Bruce Schneier:

Friday Squid Blogging: Giant Squid Live in the Waters of Western Australia
Evidence of them has been found by analyzing DNA in the seawater.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:

LLMs and Text-in-Text Steganography
Turns out that LLMs are really good at hiding text messages in other text messages.

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Bruce Schneier:

Copy.Fail Linux Vulnerability
This is the worst Linux vulnerability in years.TL;DRcopy.fail is a Linux kernel local privilege escalation, not a browser or clipboard attack. Disclosed by Theori on 29 April 2026 with a working PoC.It abuses the kernel crypto API (AF_ALG sockets) plus splice() to write four bytes at a time straight into the page cache of a file the attacker does not own.The exploit works unmodified across Ubuntu, RHEL, Debian, SUSE, Amazon Linux, Fedora and most others. No race condition, no per-distro offsets.The file on disk is never modified. AIDE, Tripwire and checksum-based monitoring see nothing.Kubernetes Pod Security Standards (Restricted) and the default RuntimeDefault seccomp profile do not block the syscall used. A custom seccomp profile is needed.The mainline fix landed on 1 April. Distros are rolling kernels out now. Patch.“Local privilege escalation” sounds dry, so let me unpack it. It means: an attacker who already has some way to run code on the machine, even as the most boring unprivileged user, can promote themselves to root. From there they can read every file, install backdoors, watch every process, and pivot to other systems.Why does that matter on shared infrastructure? Because “local” covers a lot of ground in 2026: every container on a shared Kubernetes node, every tenant on a shared hosting box, every CI/CD job that runs untrusted pull-request code, every WSL2 instance on a Windows laptop, every containerised AI agent given shell access. They all share one Linux kernel with their neighbours. A kernel LPE collapses that boundary.News article.

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Bruce Schneier:

OpenAI’s GPT-5.5 is as Good as Mythos at Finding Security Vulnerabilities
The UK’s AI Security Institute evaluated GPT-5.5’s ability to find security vulnerabilities, and found that it is comparable to Claude Mythos. Note that the OpenAI model is generally available.Here is the Institute’s evaluation of Mythos.And here is an analysis of a smaller, cheaper model. It requires more scaffolding from the prompter, but it is also just as good.

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Bruce Schneier:

How Dangerous Is Anthropic’s Mythos AI?
Last month, Anthropic made a remarkable announcement about its new model, Claude Mythos Preview: it was so good at finding security vulnerabilities in software that the company would not release it to the general public. Instead, it would only be available to a select group of companies to scan and fix their own software.The announcement requires context—but it contained an essential truth.While Anthropic’s model is really good at finding software vulnerabilities, so are other models. The UK’s AI Security Institute found that OpenAI’s GPT-5.5, already generally available, is comparable in capability. The company Aisle reproduced Anthropic’s published results with smaller, cheaper models.At the same time, Anthropic’s refusal to publicly release its new model makes a virtue out of necessity. Mythos is very expensive to run, and the company doesn’t appear to have the resources for a general release. What better way to juice the company’s valuation than to hint at capabilities but not prove them, and then have others parrot their claims?Nonetheless, the truth is scary. Modern generative AI systems—not just Anthropic’s, but OpenAI’s and other, open-source models—are getting really good at finding and exploiting vulnerabilities in software. And that has important ramifications for cybersecurity: on both the offense and the defense.Attackers will use these capabilities to find, and automatically hack, vulnerabilities in systems of all kinds. They will be able to break into critical systems around the world, sometimes to plant ransomware and make money, sometimes to steal data for espionage purposes, and sometimes to control systems in times of hostility. This will make the world a much more dangerous, and more volatile, place.But at the same time, defenders will use these same capabilities to find, and then patch, many of those same systems. For example, Mozilla used Mythos to find 271 vulnerabilities in Firefox. Those vulnerabilities have been fixed, and will never again be available to attackers. In the future, AIs automatically finding and fixing vulnerabilities in all software will be a normal part of the development process, which will result in much more secure software.Of course, it’s not that simple. We should expect a deluge of both attackers using newly found vulnerabilities to break into systems, and at the same time much more frequent software updates for every app and device we use. But lots of systems aren’t patchable, and many systems that are don’t get patched, meaning that many vulnerabilities will stick around. And it does seem that finding and exploiting is easier than finding and fixing. All of this points to a more dangerous short-term future. Organizations will need to adapt their security to this new reality.But it’s the long term that we need to focus on. Mythos isn’t unique, but it’s more capable than many models that have come before. And it’s less capable than models that will come after. AIs are much better at writing software than they were just six months ago. There’s every reason to believe that they will continue to get better, which means that they will get better at writing more secure software. The endgame gives AI-enhanced defenders advantages over AI-enhanced attackers.Even more interesting are the broader implications. The same searching, pattern-matching and reasoning capabilities that make these models so good at analyzing software almost certainly apply to similar systems. The tax code isn’t computer code, but it’s a series of algorithms with inputs and outputs. It has vulnerabilities; we call them tax loopholes. It has exploits; we call them tax avoidance strategies. And it has black hat hackers: attorneys and accountants.Just as these models are finding hundreds of vulnerabilities in complex software systems, we should expect them to be equally effective at finding many new and undiscovered tax loopholes. I am confident that the major investment banks are working on this right now…

