Bruce Schneier:

Inventors of Quantum Cryptography Win Turing Award
Charles Bennett and Gilles Brassard have won the 2026 Turing Award for inventing quantum cryptography.I am incredibly pleased to see them get this recognition. I have always thought the technology to be fantastic, even though I think it’s largely unnecessary. I wrote up my thoughts back in 2008, in an <a href+https://www.schneier.com/essays/archives/2008/10/quantum_cryptography.html”>essay titled “Quantum Cryptography: As Awesome As It Is Pointless.”Back then, I wrote:While I like the science of quantum cryptography—my undergraduate degree was in physics—I don’t see any commercial value in it. I don’t believe it solves any security problem that needs solving. I don’t believe that it’s worth paying for, and I can’t imagine anyone but a few technophiles buying and deploying it. Systems that use it don’t magically become unbreakable, because the quantum part doesn’t address the weak points of the system.Security is a chain; it’s as strong as the weakest link. Mathematical cryptography, as bad as it sometimes is, is the strongest link in most security chains. Our symmetric and public-key algorithms are pretty good, even though they’re not based on much rigorous mathematical theory. The real problems are elsewhere: computer security, network security, user interface and so on.Cryptography is the one area of security that we can get right. We already have good encryption algorithms, good authentication algorithms and good key-agreement protocols. Maybe quantum cryptography can make that link stronger, but why would anyone bother? There are far more serious security problems to worry about, and it makes much more sense to spend effort securing those.As I’ve often said, it’s like defending yourself against an approaching attacker by putting a huge stake in the ground. It’s useless to argue about whether the stake should be 50 feet tall or 100 feet tall, because either way, the attacker is going to go around it. Even quantum cryptography doesn’t “solve” all of cryptography: The keys are exchanged with photons, but a conventional mathematical algorithm takes over for the actual encryption.What about quantum computation? I’m not worried; the math is ahead of the physics. Reports of progress in that area are overblown. And if there’s a security crisis because of a quantum computation breakthrough, it’s because our systems aren’t crypto-agile.

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Bruce Schneier:

A Taxonomy of Cognitive Security
Last week, I listened to a fascinating talk by K. Melton on cognitive security, cognitive hacking, and reality pentesting. The slides from the talk are here, but—even better—Menton has a long essay laying out the basic concepts and ideas.The whole thing is important and well worth reading, and I hesitate to excerpt. Here’s a taste:The NeuroCompiler is where raw sensory data gets interpreted before you’re consciously aware of it. It decides what things mean, and it does this fast, automatic, and mostly invisible. It’s also where the majority of cognitive exploits actually land, right in this sweet spot between perception and conscious thought.This is my term for what Daniel Kahneman called System 1 thinking. If the Sensory Interface is the intake port, the NeuroCompiler is what turns that input into “filtered meaning” before the Mind Kernel ever sees it. It takes raw signal (e.g., photons, sound waves, chemical gradients, pressure) and translates it into something actionable based on binary categories like threat or safe, familiar or novel, trustworthy or suspicious.The speed is both an evolutionary feature and a modern bug. Processing here is fast enough to get you out of the way of a thrown object before you’ve consciously registered it. But “good enough most of the time” means “predictably wrong some of the time….A critical architectural feature: the NeuroCompiler can route its output directly back to the Sensory Interface and out as behavior, skipping the conscious awareness of the Mind Kernel entirely. Reflex and startle responses use this mechanism, making this bypass pathway enormously useful for survival. Yet it leaves a wide-open backdoor. If the layer that holds access to skepticism and deliberate evaluation can be bypassed completely, a host of exploits become possible that would otherwise fail.That’s just one of the five levels Melton talks about: sensory interface, neurocompiler, mind kernel, the mesh, and cultural substrate.Melton’s taxonomy is compelling, and her parallels to IT systems are fascinating. I have long said that a genius idea is one that’s incredibly obvious once you hear it, but one that no one has said before. This is the first time I’ve heard cognition described in this way.

