Entries Tagged "cyberattack"

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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.

Posted on April 13, 2026 at 12:52 PM • View Comments

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.

Posted on April 2, 2026 at 1:28 PM • View Comments

New Attack Against Wi-Fi

It’s called AirSnitch:

Unlike previous Wi-Fi attacks, AirSnitch exploits core features in Layers 1 and 2 and the failure to bind and synchronize a client across these and higher layers, other nodes, and other network names such as SSIDs (Service Set Identifiers). This cross-layer identity desynchronization is the key driver of AirSnitch attacks.

The most powerful such attack is a full, bidirectional machine-in-the-middle (MitM) attack, meaning the attacker can view and modify data before it makes its way to the intended recipient. The attacker can be on the same SSID, a separate one, or even a separate network segment tied to the same AP. It works against small Wi-Fi networks in both homes and offices and large networks in enterprises.

With the ability to intercept all link-layer traffic (that is, the traffic as it passes between Layers 1 and 2), an attacker can perform other attacks on higher layers. The most dire consequence occurs when an Internet connection isn’t encrypted­—something that Google recently estimated occurred when as much as 6 percent and 20 percent of pages loaded on Windows and Linux, respectively. In these cases, the attacker can view and modify all traffic in the clear and steal authentication cookies, passwords, payment card details, and any other sensitive data. Since many company intranets are sent in plaintext, traffic from them can also be intercepted.

Even when HTTPS is in place, an attacker can still intercept domain look-up traffic and use DNS cache poisoning to corrupt tables stored by the target’s operating system. The AirSnitch MitM also puts the attacker in the position to wage attacks against vulnerabilities that may not be patched. Attackers can also see the external IP addresses hosting webpages being visited and often correlate them with the precise URL.

Here’s the paper.

Posted on March 9, 2026 at 6:57 AM • View Comments

A Cyberattack Was Part of the US Assault on Venezuela

We don’t have many details:

President Donald Trump suggested Saturday that the U.S. used cyberattacks or other technical capabilities to cut power off in Caracas during strikes on the Venezuelan capital that led to the capture of Venezuelan President Nicolás Maduro.

If true, it would mark one of the most public uses of U.S. cyber power against another nation in recent memory. These operations are typically highly classified, and the U.S. is considered one of the most advanced nations in cyberspace operations globally.

Posted on January 6, 2026 at 11:08 AM • View Comments

Denmark Accuses Russia of Conducting Two Cyberattacks

News:

The Danish Defence Intelligence Service (DDIS) announced on Thursday that Moscow was behind a cyber-attack on a Danish water utility in 2024 and a series of distributed denial-of-service (DDoS) attacks on Danish websites in the lead-up to the municipal and regional council elections in November.

The first, it said, was carried out by the pro-Russian group known as Z-Pentest and the second by NoName057(16), which has links to the Russian state.

Slashdot thread.

Posted on December 23, 2025 at 7:02 AM • View Comments

AI as Cyberattacker

From Anthropic:

In mid-September 2025, we detected suspicious activity that later investigation determined to be a highly sophisticated espionage campaign. The attackers used AI’s “agentic” capabilities to an unprecedented degree­—using AI not just as an advisor, but to execute the cyberattacks themselves.

The threat actor—­whom we assess with high confidence was a Chinese state-sponsored group—­manipulated our Claude Code tool into attempting infiltration into roughly thirty global targets and succeeded in a small number of cases. The operation targeted large tech companies, financial institutions, chemical manufacturing companies, and government agencies. We believe this is the first documented case of a large-scale cyberattack executed without substantial human intervention.

[…]

The attack relied on several features of AI models that did not exist, or were in much more nascent form, just a year ago:

  1. Intelligence. Models’ general levels of capability have increased to the point that they can follow complex instructions and understand context in ways that make very sophisticated tasks possible. Not only that, but several of their well-developed specific skills—in particular, software coding­—lend themselves to being used in cyberattacks.
  2. Agency. Models can act as agents—­that is, they can run in loops where they take autonomous actions, chain together tasks, and make decisions with only minimal, occasional human input.
  3. Tools. Models have access to a wide array of software tools (often via the open standard Model Context Protocol). They can now search the web, retrieve data, and perform many other actions that were previously the sole domain of human operators. In the case of cyberattacks, the tools might include password crackers, network scanners, and other security-related software.

Posted on November 21, 2025 at 7:01 AM • View Comments

Prompt Injection in AI Browsers

This is why AIs are not ready to be personal assistants:

A new attack called ‘CometJacking’ exploits URL parameters to pass to Perplexity’s Comet AI browser hidden instructions that allow access to sensitive data from connected services, like email and calendar.

In a realistic scenario, no credentials or user interaction are required and a threat actor can leverage the attack by simply exposing a maliciously crafted URL to targeted users.

[…]

CometJacking is a prompt-injection attack where the query string processed by the Comet AI browser contains malicious instructions added using the ‘collection’ parameter of the URL.

