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That resulted in the Communications Assistance to Law Enforcement Act, which mandated that central offices offer remote wiretapping. Capacity up to 1% of lines is required.
Back in the electromechanical era, the only call data that could be collected was outgoing dial pulses, using a "pen register".[1] (The one shown in Wikipedia is mine. It's a beautiful piece of antique brass telegraph technology. It records dial pulses as dashes, and has to be wound up like a clock, with a big brass key.) The Supreme Court decision allowing "pen registers" without a warrant refers to these "extremely limited" devices. That definition has been stretched and stretched by law enforcement into all non-voice data collected by telcos.
Law enforcement still wants more.
[1] https://en.wikipedia.org/wiki/Pen_register
This doesn't resonate with me. I see companies adding more sloppily written features with AI. I see more bugs in the software I use, not less. While it's plausible that software is getting both buggier and more secure, I suspect those two move in the same direction not opposite.
My guess is that we're getting better at finding _existing_ security issues with AI (and thus fixing those issues), but simultaneously adding more insecure surface areas _at a faster rate_.
Over the long term this state of play could change, and IC/LEO organizations could start leaning more on application vulnerabilities than on platform RCEs. But the action would probably still coalesce around a couple of app-layer targets that could themselves be hardened.
That said if companies want to "ship ship ship fast", then yes even AI can produce bugs or regressions if not carefully reviewed by the human.
There days we're generating multiple times more code than we were writing before. That means a similar multiple of opportunities for bugs to be introduced - so the ability to automate security review is more impactful in proportion to that.
You should question your ability to see any bugs on YOUR side.
It's like two parallel worlds, that exist in the same place at the same time, but somehow don't cross.
Anyways, while there I attended a little roundtable on software security. It was me, representing a small unit from the Air Force, some dude from Google, and like 15 game devs.
Despite only being a dev of 5 years at that point, I was SHOCKED at the lack of knowledge on software security. Even simple concepts seemed completely foreign to the game devs, though the Google dude seemed to have a really solid understanding of security.
Obviously game devs and website devs and all kinds of devs have different focuses, but it just blew my mind that out of all the topics there I might’ve been considered a comparative expert in, security was somehow the one. I wasn’t sure if that was a major plus for military devs or a major concern for the other devs, but now I’m starting to learn in the latter direction.
As an end user, security in game development seems to hit a minimum is the early 2000s.
I recall playing EverQuest and using ShowEQ on a Linux machine on the same network as a proxy to silently eavesdrop on the traffic to show a map of the game with all the hidden/obscured/visible stuff all present. They either never encrypted that traffic or I quit playing before they did.
As multiplayer games started to become the default, netcode improved quite a bit and basic encryption was implemented - but I don't recall a single multi-player game, ever, that was free of hackers when playing online.
It feels like over the years the issue moved from remote exploitation to hiding processes on the user's machine. That has lead to kernel-level anticheat systems. I'm unsure of the effectiveness as when they started to become common I moved all of my gaming to dedicated hosts because I wasn't willing to give that level of access to my "real" computers. That said, I've certainly not noticed a decrease in the perceived number of cheaters.
These days, as far as I know - and to be clear, this isn't an area of deep interest for me - I'm not worried about my gaming accounts being compromised through technical means. It feels like that sort of security is a solved issue overall, although I suppose it's also possible that other forms of exploits have simply gotten easier/cheaper.
heh. long greasy slide. It really does feel like that.
Apart from the obvious harms of invasion of privacy, and fishing expeditions being biased to the places you decided to fish. There is the simple fact that data can be misleading, especially without context. An interceped communication is a piece of data that is intrinsically tied to the trust of the inteceptor. A few people with an agenda can collaborate to create a seeming truth by 'discovering' the same thing from different sources.
Requiring warrants compelling information holders to provide data, not only serves the task of protection from abuse but also create a record of provenance that can be verified.
It also provides a degree of symmetry in capabilities which discourages actions that one party may do over another if they are motivated to act because they have a temporary advantage over another.
I don't understand how you can both argue for that law enforcement (and intelligence) agencies will force others to implement intentional backdoors AND also everyone will be using AI to find and secure ALL potential holes in the software so there won't be any vulnerabilities anymore.
Wouldn't one AI or another detect this deliberate backdoor and report it, as it'll look just like any other security vulnerability, the only difference being the intention?
I have respect for the author so I feel like I probably misunderstand something from the overall text rather than I somehow have a better perspective on this topic that the author knows very much more about than me. I felt like I nodded along all up until "So how is this a problem?" and now I'm not sure I understood correctly.
It's seems like an odd-duck for sure, and I doubt it's a realistic proposition. I do think "perfect encryption for dummies" is all well and good until organized crime organizations are able to challenge the government in certain regions of our country.
All of this sends us deep into the realm of political philosophy, the nature and purpose of governments, and the freedom vs security tradeoffs we live with.
