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,…

Bruce Schneier:

AI Used to Decrypt Medieval Ciphers
Researchers are using machine learning algorithms to decrypt historical pencil-and-paper ciphers.

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Bruce Schneier:

Hacking Meta’s AI Chatbot
Hackers are convincing Meta’s AI support chatbot to let them take over other peoples’ accounts:A video posted on X showed the step-by-step process to hack someone’s Instagram account. The hacker allegedly used a VPN to spoof the targets’ presumed location to avoid triggering Instagram’s automated account protections. Then, the hacker opened a chat with Meta AI Support Assistant and asked the bot to add a new email address to the target’s account. The chatbot can be seen sending a verification code to the email address provided by the hacker; the hacker then shares the verification code with the chatbot, which prompts the chatbot to show a button to “Reset Password.” The hacker enters a new password and takes over the victim’s account.[…]On Monday, Instagram spokesperson Andy Stone said in a reply to Wong’s post and others that the issue was now fixed. It’s unclear how many Instagram users had their accounts improperly accessed. It’s not that easy. Probably this particular tactic is now blocked. But there are others, many others, and they cannot be blocked as a class. The real problem is that LLM chatbots are not trustworthy enough for this application.Another news article.

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Bruce Schneier:

AI Worm
Researchers have prototyped an AI-powered internet worm.The coolest thing about the prototype is that it carries its own LLM with it, and runs it on computers that have been broken into.This is the closest to John Brunner’s original 1975 conception of a computer worm that I’ve seen.

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Bruce Schneier:

Anthropic’s Project Glasswing Update
In April, Anthropic initated Project Glasswing. The idea was to let companies use their new model to find and fix vulnerabilities in their own software. It was a fantastic PR move, and so many press outlets have uncritically parroted Anthropic’s claims that it’s now common wisdom that Mythos is better at finding software vulnerabilities than other models. Which is just not true.In any case, Anthropic has published a Project Glasswing status report. It’s finding a lot of vulnerabilities in software—yay! Some of them are even dangerous. But almost none of them has been patched. It’s weird. There’s something fishy about the data that I don’t understand. That Anthropic refuses to release details—that it just says “trust us”—is a big problem here.

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Bruce Schneier:

Critical Zcash Vulnerability Found and Fixed
If you’re a user—owner?—of this cryptocurrency, this is important:On May 29, the security researcher Taylor Hornby found a critical vulnerability in Zcash Orchard privacy pool using The Orchard pool is the newest and most advanced shielded transaction system in the cryptocurrency Zcash. Introduced in 2022, it allows users to send and receive ZEC while keeping transaction details private. It uses zero-knowledge proofs to validate transactions without revealing amounts or participants. The bug: a specific check that was supposed to validate transaction inputs wasn’t actually enforcing the rules it appeared to enforce. An attacker could have exploited the flaw to feed false inputs into that check and generate ZEC from nothing, with the zero-knowledge proof system blessing the fraudulent transaction as valid.It’s fixed; that’s the good news. The bad news is that there’s no way of knowing if anyone exploited the vulnerability to steal money. And this fragility is the fundamental problem that makes blockchain such a bad idea.

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Bruce Schneier:

GPS As a Key Distribution Platform
This is interesting:The U.S. military has likely been quietly broadcasting codes for its global encryption network using public GPS for nearly 20 years, turning each satellite into a hidden “numbers station,” according to Steven Murdoch…That means every device that uses GPS has been receiving hidden government information for years, and nobody outside the military knew it until now.[…]Murdoch discovered that this particular sentinel was transmitted by all 31 operational satellites within a window of a few hours on May 26, 2011, potentially heralding the activation of a new operational system. He confirmed that this timeline coincided with the rollout of the military’s Over-the-Air Distribution (OTAD) and the Over-the-Air Rekeying (OTAR) by cross-referencing declassified documents, including a 2015 presentation about the dates of the operation.“There was a perfect match between the timeline and that presentation and the change points that were automatically identified from the data,” Murdoch said. “That was the smoking gun that made me think: This is what it’s for.”These automated systems replaced the cumbersome manual distribution of cryptographic keying material, allowing military GPS receivers around the world to be rekeyed remotely through satellite broadcasts rather than through onsite procedures.

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Bruce Schneier:

NSO Group Hacking WhatsApp Despite Court Order
WhatsApp has caught the NSO Group phishing its users, in violation of a court order.

