Systems that no one will test

Relevant: https://www.reddit.com/r/YouShouldKnow/comments/1wssf4u/ysk_... https://imgur.com/a/6FaQQhb (original post before being taken down by mods) >The Work Number is an Equifax (who famously had a massive data breach a few years back) owned database with employment and pay information. >You can create a login on theworknumber .com and pull your report. Mine is seventy four pages and had info from every company I've worked at in the last 13 years including every paycheck I had received with the exact dollar amount (both net and gross) and hours worked. It has employment start/end dates, termination reason, details about withholdings, benefit enrollment, union affiliation, etc etc etc. >This data is sourced directly from the HR platform your employees use (ADP, Rippling, Gusto, iSolved, etc). Equifax sells your data for things like employment background checks. >You cannot have your data removed from The Work Number. You can freeze your report (much like a credit report) but if a potential employer cannot access your frozen report that may disqualify you. >Why YSK: If you're interviewing for a job you can be at a significant disadvantage especially for things like salary negotiations because they can literally see how much you make including your most recent paycheck. Creditors also can access these reports. >This is the biggest privacy violation I have ever seen and almost nobody is even aware of it. Certainly none of us consented to having our employment and income data harvested and sold, especially since we get nothing in return. At a minimum, people should know about how this data can impact you. >Edit: The Work Number is primarily for the US, but there are similar services for other countries.

Every since the OPM hack of 2015, I've been apparent to me that my former field of IT administration has lost the plot. Nobody knows what a data diode is, or why you would use one. Systems that should clearly be air-gapped aren't. While it's easy to lay this at the feet of AI getting better at hacking. I see it as an primarily an IT issue. We've collectively ignored the lessons of history, and made do with patch jobs over poorly chosen operating systems instead. -- We need air gaps, data diodes, and capability based operating systems. Now that I'm retired, when I have the energy, I'm working on the data diode part. This weeks lesson for me, personally, as I try to build an open source data diode, is that the Waveshare RP2350-ETH is a horrible choice for a proxy/data source/sink, as the CH9120 ethernet interface can't do promiscuous mode. It might still be sufficient to build a data diode that can mirror a website, with << $50 component cost. Time will tell.

"What will happen to the many government systems that will never get the chance to be AI-pentested?" Oh, everybody's going to get AI-pentested whether they want to or know about it or not. It's the cost of being on the Internet. Probably the situation will continue to deteriorate. Both the British Library and Jaguar Land Rover recently suffered long outages due to compromises, for example. I suspect we'll probably just lose a few large, famous businesses entirely to compromises.

> I honestly don’t blame them: [...] software is software That attitude is the problem. Why does our industry have that attitude towards quality? Every bike shop in my little town is better with quality than the average software shop in the world. Yes, software is more complex than bicycle. But a software engineer also gets paid 10x and has the luxury of spending substantial time on their product, compared to the 10 minutes it takes the bike guy down the street to diagnose and then fix an issue with my bike which I then trust my life with once they are done and I bike through traffic. We need to treat software differently. "Oh well, it's just software shrug" does not cut it anymore, if it even ever did.

The narrative around security and LLMs doesn't make sense to me. I think we've created a self-fulfilling prophecy. Everyone involved is acting with the best of intentions, but in avoiding what they fear, they've give shape and realized their fears. Much like a greek tragedy. An example of this is the story of Oedipus Rex, in the story Laius, the king, is told that he is "doomed to perish by the hand of his own son." (and wed his mother) And so to avoid this fate he decides to kill the infant. The person assigned to abandon him in the woods takes pity on the baby and gives the baby away. Thereby ensuring that Oedipus knows neither his mother or his father (and arguably giving him a reason to kill his father). The child grows up and hears the same prophecy again and the child tries to avoid the prophecy as well, as he loves his adoptive parents. So he leaves them and travels to Laius' kingdom, where he runs into Laius. Neither recognizes the other. As Laius is the type of man to kill an infant, they end up in an argument, whereupon Oedipus kills him. I think the ancients were on to something, because if Laius had reacted to the prophecy with courage, he would have been saved. I would like to argue that if he had faced his fear and raised Oedipus with love, then the necessary preconditions for the prophecy to come true wouldn't have taken root. But that's not what happens. By being driven by his neuroses and in acting with cruelty out of fear, Laius makes the prophecy real. To quote Heraclitus, ethos is fate. Or, character is fate. I think a lot of people in this AI research sub-culture would be served well by reading these classics, because they are making their self-prophesied doom come true. They have been convinced for years (GPT-2 was released in Feb 2019) that AI is dangerous. A tremendous threat. An apocalyptic threat. One dimension of this fear has been the idea that a super smart AI will take over our digital infrastructure and be responsible for the digital apocalypse. That would be terrible! So what do they do? They try to make a counter to their fears by teaching models how to exploit vulnerabilities. How dangerous is such an entity? Very! Convinced of this danger, they start testing their models as if they were weapons with offensive capability. And then they create models that can be used as weapons. And because they don't want to release a dangerous weapon out into the world (oh no!), they restrict access to their AI, thereby depriving everyone of tools they can use to improve their security... Ethos anthropoi daimon.