AI security tool Fable disables its services for all users following US export control restrictions

I was using Fable to improve security for my apps and when it suddenly stopped working. It's only on twitter that I found out that it has been stopped for people who are not US nationals, by the US government. Here's how I'm seeing this:

1. Fable comes with security safeguards to prevent misuse, and can be used to plug security loopholes. I've seen it identify and plug security issues in my apps. The US government refusing to let non-US nationals protect themselves is deeply problematic in an interconnected internet world, especially when these issues will impact US customers of foreign apps and websites. It doesn't make sense. This hurts everyone by making all systems vulnerable.

2. Yesterday Anthropic announced a partnership with TCS in India as a commercial deal. Today Fable is banned for Indians. During the AI summit they had announced a partnership with Infosys. The fact is that these are just commercial deals but the Indian companies have no strategic leverage here. Both companies run critical systems in India: Infosys runs finnacle. TCS runs passport sewa etc, all with critical personal data at stake. They had zero access to Project Glasswing when it launched to secure systems with Mythos, while some US companies got access. This proves that for Anthropic, Indian partnerships are just about the money. To call such partnerships strategic is hogwash. I think Anthropics leadership and policy teams in India have much to answer for. I would request @nishikant_dubey to take up this bipartisan issue up in the standing committee on IT since MEITY is quite toothless.

3. We've seen this story play out before: in President Trump's last term, the US govt momentarily stopped Android security updates for China. Today China has its own Huawei OS. Where is IndusOS? We need to adopt open source tech because geopolitics is increasingly win-lose, and the win-win era is behind us. It's sad but this is where we are today. We need to invest in research, and building a culture that supports research. The Atal Tinkering Labs are a great starting point and we need to build on this, at a university level. Allow universities to monetize research and professors and students to start companies with university support. Let professors consult. Build a marketplace that rewards innovation and expertise.

4. CERT-IN, RBI and other agencies holding meetings regarding mythos was farcical. Its proof that our cybersecurity agencies are out of their depth, and doing a checkbox exercise to show the PM that they're doing something when they can't, because this is about Zero Day vulnerabilities, not predictable cybersecurity issues. We need a cybersecurity strategy overhaul. Basically fire bureaucratic-mindset people doing farcical compliance at CERT-IN and get technocrats with actual cybersecurity understanding. Hire for competence, not loyalty. Hire for competence not badges (definitely not the clueless famous IIT professor we know who does committe hopping).

5. Time to start ignoring Nandan Nilekani's ignorant comments on what India should do in AI. We need to focus on hardware, start working on small language models and get people who know AI to drive policy. As history has shown us, Vishal Sikka was right, Narayan Murthy and Nandan Nilekani were not. We have a long way to go. The AI Summit was great for increasing diffusion, and we need more of that, but not just that. The IndiaAI mission needs to speed up and become a mission critical project.

Cc @narendramodi. Hire better people please. Choose open source. Build a long term strategy.

The points you have mentioned are quite accurate and certainly what needs to be done. However, we need to be very aware that these dangers were already evident when ChatGPT was just launched and Sam Altman came to India. Yet, we haven't done anything major since.

All we could think about then, and even now, is how to build software solutions on top of the core inteligence models available to us via APIs. At the end of the day, everything you mentioned requires deep pockets and a readiness to take risks, which after having done some fund-raising attempts I know we severly lack.

While we have built some brilliant apps on top of the intelligence provided by these models, we haven't done much else.

And even if we overlook the fact that we are already super late to the party, we have to realize that we do not have the talent density in India to perform that level of research and build something even close to the open-source models already available. (blame brain drain)

There is very little reason to think we will start now, especially when we are heavily lacking in 3/5 layers of AI: - Intelligence models (severly lacking) - Data Centers (initial phases) - Chipsets (no major step) - Electricity Demands (okay-ish) - Software Layer (great)

This is simply the truth of where we are as of right now in 2026.