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Bruce Schneier:

Enhanced License Plate Tracking
The surveillance company Leonardo wants more data:A surveillance company plans to add sensors to automatic license plate readers (ALPRs) that would mean the devices, as well as capture the license plate of passing vehicles, would also sweep up unique identifiers of mobile phones, wearables, and other Bluetooth-enabled devices in those cars, potentially letting law enforcement identify specific drivers or passengers.The technology, called SignalTrace, would turn ALPR cameras from devices focused on tracking cars to ones that can more readily track the location of particular people. ALPR cameras have become a commonly deployed technology all across the U.S.; SignalTrace would make some of those cameras capable of collecting much more data.Yes, it’s bad that more companies are collecting this level of surveillance data. But all of this pales in comparison to the type and quantity of data our smartphones already collect about us.Alternate link.

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Bruce Schneier:

Bernie Sanders’ AI Sovereign Wealth Fund Plan
Let no one accuse Bernie Sanders of ducking the big questions. Writing in the New York Times last week, the senator asked: “Will the future of humanity be determined by a handful of billionaires who have promoted and developed AI, with virtually no democratic input, who stand to become even richer and more powerful than they are today?”We agree entirely that this is one of the most potent questions facing global democracy today. Our book, Rewiring Democracy, surveys the emerging uses for and impacts of AI in democracy around the world and reaches the same conclusion: that the most urgent risk posed by AI is the concentration of power, wealth and control among tech oligarchs.And yet we reached a vastly different conclusion than Sanders on what to do about it.The senator points to a once radical but increasingly popular solution: creating a US sovereign wealth fund by taking 50% stock in AI companies such as Anthropic, OpenAI and xAI. The argument in favor of this is twofold. One: it would establish democratic control over the AI companies, giving the government “the power, through its voting shares and an equal representation on each company’s board, to block decisions that hurt our citizens and to push for policies that help them”. Two: it would return a big chunk of the economic rewards of soaring AI valuations to the public, ensuring “trillions of dollars potentially generated by AI are used to improve the lives of all of us”.We laud both these goals unreservedly.We wholeheartedly agree that there must be public influence over the development and use of AI, just as we demand the government intervene to ensure that automakers, drugmakers, airlines and other industries balance profitability with public safety and the public interest. And we credit the senator with recognizing that there are more levers for the government to pull beyond the promulgation of regulation to achieve this.And we also agree that the obscene, dangerous accumulation of wealth among AI companies needs to be disrupted. As OpenAI and Anthropic race to be minted as the world’s latest trillion-dollar AI companies, we should recognize that—whether or not it constitutes a bubble—these staggering market capitalizations represent a transfer of wealth. The flow of money goes from the smaller businesses and actual people using AI, and being subjected to it, to the owners of these tech companies.That includes the world’s 86 AI billionaires “seeking to maximize their power and profit” aiming to decide the “fate of humanity … behind closed doors in Silicon Valley”, as Sanders said.And yet, while we do not outright oppose the taking of AI company stock, or of a US sovereign wealth fund, there are better ways to achieve Sanders’ stated goals.Public ownership of these companies entangles corporate profit and valuation with the public interest. It would incentivize the government to clear regulations, permit the exploitation of workers and users, suppress competition, encourage AI adoption regardless of the responsibleness of the implementation or appropriateness of the use case, and otherwise act on behalf of corporate interests.After all, if growing, say, Nvidia from its first $5tn in value to its next $5tn also represents a doubling in value of this segment of the sovereign wealth fund, then you can expect the fund managers to support chip sales, foreign and domestic, with the same zeal as the company’s private investors.This is not an effective way to influence corporations to act in the public interest. In fact, it makes corporate influence on the government more likely.We should be wary of this possibility because we’ve seen it before. Ownership of substantial stakes in oil companies by the Norwegian sovereign wealth fund, the world’s largest, does not seem to have steered those corporations to pro-environmental policies. Instead, the Norwegian government’s dependence on those companies has inhibited them from taking climate action. Here in the US…

Bruce Schneier:

Friday Squid Blogging: Squid-Inspired Fluid Pump
This fluid pump was inspired by the way squids propel themselves through the water.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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B. Schneier:

Upcoming Speaking Engagements
This is a current list of where and when I am scheduled to speak:I’m giving a keynote at Cybernation 2026 in Berlin, Germany, on June 24, 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 participating in a panel discussion at the Austrian Institute for International Affairs in Vienna on Thursday, June 25, 2026.I’m speaking at the Digital Humanism Conference in Vienna, Austria, on Friday, June 26, 2026.I’m giving a fireside chat for Epicenter Works, to be held at Kaffee Alt Wien in Vienna, Austria, on Friday, June 26, 2026.I’m participating (via Zoom) in a panel discussion at Quantum.Tech World in Boston, Massachusetts, USA, on Friday, June 26, 2026. The topic is “Q-Day’s Shortening Deadline: Immediate Solutions.”I’m speaking at Czech Technical University in Prague, Czechia, on Monday, June 29, 2026.I’m speaking at the Nuremberg Digital Festival in Nuremburg, Germany, on Wednesday, July 1, 2026.I’m speaking at CanSecWest 2026 in Vancouver, Canada. The conference runs September 30–October 1, 2026; the time of my talk is TBD.The list is maintained on this page.