Bruce Schneier:

Upcoming Speaking Engagements
This is a current list of where and when I am scheduled to speak:I’m giving a virtual talk on “The Security of Trust in the Age of AI,” hosted by the Financial Women’s Association of New York, at 6:00 PM ET on May 21, 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.I’m speaking at the Digital Humanism Conference in Vienna, Austria, on Tuesday, June 26, 2026.I’m speaking at the Nuremberg Digital Festival in Nuremburg, Germany, on Wednesday, July 1, 2026.The list is maintained on this page.

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Bruce Schneier:

Bypassing On-Camera Age-Verification Checks
Some AI-based video age-verification checks can be fooled with a fake mustache.

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Bruce Schneier:

Friday Squid Blogging: Bigfin Squid
Article about the bigfin squid.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:

Zero-Day Exploit Against Windows BitLocker
It’s nasty, but it requires physical access to the computer:The exploit, named YellowKey, was published earlier this week by a researcher who goes by the alias Nightmare-Eclipse. It reliably bypasses default Windows 11 deployments of BitLocker, the full-volume encryption protection Microsoft provides to make disk contents off-limits to anyone without the decryption key, which is stored in a secured piece of hardware known as a trusted platform module (TPM). BitLocker is a mandatory protection for many organizations, including those that contract with governments.Slashdot thread. And here’s Nightmare-Eclipse’s GitHub account.

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Bruce Schneier:

Laurie Anderson Is Quoting Me
Not by name, but Laurie Anderson quotes me in one of the tracks of her new album:My favorite quote is from a cryptologist who said “If you think technology will solve your problems, you don’t understand technology and you don’t understand your problems.”Also in interviews:“Of course, it’s ridiculous, outrageous, blah, blah, blah,” Anderson says about the ad. ‘But, I mean, my favorite quote on this is from a cryptologist who said, ‘If you think technology will solve your problems, you don’t understand technology ­ and you don’t understand your problems.’ And I think I’m completely on board with that.”People are telling me that she has been reciting this quote in performances for years. (I lost track of her since college and her 1981 hit “”https://www.youtube.com/watch?v=Vkfpi2H8tOE”>O Superman.”)The origins of the quote is from Roger Needham:If you think cryptography can solve your problem, you don’t understand your problem and you don’t understand cryptography.I modified the quote in the preface to my 2000 book Secrets and Lies:A few years ago I heard a quotation, and I am going to modify it here: If you think technology can solve your security problems, then you don’t understand the problems and you don’t understand the technology.I can’t tell you why me in 2000 didn’t credit Needham by name. I should have.I have used the quote pretty consistently since then. Somewhere along the line I dropped “security” from the phrase, and now say it more like Anderson quotes me:If you think technology will solve your problem, you don’t understand your problem and you don’t understand technology.I sometimes use singular and sometimes use plural. Sometimes I say “the problem” and “the technology.” But I think the quote flows better ending with just the word “technology.”

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Bruce Schneier:

On AI Security
Good report:Executive Summary: Let’s say you wanted to make sure that your AI is secure. Can you just maximize the security and privacy benchmark and call it a day? Nope, because benchmarks don’t actually work for measuring AI capabilities (even when they are NOT emergent systemic properties like security). So let’s take a step back: how do you measure security in the first place? Good question. Over the last 30 years, security engineering for software evolved from black box penetration testing, through whitebox code analysis and architectural risk analysis to de facto process-driven standards like the Building Security In Maturity Model (BSIMM). Software had a very deep impact on business operations, and it appears that AI is going to have an even deeper impact. Will a software security-like measurement move work for AI? Probably. In the meantime we can make real progress in AI security by cleaning up our WHAT piles and managing risk by identifying and applying good assurance processes. (Spoiler alert: no matter what we do, we still don’t get a security meter for AI, so we need to be extra vigilant about security.)

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Bruce Schneier:

macOS Kernel Memory Corruption Exploit
A group used Anthropic’s Mythos AI model to help find a kernel memory corruption vulnerability and exploit on Apple’s M5.News article.

