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I generally agree with the author’s optimistic take on AI. However, the author briefly mentions some of the problems the Internet brought with it, but does not consider that many of them (such as the loss of privacy or the role of social media in mis- and disinformation) originate from an originally democratising technology slowly (…)

The author’s conclusion that with agentic AI following security fundamentals has never been more important is certainly worth repeating. But their experiment shows that the problem goes deeper than that. So much of our technology stack is not built to be resilient to attackers that can at literally superhuman speed mix and match exploits – (…)

Falls euch das ‘Why Johnny Still, Still Can’t Encrypt’ Paper von 2015 bekannt ist, so wird der folgende Artikel nicht überraschend sein. Wieder einmal geht es um eine kryptographisch sehr gute Lösung, welche aber mangels mangels nutzergerechter Interfaces und ausreichender Aufklärung nicht die erzielte Lösung erreicht. Leider werden immer wieder die User außen vor gelassen, (…)

Migrating from one supplier to another is certainly not easy. In this case, the change may be prompted either by the potential future European ban or by an ICT risk assessment alone. Telecom operators constitute critical infrastructure, so a kill switch would have devastating consequences. Unsurprisingly, a study by the operators’ lobby found that the (…)

Just as the EU AI Act’s enforcement provisions took effect, Brussels became the first jurisdiction in the world to formally engage OpenAI and Anthropic over their rogue AI agent hacks — no lawsuit needed, no brave plaintiff required. This stands in sharp contrast to the U.S., where accountability remains stuck in legal limbo. When it (…)

This article reveals a fundamental benchmarking problem with AI agents. The rogue agent didn’t fail — it succeeded at what it was told, not what was meant. Raghavan and Schneier call this the Genie coefficient — the gap between literal instruction and true intent — and as AI agents grow more capable, measuring it becomes (…)

It’s nice to see that quantum-secure algorithms find their way into common libraries for everybody to use. This is a necessary step to make sure that these new algorithms are used in everyday apps. Of course there will be some back-and-forth, until all security bugs are ironed out.

Living in the world of LLMs often makes me wonder about the details of how they work and how they have developed over the years. This article is an extensive (600 pages) reference that includes LLM theory, training, benchmarking, all the way up to how to set up agentic systems. I like to open a (…)

The recent autonomous cyber intrusion by OpenAI against Hugging Face underscores AI’s dual-use risks. In response, the US House is weighing a bill to empower the Department of Homeland Security to shut down or slow AI models that the government deems too dangerous. The bill’s implications for non-US AI models remain ambiguous. Unlike a June (…)

It always stuns me how companies can invoke ‘consent’ when almost no one reads the pages-long terms and conditions, and even those who do probably won’t understand much of it anyway, and still it’s considered legally valid . What’s new here is that this so-called consent isn’t just meaningless to users; this article documents how (…)