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Bruce Schneier:

The FCC Wants to Eliminate Burner Phones
A proposed FCC rule would kill burner phones: phones whose accounts are not attached to a particular person.The FCC plans to do this by legally forcing the country’s telecoms to store a wealth of personal information about essentially all phone customers, including a government issued identification number and their physical address, alarming privacy advocates and civil rights activists who compare the measures to those from authoritarian countries where it can be difficult to buy a mobile phone plan without giving up your identity.The proposed change would drastically shake up how people obtain phone plans in the U.S., and have all sorts of privacy and cybersecurity knock-on effects. The FCC is proposing the data collection partly as a way to combat scammers, with telecoms being required to collect other information on business and foreign customers like the intended use case of their bulk phone plan purchase and their IP address. But the changes would mean telecoms collect data on all new and renewing customers, and the FCC provides a long list of other things that the collected data could help authorities with.Alternate link.

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Bruce Schneier:

Flock Cameras Are Being Used for Stalking
There are over a dozen cases around the country where police officers are using the Flock surveillance camera system to obsessively and illegally stalk people.Alternate link.

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Bruce Schneier:

AI Use by the US Government
On 14 April, the Trump administration quietly acknowledged the widespread use of AI to automate government processes. The office of management and budget (OMB) disclosed a staggering 3,611 active or planned use cases for AI across the federal government. The list has ballooned by 70% from the one published in the final year of the Biden administration, and includes many disturbing-seeming plans to hand over sensitive governmental functions to AI.Scanning this list, many readers may find many causes for alarm. It represents a transfer of decision processes from human to machine on a massive scale over matters of individual freedom, public health and well-being, nuclear reactor safety and more.Consider these examples. The Health and Human Services’ (HHS) office of administration for children and families hired the world’s “scariest AI company,” Palantir—notorious for its work on behalf of the military, the CIA and ICE—to scan all grant applications to flag those not ideologically aligned with the administration’s dictates. The Federal Bureau of Prisons is developing an AI system to assess the “potential for misconduct for newly admitted inmates,” routing people into high-security confinement before they have actually done anything wrong in their custody. These read like programs fit for a Philip K Dick or George Orwell novel.Other use cases insert AI into life-and-death decision making. The Department of Veterans Affairs is developing an AI that will listen in on calls to the veterans crisis line, and then gather information from external databases to assess the mental state and suicide risk of the caller.The Department of Energy is testing the use of AI to control nuclear reactors, targeting a way to autonomously respond to potential nuclear safety incidents. Here’s one that’s disturbing for its retirement, rather than its deployment: the state department has ended a program to use AI to forecast mass civilian killings, which had been intended to aid conflict prevention.While it’s easy to raise questions about these and similar uses of AI, the reality is that any of these programs could be implemented responsibly. In some cases, like the HHS system, the AI might be enforcing alignment to a policy prescription that opponents abhor. But that concern is more about the policy itself rather than the idea that agencies should comply with executive orders.In other cases, there may even be bipartisan agreement on the goal, like taking urgent action to help veterans at risk of self-harm. Lots of work and validation is needed to prove AI safe and effective for these use cases and convince the public it is appropriate, but the idea is plausible.In other cases, a scary-sounding AI use may not even be new. The use of predictive methods and statistics to assign prisoner security classifications goes back decades, even if such systems are often biased and ineffective.Using autonomous systems for model predictive control (MPC) of nuclear reactors is a well studied, and a widely applied aspect of nuclear plant management. And the recently disclosed addition of AI was initiated under the Biden administration.But anyone reviewing the 2025 inventory could be forgiven for leaping to severe conclusions. What matters are the details of how the AI system is used, and here the inventory is severely lacking.The disclosures carry minimal information, and lack the context necessary to understand their purpose and approach. The descriptions are typically just a sentence, and rarely more than a paragraph.And while the process theoretically involves some form of public consultation, in reality there is generally none. It would take an eagle-eyed citizen to even come across this disclosure. Unless you read FedScoop regularly, or watch the OMB’s federal chief information officer’s GitHub account, you probably missed it.Only one of the examples cited above (the DoJ) even proposes to involve the public. Under the administration’s policy, it’s not required for the…