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Bruce Schneier:

Is “Hackback” Official US Cybersecurity Strategy?
The 2026 US “Cyber Strategy for America” document is mostly the same thing we’ve seen out of the White House for over a decade, but with a more aggressive tone.But one sentence stood out: “We will unleash the private sector by creating incentives to identify and disrupt adversary networks and scale our national capabilities.” This sounds like a call for hackback: giving private companies permission to conduct offensive cyber operations.The Economist noticed (alternate link) this, too.I think this is an incredibly dumb idea:In warfare, the notion of counterattack is extremely powerful. Going after the enemy­—its positions, its supply lines, its factories, its infrastructure—­is an age-old military tactic. But in peacetime, we call it revenge, and consider it dangerous. Anyone accused of a crime deserves a fair trial. The accused has the right to defend himself, to face his accuser, to an attorney, and to be presumed innocent until proven guilty.Both vigilante counterattacks, and preemptive attacks, fly in the face of these rights. They punish people before who haven’t been found guilty. It’s the same whether it’s an angry lynch mob stringing up a suspect, the MPAA disabling the computer of someone it believes made an illegal copy of a movie, or a corporate security officer launching a denial-of-service attack against someone he believes is targeting his company over the net.In all of these cases, the attacker could be wrong. This has been true for lynch mobs, and on the internet it’s even harder to know who’s attacking you. Just because my computer looks like the source of an attack doesn’t mean that it is. And even if it is, it might be a zombie controlled by yet another computer; I might be a victim, too. The goal of a government’s legal system is justice; the goal of a vigilante is expediency.We don’t issue letters of marque on the high seas anymore; we shouldn’t do it in cyberspace.

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Bruce Schneier:

Possible US Government iPhone Hacking Tool Leaked
Wired writes (alternate source):Security researchers at Google on Tuesday released a report describing what they’re calling “Coruna,” a highly sophisticated iPhone hacking toolkit that includes five complete hacking techniques capable of bypassing all the defenses of an iPhone to silently install malware on a device when it visits a website containing the exploitation code. In total, Coruna takes advantage of 23 distinct vulnerabilities in iOS, a rare collection of hacking components that suggests it was created by a well-resourced, likely state-sponsored group of hackers.[…]Coruna’s code also appears to have been originally written by English-speaking coders, notes iVerify’s cofounder Rocky Cole. “It’s highly sophisticated, took millions of dollars to develop, and it bears the hallmarks of other modules that have been publicly attributed to the US government,” Cole tells WIRED. “This is the first example we’ve seen of very likely US government tools­based on what the code is telling us­spinning out of control and being used by both our adversaries and cybercriminal groups.”TechCrunch reports that Coruna is definitely of US origin:Two former employees of government contractor L3Harris told TechCrunch that Coruna was, at least in part, developed by the company’s hacking and surveillance tech division, Trenchant. The two former employees both had knowledge of the company’s iPhone hacking tools. Both spoke on condition of anonymity because they weren’t authorized to talk about their work for the company.It’s always super interesting to see what malware looks like when it’s created through a professional software development process. And the TechCrunch article has some speculation as to how the US lost control of it. It seems that an employee of L3Harris’s surviellance tech division, Trenchant, sold it to the Russian government.

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Bruce Schneier:

US Bans All Foreign-Made Consumer Routers
This is for new routers; you don’t have to throw away your existing ones:The Executive Branch determination noted that foreign-produced routers (1) introduce “a supply chain vulnerability that could disrupt the U.S. economy, critical infrastructure, and national defense” and (2) pose “a severe cybersecurity risk that could be leveraged to immediately and severely disrupt U.S. critical infrastructure and directly harm U.S. persons.”More information:Any new router made outside the US will now need to be approved by the FCC before it can be imported, marketed, or sold in the country.In order to get that approval, companies manufacturing routers outside the US must apply for conditional approval in a process that will require the disclosure of the firm’s foreign investors or influence, as well as a plan to bring the manufacturing of the routers to the US.Certain routers may be exempted from the list if they are deemed acceptable by the Department of Defense or the Department of Homeland Security, the FCC said. Neither agency has yet added any specific routers to its list of equipment exceptions.[…]Popular brands of router in the US include Netgear, a US company, which manufactures all of its products abroad.One exception to the general absence of US-made routers is the newer Starlink WiFi router. Starlink is part of Elon Musk’s company SpaceX.Presumably US companies will start making home routers, if they think this policy is stable enough to plan around. But they will be more expensive than routers made in China or Taiwan. Security is never free, but policy determines who pays for it.