I listened to the latest Plain English podcast this morning, which was explicitly about the potential for a ransomwarepocalypse in the coming years, as open models let any tom, dick, or harry become capable of a plug-and-play ransomware attack, instead of that being left to the realm of professionals. It's a bit nerveracking to think about every nigerian prince scam suddenly becoming a sophisticated attack on your local water sanitation system.
https://youtu.be/vWvazbGPCCI
I think I can kind of see that from the text re-reading it, it's kind of hidden though and not so explicit if this is what he is trying to communicate. Thanks for giving me a new perspective to read it with!
The author agrees with you and addressed this point. The US forcing backdoors into its own systems ("own": Those for sale and distribution within the US) would create vulnerabilities making those systems weaker.
That's precisely the author's point: deliberate backdoors will be more adversary-exploitable than ever before, but the demand for such from law enforcement agencies is likely to ratchet upwards.
But that's one step after, I'm trying to understand how those backdoors even end up in software if everything gets automatically reviewed by the people working on these codebases? Wouldn't things like these be flagged by systems other than the developers tasked by the agency to implement it? How can law enforcement actually get these things implemented without big parts of the engineering team not seeing warnings about it happening?
If you're a US company building an app/device/etc. such that an intelligence agency like the CIA or FBI would want access to the data in that product which is normally secured, then they're not going to try to sneak it in there without your development team knowing. They're going to have a meeting with the owners of the company and say, "hey, we'd really like you to implement this backdoor for us, and in return we won't cause you in problems."
Note that this does certainly already happen a lot, but it's also not something that can happen across the board (like the author points out). Apple, being one of the largest companies in the world and who has one of their biggest selling points being their security, has explicitly refused to do this to the point that the intelligence agencies couldn't break into an iPhone until another company found a way to do so.
>I'm trying to understand how those backdoors even end up in software if everything gets automatically reviewed by the people working on these codebases?
The people working on these codebases are "in on it." Of course, we're talking backdoors which are very subtle, target very minimal infrastructure, and are known about by very few people. But, like I said, companies are currently shipping products with backdoors in them knowing they exist already. AI doesn't change that dynamic.
>Wouldn't things like these be flagged by systems other than the developers tasked by the agency to implement it?
The only people who would have access to the systems that can even be flagged by this stuff would be people who would know about it. Keep in mind that the scale we're talking here is massive. Think about how software development works at companies like Apple, Microsoft, Google, etc. There are devs working in offices all around the world where they only ever have access to a fraction of the code that company owns. These companies are very capable of keeping their stuff locked down. It's a necessary component of their work.
>How can law enforcement actually get these things implemented without big parts of the engineering team not seeing warnings about it happening?
Hopefully my explanation at this point is clear, but just to be concrete: backdoors are, by design, very hard to detect. That doesn't mean they're just sneakily written code that humans don't notice as they read over it, but, instead, they're very subtle implementations in very specific parts of huge systems that are already locked down to the point that the number of people who even have access to those portions of the systems are very limited. These agencies don't slip in backdoors without anybody noticing; they convince the minimal number of people needed to know about it to implement it. Again, we're talking about a meeting between the directory of a three letter agency and a CEO, where the CEO then directs the CTO to implement the backdoor who then instructs the handful of very high-ranking engineers to do so.
AI systems in these companies may very well flag these backdoors to the people who already know they exist, then these people can tell the AI "hey, those are their on purpose, so just move on," and the other 99.99% of the company will never know they exist.
I suppose it's important to emphasize, again, that these systems are incredibly massive and complex and most people at these orgs don't have any access to most of these systems, so it's not like you can expect an intern running BugBot across a repo and expecting it to find a backdoor.
One of the author’s blind spots here is the concept of “digital sovereignty”. The US is continuing to ban more and more Chinese-made hardware out of fear that the Chinese govt has installed backdoors in them… which you could interpret as an admission that the US does exactly that with American made products. Globalized supply chains are, erm, complex, and few if any companies are really going to be able to achieve “digital sovereignty” with hardware. But with software it’s actually plausible, though obviously hard. Whether or not the feds have actually installed backdoors in Microsoft Outlook, foreign govts are rightly concerned that they have, and are increasingly pushing to avoid US made software for simple national security reasons.
In a nutshell, what I’m saying is “They shouldn’t do either” is at best a platitude and at worst a distraction preventing critical thought.
> Thus: over the next two years, major pieces of software are likely to run out of remotely-exploitable bugs.
> While I think this is great, for law enforcement and offensive intelligence agencies, it’s going to be a nightmare.
> So what do we do about it? I honestly have no idea. [...] it’s just occurring to me that we’re on a long greasy slide to a place that will look different than where we are today. [We’re] just going to have to hope that this time we make the right choices.