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Bruce Schneier:

CISA Security Leak
Crazy story:Until this past weekend, a contractor for the Cybersecurity & Infrastructure Security Agency (CISA) maintained a public GitHub repository that exposed credentials to several highly privileged AWS GovCloud accounts and a large number of internal CISA systems. Security experts said the public archive included files detailing how CISA builds, tests and deploys software internally, and that it represents one of the most egregious government data leaks in recent history.News article.

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Bruce Schneier:

Friday Squid Blogging: Regulating Squid Fishing in the South Pacific
The South Pacific Regional Fisheries Management Organization (SPRFMO) needs to regulate squid fishing in the South Pacific.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:

Identifying People Using Wi-Fi Routers
Not identifying people based on their use of Wi-Fi routers, but identifying people using Wi-Fi signals.This is accomplished through what is known as WiFi sensing, or the use of WiFi signals to infer information about a physical environment. When radio signals like WiFi travel through a space, they interact with the objects and people around them. Those signals can be reflected, scattered, or absorbed. By analyzing how the signal is expected to behave compared with how it is actually received, researchers can infer details about the surrounding environment.“By observing the propagation of radio waves, we can create an image of the surroundings and of persons who are present,” said Thorsten Strufe, a KIT professor and study co-author, in a press release. “This works similar to a normal camera, the difference being that in our case, radio waves instead of light waves are used for the recognition.”

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Bruce Schneier:

FBI’s 2025 Internet Crime Report
The 2025 Internet Crime Report was published a few weeks ago, but I only just saw it.
Lots of interesting statistics.Press release. News articles.

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Bruce Schneier:

Chilling Effects
Younger Americans have soured on the second Donald Trump presidency, but they are not protesting it.Despite an unpopular Iran war and an even more unpopular Trump administration, college campus protests nationwide have gone silent. And at many schools, student activism is virtually nonexistent.This silence comes in the wake of a relentless Trump administration war on campus speech that has involved lawsuits, arrests, deportations and expulsions.Reports cite a range of complicated factors for the restraint, from apathy to technology-induced incapacity. But as public policy and law and social science experts, we believe students aren’t protesting for a very simple reason: They are afraid. They are self-censoring and disengaging from campaign activism to avoid punitive measures.In law and social science, we call this impact a chilling effect—the behavioral tendency for people in face of a threat to self-censor and restrain their activities for self-protection.It’s increasingly clear to us that these impacts are not incidental or ancillary to Trump administration policy. Rather, the chilling effects are the point. This is the closest thing to a consistent governing strategy in Trump’s second term.The broader chill of Trump threatsChilling effects can be subtle, but today they are everywhere. And it’s not just students who are chilled by Trump administration threats.Professors are censoring themselves in lectures and rewriting syllabuses. Researchers are stripping grant applications of words that might attract federal scrutiny, or abandoning the topics entirely. Media outlets are modifying their news coverage to avoid Trump lawsuits or sanctions.Law enforcement and regulatory agencies are refusing to investigate Trump-aligned actors inside or outside government, and major national law firms are declining cases challenging Trump administration policies.Publishers are “stepping back” from LGBTQ+ books and other progressive subjects. Many in targeted immigrant communities are afraid to leave home to go to work or school.In most cases, these people and institutions are not being specifically targeted or threatened by Trump. But they are afraid, and their fear is doing the administration’s work for it. They stay silent, avoid attention and confrontation, and look the other way. In other cases, they change their speech and behavior to accommodate or conform to the administration’s worldview.Of course, there are counterexamples, such as the winter protests in Minneapolis in response to brutality by agents with U.S. Immigration and Customs Enforcement, and the recent “No Kings” rallies. But even here, the broader but less visible trend—chilling effects—is evident.For instance, in recent reporting on the latest No Kings rallies, many media outlets observed that students were noticeably missing, despite the Trump administration’s unpopularity among younger Americans.A persistent strategyWe believe none of this is by accident.In a new book, “Chilling Effects: Repression, Conformity, and Power in the Digital Age,” one of us—Jon Penney—explains how law, technology, and state and corporate power are weaponized to chill and repress, and the dangers this poses for the United States and other democratic societies. The other—Bruce Schneier—has extensively studied the security infrastructure enabling this.What we see isn’t gratuitous government cruelty, chaos or vengeance. Instead, we see a persistent strategy to maximize fear and chilling effects in ways that are corrosive to freedom and democracy.Research suggests that surveillance, personal threats, uncertainty and abuse of power are key factors in doing so. The federal government has a clear and systematic pattern of employing these very mechanisms across a number of domains far beyond campuses.They are evident in militarized raids by Immigration and Customs Enforcement and in journalists being arrested and indicted for reporting on protests. They are made clear in the long list of political enemies the Trump…

Bruce Schneier:

Friday Squid Blogging: Another Squid
Someone named “Squid” seems to be a “West Country legend.”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:

Vulnerability Disclosure in the Age of AI
New article: “Responsible Disclosure in the Age of AI: A Call for Urgent Action,” by Melissa Hathaway.Abstract: Artificial intelligence is fundamentally reshaping the balance between vulnerability discovery and remediation. Frontier AI models are now capable of autonomously identifying exploitable software vulnerabilities at unprecedented speed and scale. This development exposes decades of accumulated technical debt created by a software industry that prioritized rapid deployment over secure-by-design engineering practices. Drawing on the evolution of software assurance, vulnerability disclosure frameworks, and U.S. cyber policy, this perspective argues that the current moment represents a strategic inflection point for governments, industry, and critical infrastructure operators. The author examines the growing tension between offensive and defensive equities in cyberspace, the emergence of AI-enabled vulnerability discovery capabilities in both the U.S. and China, and the increasing risks posed by unsupported legacy systems and AI-assisted code generation practices. Responsible disclosure can no longer remain a reactive or fragmented process, but must become a coordinated national and international resilience effort involving governments, software vendors, infrastructure operators, and emergency response organizations. The article concludes with an urgent call for accelerated remediation, large-scale patch management coordination, and sustained investment in automated vulnerability repair capabilities before adversaries exploit this rapidly narrowing window of opportunity.

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Bruce Schneier:

Microsoft Threatening Security Researcher
An anonymous security researcher called “Nightmare Eclipse” has been publishing a series of significant security exploits against Microsoft Windows—including one that breaks BitLocker. Microsoft has threatened legal action against the researcher. Lots of recriminations are being traded back and forth.

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Bruce Schneier:

The Intersection of Encryption and AI
As part of their 20th Anniversary celebration, Dark Reading asked five cybersecurity industry leaders who wrote blogs or columns for them over the years to select their favorite piece and share their reflections on the topic today. This is my section.Renowned technologist and author Bruce Schneier contributed a column on June 20, 2010, warning about cryptography’s inability to secure modern networks, a point he says he has been trying to argue since 2000.“For a while now, I’ve pointed out that cryptography is singularly ill-suited to solve the major network security problems of today: denial-of-service attacks, website defacement, theft of credit card numbers, identity theft, viruses and worms, DNS attacks, network penetration, and so on.“Recently, I talked to a former NSA employee at a conference. He told me that back in the 1990s, he had a copy of my book Applied Cryptography by his desk, as did many other cryptographers working at Ft. Meade. People were allowed to refer to it, but they were not allowed to cite it.“The 1990s were an important decade for cryptography. This was before the internet went mass market, when cryptography was just emerging from a niche academic discipline to a mainstream engineering one. There wasn’t much that programmers could read. The NSA used my book for the same reason it became a bestseller: because it collected all the academic cryptography of the time in one place and made it understandable to people who weren’t mathematicians. They feared it for exactly the same reason.“I’ve been thinking about that conversation as I revisit a 2010 essay I wrote for Dark Reading, ‘The Failure of Cryptography to Secure Modern Networks.’ Cryptography has inherent mathematical properties that greatly favor the defender. Adding a single bit to the length of a key adds only a slight amount of work for the defender but doubles the amount of work the attacker has to do. Doubling the key length doubles the amount of work the defender has to do (if that—I’m being approximate here) but increases the attacker’s workload exponentially. For many years, we have exploited that mathematical imbalance.“Computer security is much more balanced. There’ll be a new attack, and a new defense, and a new attack, and a new defense. It’s an arms race between attacker and defender. And it’s a very fast arms race. New vulnerabilities are discovered all the time. The balance can tip from defender to attacker overnight, and back again the night after. Computer security defenses are inherently very fragile.“That isn’t a new idea. I said much the same thing in the preface to my 2000 book, Secrets and Lies:“‘Cryptography is a branch of mathematics. And like all mathematics, it involves numbers, equations, and logic. Security, real security that you or I might find useful in our lives, involves people: things people know, relationships between people, people and how they relate to machines. Digital security involves computers: complex, unstable, buggy computers.’“I especially like how I phrased it in 2016: ‘Cryptography is harder than it looks, primarily because it looks like math. Both algorithms and protocols can be precisely defined and analyzed. This isn’t easy, and there’s a lot of insecure crypto out there, but we cryptographers have gotten pretty good at getting this part right. However, math has no agency; it can’t actually secure anything. For cryptography to work, it needs to be written in software, embedded in a larger software system, managed by an operating system, run on hardware, connected to a network, and configured and operated by users. Each of these steps brings with it difficulties and vulnerabilities.’“It’s a lesson we have all learned over the decades. Cryptography is still necessary for cybersecurity—although I wouldn’t have used that word back then—but is not sufficient. There are particular attack and forms of mass surveillance that cryptography prevents. But as computers have infused throughout our lives,…