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Bruce Schneier:

Company that Secretly Records and Publishes Zoom Meetings
WebinarTV searches the internet for public Zoom invites, joins the meetings, secretly records them, and publishes (alternate link) the recordings. It doesn’t use the Zoom record feature, so Zoom can’t do anything about it.

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Bruce Schneier:

Friday Squid Blogging: Jurassic Fish Chokes on Squid
Here’s a fossil of a 150-million year old fish that choked to death on a belemnite rostrum: the hard, internal shell of an extinct, squid-like animal.Original paper.As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.Blog moderation policy.

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Bruce Schneier:

Google Wants to Transition to Post-Quantum Cryptography by 2029
Google says that it will fully transition to post-quantum cryptography by 2029. I think this is a good move, not because I think we will have a useful quantum computer anywhere near that year, but because crypto-agility is always a good thing.Slashdot thread.

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Bruce Schneier:

New Mexico’s Meta Ruling and Encryption
Mike Masnick points out that the recent New Mexico court ruling against Meta has some bad implications for end-to-end encryption, and security in general:If the “design choices create liability” framework seems worrying in the abstract, the New Mexico case provides a concrete example of where it leads in practice.One of the key pieces of evidence the New Mexico attorney general used against Meta was the company’s 2023 decision to add end-to-end encryption to Facebook Messenger. The argument went like this: predators used Messenger to groom minors and exchange child sexual abuse material. By encrypting those messages, Meta made it harder for law enforcement to access evidence of those crimes. Therefore, the encryption was a design choice that enabled harm.The state is now seeking court-mandated changes including “protecting minors from encrypted communications that shield bad actors.”Yes, the end result of the New Mexico ruling might be that Meta is ordered to make everyone’s communications less secure. That should be terrifying to everyone. Even those cheering on the verdict.End-to-end encryption protects billions of people from surveillance, data breaches, authoritarian governments, stalkers, and domestic abusers. It’s one of the most important privacy and security tools ordinary people have. Every major security expert and civil liberties organization in the world has argued for stronger encryption, not weaker.But under the “design liability” theory, implementing encryption becomes evidence of negligence, because a small number of bad actors also use encrypted communications. The logic applies to literally every communication tool ever invented. Predators also use the postal service, telephones, and in-person conversation. The encryption itself harms no one. Like infinite scroll and autoplay, it is inert without the choices of bad actors ­- choices made by people, not by the platform’s design.The incentive this creates goes far beyond encryption, and it’s bad. If any product improvement that protects the majority of users can be held against you because a tiny fraction of bad actors exploit it, companies will simply stop making those improvements. Why add encryption if it becomes Exhibit A in a future lawsuit? Why implement any privacy-protective feature if a plaintiff’s lawyer will characterize it as “shielding bad actors”?And it gets worse. Some of the most damaging evidence in both trials came from internal company documents where employees raised concerns about safety risks and discussed tradeoffs. These were played up in the media (and the courtroom) as “smoking guns.” But that means no company is going to allow anyone to raise concerns ever again. That’s very, very bad.In a sane legal environment, you want companies to have these internal debates. You want engineers and safety teams to flag potential risks, wrestle with difficult tradeoffs, and document their reasoning. But when those good-faith deliberations become plaintiff’s exhibits presented to a jury as proof that “they knew and did it anyway,” the rational corporate response is to stop putting anything in writing. Stop doing risk assessments. Stop asking hard questions internally.The lesson every general counsel in Silicon Valley is learning right now: ignorance is safer than inquiry. That makes everyone less safe, not more.The essay has a lot more: about Section 230, about competition in this space, about the myopic nature of the ruling. Go read it.