AI code is flawless and impenetrable!
we live in a world where the government can't even do much about illegal drug markets anyone can access by downloading a piece of software.
if they pass laws that mandate backdoor access and block software which doesn't conform more and more people will move to the dark networks.
and if they effectively block the dark networks (in the limit they will have to block all encrypted communications) then we will be living in a tyranny.
freedom is messy. accept that digital crime can only be solved when the criminal makes a tangible mistake. LLM's will be building profiles on criminals to help with identifying mistakes.
Like if we were willing to stop adding new code and just have a small secure code base, AI could maybe help us find all the vulnerabilities in that code base.
But people have consistently been unwilling to do that. Like if we were willing to stop adding code we could have stopped decades ago and done SQLite level testing everywhere and probably have found almost all the bugs already.
Now it’s just as you said- asking AI to red team your app will get you pretty far.
Unless you remember 2013, Snowden, that nothing was done (at most was some concern about doing it to US citizens, the rest of the world doesn't deserve privacy), all US (and/or five-eyes) based web companies must disclose users information and be forced to not disclose that, and things kept going surely at a faster and more intrusive rate in everything else, and of course phones.
You are complaining being sprinkled by water while at the bottom of the ocean. At least the big companies can find their own vulnerabilities with the AI tools you mention, the rest of the doors are still wide open.
It will be interesting to see if my prophecy becomes reality.
BTW I also hate that Hacker News is being dominated by articles on A.I. lately. Maybe we should vote on HN reducing or even eliminating A.I. related news?
It also seems likely to me that the US Gov. probably already has routine mechanisms for compelling targeted software updates for persons of interest, so I'm not sure that a more formalized backdoor than automatic updates is going to be surfaced in the mainstream, unless that is avenue is also cut down somehow.
Basically in the AI age, the difference between a vulnerability and a backdoor diminishes..
I'm more curious what could be a right choice, and more importantly who is the "we" in this, as many decisions are largely made by companies and governments.
These laws exist - they aren't the focus yet. Right now there's still no need; just hack the device or compel the cloud service to give the data, why waste energy getting consent from its owner!
More bugfinding AI, more end to end encryption, more CVEs and more fixes, cannot happen soon enough.
If automated pentesting in PR review CI pipeline will become table stakes - which is very plausible - maybe the OP has a point.
(It’s of course not only the US, just that the largest AI providers are US based and we know from history how US agencies operate)
I'm using open weights models on a privacy-focused provider right now, and that's adequate for my current usage, but I'm rapidly getting to the point where my agent's access level to my data (and to a lesser extent, my accounts) is becoming something I'm not comfortable sending outside my network at all.
My hope is that models that are roughly on par with Deepseek V4 Flash can be run on hardware that I can own for <~$5k in the near future. We're close, but not there yet as far as I know.
The only long-term solution to this is self-hosting.
Law enforcement doesn’t need this surveillance ability at all. All time periods prior to 25 years ago didn’t have it.
Additionally, there is no correlation between “law enforcement reads text messages” and crime rates going down.
Crime's been decreasing for years, and (from what I understand) this year is tracking to be one of the safest years on record?
Definitionally, there absolutely has to be a correlation (not causation) between those two factors you listed.
https://ourworldindata.org/us-crime-rates
No, it was just good at it because it wasn't RL'd against it. I know this is a small detail, but it tosses journalistic credibility in my eyes.
> In response to questions about the draft blog post, the company acknowledged training and testing a new model. “We’re developing a general purpose model with meaningful advances in reasoning, coding, and cybersecurity,” an Anthropic spokesperson said. - https://fortune.com/2026/03/26/anthropic-says-testing-mythos...
It is possible it is both, they used to RL against cybersecurity, but also didn't explicitly do any qualitative tests and added/changed more data because of those results. For Mythos, they stopped RL'ing against it, and also now intentionally try to make it better.
Unless of course they've actually noted exactly how things were trained here in some technical report and I've missed it, that's possible. Anthropic aren't famous for being very public about their internals though, but would be curious to read more details about it if it's out there from the horse's mouth.
Presumably RLHF (Reinforcement Learning from Human Feedback).
I personally welcome such spiraling offense-defense cycles as it is one of the main drivers of the technological progress.
> Thus: over the next two years, major pieces of software are likely to run out of remotely-exploitable bugs.
His conclusion sounds extremely optimistic to me.
Perhaps we are going to go up a level with hacking done by probing the systems and the system of systems.
Pre-AI, the advantage went to the entities with the largest budget to hire the best and brightest security engineers.
Post-AI, it'll go to the entities with the largest inference budget.
Right now we're in a transitionary period where it's kind of a tossup which approach is more practical, but at the end of the day - it's still all about how much money you can throw at the problem. I'm just hoping the threshold climbs high enough it's no longer practical for governments to be able to compromise individual actors' devices because doing so would waste a 0-day that's far, far more valuable than prosecuting one arbitrary person is worth.
Lmao this is like “I’m concerned the raccoons that I see in the storm drains are going to make our sewer system much too efficient”