LayerX researchers say that the prompt tells the agent to consult its memory and connected services instead of searching the web. As the AI tool is connected to various services, an attacker leveraging the CometJacking method could exfiltrate available data.

In their tests, the connected services and accessible data include Google Calendar invites and Gmail messages and the malicious prompt included instructions to encode the sensitive data in base64 and then exfiltrate them to an external endpoint.

According to the researchers, Comet followed the instructions and delivered the information to an external system controlled by the attacker, evading Perplexity’s checks.

I wrote previously:

Prompt injection isn’t just a minor security problem we need to deal with. It’s a fundamental property of current LLM technology. The systems have no ability to separate trusted commands from untrusted data, and there are an infinite number of prompt injection attacks with no way to block them as a class. We need some new fundamental science of LLMs before we can solve this.

Posted on November 11, 2025 at 7:08 AM • View Comments

Autonomous AI Hacking and the Future of Cybersecurity

AI agents are now hacking computers. They’re getting better at all phases of cyberattacks, faster than most of us expected. They can chain together different aspects of a cyber operation, and hack autonomously, at computer speeds and scale. This is going to change everything.

Over the summer, hackers proved the concept, industry institutionalized it, and criminals operationalized it. In June, AI company XBOW took the top spot on HackerOne’s US leaderboard after submitting over 1,000 new vulnerabilities in just a few months. In August, the seven teams competing in DARPA’s AI Cyber Challenge collectively found 54 new vulnerabilities in a target system, in four hours (of compute). Also in August, Google announced that its Big Sleep AI found dozens of new vulnerabilities in open-source projects.

It gets worse. In July Ukraine’s CERT discovered a piece of Russian malware that used an LLM to automate the cyberattack process, generating both system reconnaissance and data theft commands in real-time. In August, Anthropic reported that they disrupted a threat actor that used Claude, Anthropic’s AI model, to automate the entire cyberattack process. It was an impressive use of the AI, which performed network reconnaissance, penetrated networks, and harvested victims’ credentials. The AI was able to figure out which data to steal, how much money to extort out of the victims, and how to best write extortion emails.

Another hacker used Claude to create and market his own ransomware, complete with “advanced evasion capabilities, encryption, and anti-recovery mechanisms.” And in September, Checkpoint reported on hackers using HexStrike-AI to create autonomous agents that can scan, exploit, and persist inside target networks. Also in September, a research team showed how they can quickly and easily reproduce hundreds of vulnerabilities from public information. These tools are increasingly free for anyone to use. Villager, a recently released AI pentesting tool from Chinese company Cyberspike, uses the Deepseek model to completely automate attack chains.

This is all well beyond AIs capabilities in 2016, at DARPA’s Cyber Grand Challenge. The annual Chinese AI hacking challenge, Robot Hacking Games, might be on this level, but little is known outside of China.

Tipping point on the horizon

AI agents now rival and sometimes surpass even elite human hackers in sophistication. They automate operations at machine speed and global scale. The scope of their capabilities allows these AI agents to completely automate a criminal’s command to maximize profit, or structure advanced attacks to a government’s precise specifications, such as to avoid detection.

In this future, attack capabilities could accelerate beyond our individual and collective capability to handle. We have long taken it for granted that we have time to patch systems after vulnerabilities become known, or that withholding vulnerability details prevents attackers from exploiting them. This is no longer the case.

The cyberattack/cyberdefense balance has long skewed towards the attackers; these developments threaten to tip the scales completely. We’re potentially looking at a singularity event for cyber attackers. Key parts of the attack chain are becoming automated and integrated: persistence, obfuscation, command-and-control, and endpoint evasion. Vulnerability research could potentially be carried out during operations instead of months in advance.

The most skilled will likely retain an edge for now. But AI agents don’t have to be better at a human task in order to be useful. They just have to excel in one of four dimensions: speed, scale, scope, or sophistication. But there is every indication that they will eventually excel at all four. By reducing the skill, cost, and time required to find and exploit flaws, AI can turn rare expertise into commodity capabilities and gives average criminals an outsized advantage.

The AI-assisted evolution of cyberdefense

AI technologies can benefit defenders as well. We don’t know how the different technologies of cyber-offense and cyber-defense will be amenable to AI enhancement, but we can extrapolate a possible series of overlapping developments.

Phase One: The Transformation of the Vulnerability Researcher. AI-based hacking benefits defenders as well as attackers. In this scenario, AI empowers defenders to do more. It simplifies capabilities, providing far more people the ability to perform previously complex tasks, and empowers researchers previously busy with these tasks to accelerate or move beyond them, freeing time to work on problems that require human creativity. History suggests a pattern. Reverse engineering was a laborious manual process until tools such as IDA Pro made the capability available to many. AI vulnerability discovery could follow a similar trajectory, evolving through scriptable interfaces, automated workflows, and automated research before reaching broad accessibility.