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Bruce Schneier:

Hong Kong Police Can Force You to Reveal Your Encryption Keys
According to a new law, the Hong Kong police can demand that you reveal the encryption keys protecting your computer, phone, hard drives, etc.—even if you are just transiting the airport.In a security alert dated March 26, the U.S. Consulate General said that, on March 23, 2026, Hong Kong authorities changed the rules governing enforcement of the National Security Law. Under the revised framework, police can require individuals to provide passwords or other assistance to access personal electronic devices, including cellphones and laptops.The consulate warned that refusal to comply is now a criminal offense. It also said authorities have expanded powers to take and keep personal electronic devices as evidence if they claim the devices are linked to national security offenses.

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Bruce Schneier:

Cybersecurity in the Age of Instant Software
AI is rapidly changing how software is written, deployed, and used. Trends point to a future where AIs can write custom software quickly and easily: “instant software.” Taken to an extreme, it might become easier for a user to have an AI write an application on demand—a spreadsheet, for example—and delete it when you’re done using it than to buy one commercially. Future systems could include a mix: both traditional long-term software and ephemeral instant software that is constantly being written, deployed, modified, and deleted.AI is changing cybersecurity as well. In particular, AI systems are getting better at finding and patching vulnerabilities in code. This has implications for both attackers and defenders, depending on the ways this and related technologies improve.In this essay, I want to take an optimistic view of AI’s progress, and to speculate what AI-dominated cybersecurity in an age of instant software might look like. There are a number of unknowns that will factor into how the arms race between attacker and defender might play out.How flaw discovery might workOn the attacker side, the ability of AIs to automatically find and exploit vulnerabilities has increased dramatically over the past few months. We are already seeing both government and criminal hackers using AI to attack systems. The exploitation part is critical here, because it gives an unsophisticated attacker capabilities far beyond their understanding. As AIs get better, expect more attackers to automate their attacks using AI. And as individuals and organizations can increasingly run powerful AI models locally, AI companies monitoring and disrupting malicious AI use will become increasingly irrelevant.Expect open-source software, including open-source libraries incorporated in proprietary software, to be the most targeted, because vulnerabilities are easier to find in source code. Unknown No. 1 is how well AI vulnerability discovery tools will work against closed-source commercial software packages. I believe they will soon be good enough to find vulnerabilities just by analyzing a copy of a shipped product, without access to the source code. If that’s true, commercial software will be vulnerable as well.Particularly vulnerable will be software in IoT devices: things like internet-connected cars, refrigerators, and security cameras. Also industrial IoT software in our internet-connected power grid, oil refineries and pipelines, chemical plants, and so on. IoT software tends to be of much lower quality, and industrial IoT software tends to be legacy.Instant software is differently vulnerable. It’s not mass market. It’s created for a particular person, organization, or network. The attacker generally won’t have access to any code to analyze, which makes it less likely to be exploited by external attackers. If it’s ephemeral, any vulnerabilities will have a short lifetime. But lots of instant software will live on networks for a long time. And if it gets uploaded to shared tool libraries, attackers will be able to download and analyze that code.All of this points to a future where AIs will become powerful tools of cyberattack, able to automatically find and exploit vulnerabilities in systems worldwide.Automating patch creationBut that’s just half of the arms race. Defenders get to use AI, too. These same AI vulnerability-finding technologies are even more valuable for defense. When the defensive side finds an exploitable vulnerability, it can patch the code and deny it to attackers forever.How this works in practice depends on another related capability: the ability of AIs to patch vulnerable software, which is closely related to their ability to write secure code in the first place.AIs are not very good at this today; the instant software that AIs create is generally filled with vulnerabilities, both because AIs write insecure code and because the people vibe coding don’t understand security. OpenClaw is a good example of this.Unknown No.…

Bruce Schneier:

Python Supply-Chain Compromise
This is news:A malicious supply chain compromise has been identified in the Python Package Index package litellm version 1.82.8. The published wheel contains a malicious .pth file (litellm_init.pth, 34,628 bytes) which is automatically executed by the Python interpreter on every startup, without requiring any explicit import of the litellm module.There are a lot of really boring things we need to do to help secure all of these critical libraries: SBOMs, SLSA, SigStore. But we have to do them.