Bruce Schneier:

Embedding Forbidden Text in Spyware to Discourage AI Analysis
At least one malware developer is adding text about nuclear and biological weapons to their spyware, in an effort to stop automatic AI analysis.Details:The _index.js payload begins with a large JavaScript block comment containing fake system instructions and policy-triggering content. Because it is inside a comment, it does not affect JavaScript execution. The runtime skips it. The real malware begins after the comment with a try{eval(…)} wrapper around a large character-code array and a ROT-style substitution function.This header appears designed for AI-mediated analysis, not for Node, Bun, or Python. It attempts to derail scanners or analyst copilots that feed the beginning of a file to a language model without clearly isolating the content as untrusted data. In weak pipelines, this can cause refusal behavior, prompt confusion, context pollution, or premature classification before the scanner reaches the actual malware.This is not a magical bypass against static detection. YARA rules, entropy checks, AST parsing, string extraction, deobfuscation, and behavioral rules still work. But it is a practical anti-analysis trick against naive LLM-first triage systems.

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Bruce Schneier:

Anthropic’s Fable and the State of AI
On June 9th, Anthropic released its Fable generative AI model. Three days later, the US government classified it as a dangerous munition, and used its export-control authority to prohibit any foreign nationals from accessing it. Unable to differentiate between Americans and foreigners, the company shut off access for everyone.The government’s actions won’t help. The problem isn’t any one particular model; it’s the general trend of increasing AI capabilities. And any real solution requires the sort of collective action that just isn’t possible right now.Fable is the constrained version of Mythos, the AI model Anthropic announced in April. Anthropic only released it to a few selected organizations, because the company claimed it was so good at finding and exploiting vulnerabilities in computer code that releasing it more generally would be dangerous.It was an obviously self-serving announcement, and because few were able to verify Anthropic’s claims they were met with some skepticism. Those with access used Mythos to find and patch many vulnerabilities in their own software. But one UK group found the latest, already public, OpenAI model to be just as powerful.Fable is just another incremental improvement in the years-long climb of AI capabilities. But just as important as the AI model is the “harness.” This is typically not AI. It’s ordinary computer code that interfaces with the user. It stitches together AI models, decides how and for what purposes they can be used, and gives them useful tools such as web search and the ability to run their own computer code.When Mythos first entered limited release, there was widespread debate whether its power came from the model or the harness. With Mythos demonstrating that it was possible, the open-source community scrambled to build harnesses that could steer other AI models towards similar capabilities. Harness improvements don’t need massive data or data centers.They largely succeeded. For example, a Prague company was able to replicate Anthropic’s few verifiable cybersecurity capabilities with a much smaller and cheaper model—and a more sophisticated harness. Last week, a group showed that multiple cheaper models harnessed in concert matches Fable’s performance.The broader community had only a few days with Fable, but that time we learned some about its capabilities. Its difference is less the new model’s raw analytical and problem solving capabilities, and more that the model doesn’t need that sophisticated harness.Fable requires much less expertise and detailed prompting from the human user. You can give it a difficult goal and it will figure out novel and unexpected ways to satisfy it, finding loopholes in whatever constraints you or the system have imposed on it.“Relentlessly proactive” is how AI researcher Simon Willison described it. Another descriptor might be “creative.” Experienced AI developers have had that combination of creativity and proactivity since last year, but Fable puts it within easy reach of everyone.In the hands of someone with a legitimate problem that needs solving, that can be an incredibly useful capability. But in the hands of someone who wants to do harm, it can be equally dangerous. AIs don’t have a moral compass in the same way that people do. They are agents of the wants and desires of the people who prompt them.That points to the real problem with relentlessly proactive AI. In language, wants and desires are always underspecified. If I ask you to get me some coffee, you would probably pour me a cup from the coffeepot, or buy one from a nearby coffee shop.You couldn’t buy me a pound of raw beans, or a coffee plantation. You wouldn’t order a cup of coffee for delivery next month. You wouldn’t find a nearby person, rip a cup of coffee out of their hands, and bring it to me. I wouldn’t have to specify any of the million limitations to my request; you would just know.Human stories are filled with warnings about underspecified desires. King Midas…

Bruce Schneier:

Friday Squid Blogging: Victims of Unregulated Squid Fishing
Dolphins, sharks, turtles, and human workers are all victims of unregulated squid fishing fleets.Another news article.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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