Phase Two: The Emergence of VulnOps. Between research breakthroughs and enterprise adoption, a new discipline might emerge: VulnOps. Large research teams are already building operational pipelines around their tooling. Their evolution could mirror how DevOps professionalized software delivery. In this scenario, specialized research tools become developer products. These products may emerge as a SaaS platform, or some internal operational framework, or something entirely different. Think of it as AI-assisted vulnerability research available to everyone, at scale, repeatable, and integrated into enterprise operations.

Phase Three: The Disruption of the Enterprise Software Model. If enterprises adopt AI-powered security the way they adopted continuous integration/continuous delivery (CI/CD), several paths open up. AI vulnerability discovery could become a built-in stage in delivery pipelines. We can envision a world where AI vulnerability discovery becomes an integral part of the software development process, where vulnerabilities are automatically patched even before reaching production—a shift we might call continuous discovery/continuous repair (CD/CR). Third-party risk management (TPRM) offers a natural adoption route, lower-risk vendor testing, integration into procurement and certification gates, and a proving ground before wider rollout.

Phase Four: The Self-Healing Network. If organizations can independently discover and patch vulnerabilities in running software, they will not have to wait for vendors to issue fixes. Building in-house research teams is costly, but AI agents could perform such discovery and generate patches for many kinds of code, including third-party and vendor products. Organizations may develop independent capabilities that create and deploy third-party patches on vendor timelines, extending the current trend of independent open-source patching. This would increase security, but having customers patch software without vendor approval raises questions about patch correctness, compatibility, liability, right-to-repair, and long-term vendor relationships.

These are all speculations. Maybe AI-enhanced cyberattacks won’t evolve the ways we fear. Maybe AI-enhanced cyberdefense will give us capabilities we can’t yet anticipate. What will surprise us most might not be the paths we can see, but the ones we can’t imagine yet.

This essay was written with Heather Adkins and Gadi Evron, and originally appeared in CSO.

Posted on October 10, 2025 at 7:06 AM • View Comments

Daniel Miessler on the AI Attack/Defense Balance

His conclusion:

Context wins

Basically whoever can see the most about the target, and can hold that picture in their mind the best, will be best at finding the vulnerabilities the fastest and taking advantage of them. Or, as the defender, applying patches or mitigations the fastest.

And if you’re on the inside you know what the applications do. You know what’s important and what isn’t. And you can use all that internal knowledge to fix things­—hopefully before the baddies take advantage.

Summary and prediction

  1. Attackers will have the advantage for 3-5 years. For less-advanced defender teams, this will take much longer.
  2. After that point, AI/SPQA will have the additional internal context to give Defenders the advantage.

LLM tech is nowhere near ready to handle the context of an entire company right now. That’s why this will take 3-5 years for true AI-enabled Blue to become a thing.

And in the meantime, Red will be able to use publicly-available context from OSINT, Recon, etc. to power their attacks.

I agree.

By the way, this is the SPQA architecture.

Posted on October 2, 2025 at 12:19 PM • View Comments

US Disrupts Massive Cell Phone Array in New York

This is a weird story:

The US Secret Service disrupted a network of telecommunications devices that could have shut down cellular systems as leaders gather for the United Nations General Assembly in New York City.

The agency said on Tuesday that last month it found more than 300 SIM servers and 100,000 SIM cards that could have been used for telecom attacks within the area encompassing parts of New York, New Jersey and Connecticut.

“This network had the power to disable cell phone towers and essentially shut down the cellular network in New York City,” said special agent in charge Matt McCool.

The devices were discovered within 35 miles (56km) of the UN, where leaders are meeting this week.

McCool said the “well-organised and well-funded” scheme involved “nation-state threat actors and individuals that are known to federal law enforcement.”

The unidentified nation-state actors were sending encrypted messages to organised crime groups, cartels and terrorist organisations, he added.

The equipment was capable of texting the entire population of the US within 12 minutes, officials say. It could also have disabled mobile phone towers and launched distributed denial of service attacks that might have blocked emergency dispatch communications.

The devices were seized from SIM farms at abandoned apartment buildings across more than five sites. Officials did not specify the locations.

Wait; seriously? “Special agent in charge Matt McCool”? If I wanted to pick a fake-sounding name, I couldn’t do better than that.

Wired has some more information and a lot more speculation:

The phenomenon of SIM farms, even at the scale found in this instance around New York, is far from new. Cybercriminals have long used the massive collections of centrally operated SIM cards for everything from spam to swatting to fake account creation and fraudulent engagement with social media or advertising campaigns.

[…]

SIM farms allow “bulk messaging at a speed and volume that would be impossible for an individual user,” one telecoms industry source, who asked not to be named due to the sensitivity of the Secret Service’s investigation, told WIRED. “The technology behind these farms makes them highly flexible—SIMs can be rotated to bypass detection systems, traffic can be geographically masked, and accounts can be made to look like they’re coming from genuine users.”

Posted on September 24, 2025 at 7:09 AM • View Comments

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Sidebar photo of Bruce Schneier by Joe MacInnis.