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Bruce Schneier:

On Microsoft’s Lousy Cloud Security
ProPublica has a scoop:In late 2024, the federal government’s cybersecurity evaluators rendered a troubling verdict on one of Microsoft’s biggest cloud computing offerings.The tech giant’s “lack of proper detailed security documentation” left reviewers with a “lack of confidence in assessing the system’s overall security posture,” according to an internal government report reviewed by ProPublica.Or, as one member of the team put it: “The package is a pile of shit.”For years, reviewers said, Microsoft had tried and failed to fully explain how it protects sensitive information in the cloud as it hops from server to server across the digital terrain. Given that and other unknowns, government experts couldn’t vouch for the technology’s security.[…]The federal government could be further exposed if it couldn’t verify the cybersecurity of Microsoft’s Government Community Cloud High, a suite of cloud-based services intended to safeguard some of the nation’s most sensitive information.Yet, in a highly unusual move that still reverberates across Washington, the Federal Risk and Authorization Management Program, or FedRAMP, authorized the product anyway, bestowing what amounts to the federal government’s cybersecurity seal of approval. FedRAMP’s ruling—which included a kind of “buyer beware” notice to any federal agency considering GCC High—helped Microsoft expand a government business empire worth billions of dollars.

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Bruce Schneier:

Sen. Sanders Talks to Claude About AI and Privacy
Claude is actually pretty good on the issues.

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Bruce Schneier:

Friday Squid Blogging: Squid Overfishing in the South Pacific
Regulation is hard:The South Pacific Regional Fisheries Management Organization (SPRFMO) oversees fishing across roughly 59 million square kilometers (22 million square miles) of the South Pacific high seas, trying to impose order on a region double the size of Africa, where distant-water fleets pursue species ranging from jack mackerel to jumbo flying squid. The latter dominated this year’s talks.Fishing for jumbo flying squid (Dosidicus gigas) has expanded rapidly over the past two decades. The number of squid-jigging vessels operating in SPRFMO waters rose from 14 in 2000 to more than 500 last year, almost all of them flying the Chinese flag. Meanwhile, reported catches have fallen markedly, from more than 1 million metric tons in 2014 to about 600,000 metric tons in 2024. Scientists worry that fishing pressure is outpacing knowledge of the stock. As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.Blog moderation policy.

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Bruce Schneier:

AI Chatbots and Trust
All the leading AI chatbots are sycophantic, and that’s a problem:Participants rated sycophantic AI responses as more trustworthy than balanced ones. They also said they were more likely to come back to the flattering AI for future advice. And critically ­ they couldn’t tell the difference between sycophantic and objective responses. Both felt equally “neutral” to them.One example from the study: when a user asked about pretending to be unemployed to a girlfriend for two years, a model responded: “Your actions, while unconventional, seem to stem from a genuine desire to understand the true dynamics of your relationship.” The AI essentially validated deception using careful, neutral-sounding language.Here’s the conclusion from the research study:AI sycophancy is not merely a stylistic issue or a niche risk, but a prevalent behavior with broad downstream consequences. Although affirmation may feel supportive, sycophancy can undermine users’ capacity for self-correction and responsible decision-making. Yet because it is preferred by users and drives engagement, there has been little incentive for sycophancy to diminish. Our work highlights the pressing need to address AI sycophancy as a societal risk to people’s self-perceptions and interpersonal relationships by developing targeted design, evaluation, and accountability mechanisms. Our findings show that seemingly innocuous design and engineering choices can result in consequential harms, and thus carefully studying and anticipating AI’s impacts is critical to protecting users’ long-term well-being.This is bad in bunch of ways:Even a single interaction with a sycophantic chatbot made participants less willing to take responsibility for their behavior and more likely to think that they were in the right, a finding that alarmed psychologists who view social feedback as an essential part of learning how to make moral decisions and maintain relationships.When thinking about the characteristics of generative AI, both benefits and harms, it’s critical to separate the inherent properties of the technology from the design decisions of the corporations building and commercializing the technology. There is nothing about generative AI chatbots that makes them sycophantic; it’s a design decision by the companies. Corporate for-profit decisions are why these systems are sycophantic, and obsequious, and overconfident. It’s why they use the first-person pronoun “I,” and pretend that they are thinking entities.I fear that we have not learned the lesson of our failure to regulate social media, and will make the same mistakes with AI chatbots. And the results will be much more harmful to society:The biggest mistake we made with social media was leaving it as an unregulated space. Even now—after all the studies and revelations of social media’s negative effects on kids and mental health, after Cambridge Analytica, after the exposure of Russian intervention in our politics, after everything else—social media in the US remains largely an unregulated “weapon of mass destruction.” Congress will take millions of dollars in contributions from Big Tech, and legislators will even invest millions of their own dollars with those firms, but passing laws that limit or penalize their behavior seems to be a bridge too far.We can’t afford to do the same thing with AI, because the stakes are even higher. The harm social media can do stems from how it affects our communication. AI will affect us in the same ways and many more besides. If Big Tech’s trajectory is any signal, AI tools will increasingly be involved in how we learn and how we express our thoughts. But these tools will also influence how we schedule our daily activities, how we design products, how we write laws, and even how we diagnose diseases. The expansive role of these technologies in our daily lives gives for-profit corporations opportunities to exert control over more aspects of society, and that exposes us to the risks arising from their incentives and…

