Since many company intranets are sent in plaintext, traffic from them can also
be intercepted.

    Even when HTTPS is in place, an attacker can still intercept domain look-up
traffic and use DNS cache poisoning to corrupt tables stored by the target?s
operating system. The AirSnitch MitM also puts the attacker in the position to
wage attacks against vulnerabilities that may not be patched. Attackers can also
see the external IP addresses hosting webpages being visited and often correlate
them with the precise URL.

Here?s the paper.

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Jailbreaking the F-35 Fighter Jet

[2026.03.10] Countries around the world are becoming increasingly concerned
about their dependencies on the US. If you?ve purchase US-made F-35 fighter
jets, you are dependent on the US for software maintenance.

The Dutch Defense Secretary recently said that he could jailbreak the planes to
accept third-party software.

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Canada Needs Nationalized, Public AI

[2026.03.11] Canada has a choice to make about its artificial intelligence
future. The Carney administration is investing $2-billion over five years in its
Sovereign AI Compute Strategy. Will any value generated by ?sovereign AI? be
captured in Canada, making a difference in the lives of Canadians, or is this
just a passthrough to investment in American Big Tech?

Forcing the question is OpenAI, the company behind ChatGPT, which has been
pushing an ?OpenAI for Countries? initiative. It is not the only one eyeing its
share of the $2-billion, but it appears to be the most aggressive. OpenAI?s top
lobbyist in the region has met with Ottawa officials, including Artificial
Intelligence Minister Evan Solomon.

All the while, OpenAI was less than open. The company had flagged the Tumbler
Ridge, B.C., shooter?s ChatGPT interactions, which included gun-violence chats.
Employees wanted to alert law enforcement but were rebuffed. Maybe there is a
discussion to be had about users? privacy. But even after the shooting, the
OpenAI representative who met with the B.C. government said nothing.

When tech billionaires and corporations steer AI development, the resultant AI
reflects their interests rather than those of the general public or ordinary
consumers. Only after the meeting with the B.C. government did OpenAI alert law
enforcement. Had it not been for the Wall Street Journal?s reporting, the public
would not have known about this at all.

Moreover, OpenAI for Countries is explicitly described by the company as an
initiative ?in co-ordination with the U.S. government.? And it?s not just
OpenAI: all the AI giants are for-profit American companies, operating in their
private interests, and subject to United States law and increasingly bowing to
U.S. President Donald Trump. Moving data centres into Canada under a proposal
like OpenAI?s doesn?t change that. The current geopolitical reality means Canada
should not be dependent on U.S. tech firms for essential services such as cloud
computing and AI.

While there are Canadian AI companies, they remain for-profit enterprises, their
interests not necessarily aligned with our collective good. The only real
alternative is to be bold and invest in a wholly Canadian public AI: an AI model
built and funded by Canada for Canadians, as public infrastructure. This would
give Canadians access to the myriad of benefits from AI without having to depend
on the U.S. or other countries. It would mean Canadian universities and public
agencies building and operating AI models optimized not for global scale and
corporate profit, but for practical use by Canadians.

Imagine AI embedded into health care, triaging radiology scans, flagging early
cancer risks and assisting doctors with paperwork. Imagine an AI tutor trained
on provincial curriculums, giving personalized coaching. Imagine systems that
analyze job vacancies and sectoral and wage trends, then automatically match job
seekers to government programs. Imagine using AI to optimize transit schedules,
energy grids and zoning analysis. Imagine court processes, corporate decisions
and customer service all sped up by AI.

We are already on our way to having AI become an inextricable part of society.
To ensure stability and prosperity for this country, Canadian users and
developers must be able to turn to AI models built, controlled, and operated
publicly in Canada instead of building on corporate platforms, American or
otherwise.

Switzerland has shown this to be possible. With funding from the federal
government, a consortium of academic institutions -- ETH Zurich, EPFL, and the
Swiss National Supercomputing Centre -- released the world?s most powerful and
fully realized public AI model, Apertus, last September. Apertus leveraged
renewable hydropower and existing Swiss scientific computing infrastructure. It
also used no illegally pirated copyrighted material or poorly paid labour
extracted from the Global South during training. The model?s performance stands
at roughly a year or two behind the major corporate offerings, but that is more
than adequate for the vast majority of applications. And it?s free for anyone to
use and build on.

The significance of Apertus is more than technical. It demonstrates an
alternative ownership structure for AI technology, one that allocates both
decision-making authority and value to national public institutions rather than
foreign corporations. This vision represents precisely the paradigm shift Canada
should embrace: AI as public infrastructure, like systems for transportation,
water, or electricity, rather than private commodity.

Apertus also demonstrates a far more sustainable economic framework for AI.
Switzerland spent a tiny fraction of the billions of dollars that corporate AI
labs invest annually, demonstrating that the frequent training runs with
astronomical price tags pursued by tech companies are not actually necessary for
practical AI development. They focused on making something broadly useful rather
than bleeding edge -- trying dubiously to create ?superintelligence,? as with
Silicon Valley -- so they created a smaller model at much lower cost. Apertus?s
training was at a scale (70 billion parameters) perhaps two orders of magnitude
lower than the largest Big Tech offerings.

An ecosystem is now being developed on top of Apertus, using the model as a
public good to power chatbots for free consumer use and to provide a development
platform for companies prioritizing responsible AI use, and rigorous compliance
with laws like the EU AI Act. Instead of routing queries from those users to Big
Tech infrastructure, Apertus is deployed to data centres across national AI and
computing initiatives of Switzerland, Australia, Germany, and Singapore and
other partners.

The case for public AI rests on both democratic principles and practical
benefits. Public AI systems can incorporate mechanisms for genuine public input
and democratic oversight on critical ethical questions: how to handle
copyrighted works in training data, how to mitigate bias, how to distribute
access whe
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