChatGPT, Gemini to sue UW over alleged racial discrimination Hacking MCP Servers in AI Systems – The Rug Pull: Tool Changes After Approval GitHub - MeepCastana/KubeezCut: Free Web based video editor GitHub - GenAI-Gurus/awesome-eu-ai-act: Curated tools, official sources, OSS, templates, and guides for EU AI Act compliance. Can AI judge journalism? A Thiel-backed startup says yes, even if it risks chilling whistleblowers Coming soon: 10 Things That Matter in AI Right Now DARPA built an AI to fact-check enemy weapons claims What explains heterogeneity in AI adoption? When AI Meets Muscle: Context-Aware Electrical Stimulation Promises a New Way to Guide Human Movements - Department of Computer Science AI Changed How We Build. It Did Not Change What Matters. Linux rules on using AI-generated code - Copilot is OK, but humans must take 'full responsibility for the… Meta spins up AI version of Mark Zuckerberg to engage with employees Code Mode: Let Your AI Write Programs, Not Just Call Tools | TanStack Blog GitHub - Delavalom/graft: Go framework for building AI agents. Type-safe tools, multi-provider (OpenAI, Anthropic, Gemini, Bedrock), zero vendor SDKs. India's TCS tops estimates, says new AI models did not dent services demand Gen Z's fading AI hype Strong feeling: we are in a folded AI reality GitHub - machinarii/total-recall-catalog: A reference catalog of latest knowledge retrieval, memory & RAG systems GitHub - mensfeld/code-on-incus: Give each AI agent its own isolated machine with root, Docker, and systemd. Active defense detects and stops threats automatically.. 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Open Letter on Transparent AI Cyber Protections
June 14, 2026 · 2026-06-16 · via Hacker News - Newest: "AI"

Dear Secretary Lutnick and National Cyber Director Cairncross,

We, the undersigned executives and technical leaders from across the United States and its allies, write to you to ask you to lift the export control directives on Anthropic’s Fable and Mythos large language models and commit to an open, scientific and transparent process of handling AI risk assessments in the future.

First, we would like to state that we believe that:

  • AI is having significant impacts on cybersecurity, including by greatly reducing the difficulty of finding flaws in software and writing exploits for those flaws.
  • Anthropic’s Mythos-class models are quite good at finding flaws and weaponizing exploits.
  • However, they are not uniquely good at these tasks, and many of the undersigned individuals regularly use other foundation and open-source models for security audits and red-teaming every day.
  • Anthropic has built multiple protections into the Fable model to prevent its use for cyber offensive uses. These protections were so aggressive as to be the source of humor in the cyber community on launch day.
  • It is essential to provide AI to coders and security teams so they can find and fix flaws in their own newly-written as well as decades of legacy code faster than our adversaries.
  • The Chinese open-weight models are only months behind the best American models, and those are the models we know about. It seems likely that the PRC government has access to private capabilities beyond what has been published.
  • To pull the best capabilities away from defenders without a good reason when our adversaries are rapidly advancing is dangerous.

It is our understanding that underlying model capabilities in the original research that triggered this action:

  • Were focused on determining whether a human-prompted section of code was insecure. This is a necessary capability in any model that is intended to write secure code and should not be considered an offensive capability.
  • Can be replicated on GPT-5.5, Opus, Sonnet and even Chinese models like Kimi 2.7. The justification for this unprecedented action was that Fable provides a unique “uplift” of capabilities beyond other AI models, but AI has been finding bugs and generating working exploits at superhuman levels since last year.
  • Anthropic is addressing the research. As security professionals, we recognize that our work does not lead to a simple end-state where a system is fully safe, and the purpose of research like this is to enable continuous improvement, not to ban the technology.

As a result, this action has taken the best models away from defenders, created market uncertainty, and risked America’s AI leadership without any real risk to justify it.

Not all of us agree that AI regulation is the right way forward. But if this Administration’s laudable goal of securing our nation’s critical infrastructure is going to include models being regulated, then the regulations should be:

  1. Grounded in scientific evaluations developed with input from industry and academia;
  2. Created through a democratic rule-making process;
  3. Enforced transparently and fairly with appropriate time given to remediate; and
  4. Used only to the minimal extent necessary to ensure the safety of the American public.

Thank you for your consideration and partnership in helping us maintain America’s lead in technology while protecting critical software and systems.

Signed,

Affiliations are included for reference only and do not indicate organizational endorsement.