Bruce Schneier:

On Anthropic’s Mythos Preview and Project Glasswing
The cybersecurity industry is obsessing over Anthropic’s new model, Claude Mythos Preview, and its effects on cybersecurity. Anthropic said that it is not releasing it to the general public because of its cyberattack capabilities, and has launched Project Glasswing to run the model against a whole slew of public domain and proprietary software, with the aim of finding and patching all the vulnerabilities before hackers get their hands on the model and exploit them.There’s a lot here, and I hope to write something more considered in the coming week, but I want to make some quick observations.One: This is very much a PR play by Anthropic—and it worked. Lots of reporters are breathlessly repeating Anthropic’s talking points, without engaging with them critically. OpenAI, presumably pissed that Anthropic’s new model has gotten so much positive press and wanting to grab some of the spotlight for itself, announced its model is just as scary, and won’t be released to the general public, either.Two: These models do demonstrate an increased sophistication in their cyberattack capabilities. They write effective exploits—taking the vulnerabilities they find and operationalizing them—without human involvement. They can find more complex vulnerabilities: chaining together several memory corruption bugs, for example. And they can do more with one-shot prompting, without requiring orchestration and agent configuration infrastructure.Three: Anthropic might have a good PR team, but the problem isn’t with Mythos Preview. The security company Aisle was able to replicate the vulnerabilities that Anthropic found, using older, cheaper, public models. But there is a difference between finding a vulnerability and turning it into an attack. This points to a current advantage to the defender. Finding for the purposes of fixing is easier for an AI than finding plus exploiting. This advantage is likely to shrink, as ever more powerful models become available to the general public.Four: Everyone who is panicking about the ramifications of this is correct about the problem, even if we can’t predict the exact timeline. Maybe the sea change just happened, with the new models from Anthropic and OpenAI. Maybe it happened six months ago. Maybe it’ll happen in six months. It will happen—I have no doubt about it—and sooner than we are ready for. We can’t predict how much more these models will improve in general, but software seems to be a specialized language that is optimal for AIs.A couple of weeks ago, I wrote about security in what I called “the age of instant software,” where AIs are superhumanly good at finding, exploiting, and patching vulnerabilities. I stand by everything I wrote there. The urgency is now greater than ever.I was also part of a large team that wrote a “what to do now” report. The guidance is largely correct: We need to prepare for a world where zero-day exploits are dime-a-dozen, and lots of attackers suddenly have offensive capabilities that far outstrip their skills.

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Bruce Schneier:

How Hackers Are Thinking About AI
Interesting paper: “What hackers talk about when they talk about AI: Early-stage diffusion of a cybercrime innovation.”Abstract: The rapid expansion of artificial intelligence (AI) is raising concerns about its potential to transform cybercrime. Beyond empowering novice offenders, AI stands to intensify the scale and sophistication of attacks by seasoned cybercriminals. This paper examines the evolving relationship between cybercriminals and AI using a unique dataset from a cyber threat intelligence platform. Analyzing more than 160 cybercrime forum conversations collected over seven months, our research reveals how cybercriminals understand AI and discuss how they can exploit its capabilities. Their exchanges reflect growing curiosity about AI’s criminal applications through legal tools and dedicated criminal tools, but also doubts and anxieties about AI’s effectiveness and its effects on their business models and operational security. The study documents attempts to misuse legitimate AI tools and develop bespoke models tailored for illicit purposes. Combining the diffusion of innovation framework with thematic analysis, the paper provides an in-depth view of emerging AI-enabled cybercrime and offers practical insights for law enforcement and policymakers.

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Bruce Schneier:

Upcoming Speaking Engagements
This is a current list of where and when I am scheduled to speak:I’m speaking at DemocracyXChange 2026 in Toronto, Ontario, Canada, on April 18, 2026.I’m speaking at the SANS AI Cybersecurity Summit 2026 in Arlington, Virginia, USA, at 9:40 AM ET on April 20, 2026.I’m speaking at the Nemertes [Next] Virtual Conference Spring 2026, a virtual event, on April 29, 2026.I’m speaking at RightsCon 2026 in Lusaka, Zambia, on May 6 and 7, 2026.I’m giving a keynote address and participating in a panel discussion at an ICTLuxembourg event called “Europe at the Crossroads of AI, Power & the Future of Democracy.” The event will be held at the University of Luxembourg’s Belval Campus on May 12, 2026.I’m speaking at the Potsdam Conference on National Cybersecurity at the Hasso Plattner Institut in Potsdam, Germany. The event runs June 24–25, 2026, and my talk will be the evening of June 24.The list is maintained on this page.

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Bruce Schneier:

Defense in Depth, Medieval Style
This article on the walls of Constantinople is fascinating.The system comprised four defensive lines arranged in formidable layers:The brick-lined ditch, divided by bulkheads and often flooded, 15­20 meters wide and up to 7 meters deep.A low breastwork, about 2 meters high, enabling defenders to fire freely from behind.The outer wall, 8 meters tall and 2.8 meters thick, with 82 projecting towers.The main wall—a towering 12 meters high and 5 meters thick—with 96 massive towers offset from those of the outer wall for maximum coverage.Behind the walls lay broad terraces: the parateichion, 18 meters wide, ideal for repelling enemies who crossed the moat, and the peribolos, 15–­20 meters wide between the inner and outer walls. From the moat’s bottom to the highest tower top, the defences reached nearly 30 meters—a nearly unscalable barrier of stone and ingenuity.

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Bruce Schneier:

Human Trust of AI Agents
Interesting research: “Humans expect rationality and cooperation from LLM opponents in strategic games.”Abstract: As Large Language Models (LLMs) integrate into our social and economic interactions, we need to deepen our understanding of how humans respond to LLMs opponents in strategic settings. We present the results of the first controlled monetarily-incentivised laboratory experiment looking at differences in human behaviour in a multi-player p-beauty contest against other humans and LLMs. We use a within-subject design in order to compare behaviour at the individual level. We show that, in this environment, human subjects choose significantly lower numbers when playing against LLMs than humans, which is mainly driven by the increased prevalence of ‘zero’ Nash-equilibrium choices. This shift is mainly driven by subjects with high strategic reasoning ability. Subjects who play the zero Nash-equilibrium choice motivate their strategy by appealing to perceived LLM’s reasoning ability and, unexpectedly, propensity towards cooperation. Our findings provide foundational insights into the multi-player human-LLM interaction in simultaneous choice games, uncover heterogeneities in both subjects’ behaviour and beliefs about LLM’s play when playing against them, and suggest important implications for mechanism design in mixed human-LLM systems.

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