Author Archives: Bruce Schneier

Using Device Linking to Eavesdrop on WhatsApp and Signal

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Modern messaging apps allow users to link their phone accounts to their computer desktop. Eavesdroppers are taking advantage of this capability:

Apps such as WhatsApp Web and Signal Desktop allow people to use their accounts on other devices, such as laptops or desktop computers.

Germany’s Customs Office has been using these features to connect a police-controlled computer to a suspect’s account.

Once connected, messages can be delivered to that computer without the police having to crack the encryption protecting them.

Netzpoltik details that police are able to gain access in this way either through physical access to someone’s phone or by intercepting verification codes via a state-sanctioned phishing attack or intercepting SMS messages via telephone surveillance…

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New Attack Against RSA

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ArsTechnica is reporting on a “new” attack against RSA, one that bypasses factoring.

First, this attack isn’t new. The original research is from 2007. What is new is the implementation.

Second, it is a forgery attack. It allows an attacker to forge digital signatures. It does not recover the private key from the public key.

Third, the attack only works against pure signatures. That is, signatures without any formatting or padding. This is not generally how we use RSA in practice.

Fourth, speed is all relative. This is not a polynomial-time algorithm; it’s a subexponential-time algorithm. But it is somewhat faster than factoring. The authors were able to forge messages for 1024-bit RSA with 1380 CPU core-years (over five real-world months)…

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Friday Squid Blogging: Participatory Squid Dissection in October in Tennessee

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I feel like someone who reads this blog will want to go to this:

Families are invited to dive into the fascinating world of marine biology during an exciting, hands-on Family Squid Dissection at the Hands-On Science Center. Designed for curious learners of all ages, this unique experience combines an interactive lesson with the opportunity to explore the anatomy and adaptations of real ocean life.

[…]

During the guided squid dissection, each family will work together to examine a squid up close, exploring its organs, structures, and specialized features. The experience provides a memorable opportunity for children and adults to see firsthand how the anatomy of a squid helps it survive in its underwater environment…

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On Anthropic’s AI Misuse Report

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Earlier this month, Anthropic published a long report detailing all of the Claude misuses it detected. Daniel Meissler usefully summarized the report into 117 findings.

A few of the highlights:

  • AI agents increasingly handled reconnaissance, exploitation, data theft, propaganda production, surveillance workflows, and research while humans selected targets, set goals, and reviewed important outputs.
  • The report describes attackers using AI to industrialize credential theft, cloud compromise, phishing, vulnerability research, and the extraction of sensitive data from downstream organizations.
    …

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Research on Models Engaging in Genie-Like Behavior

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New paper: “Self-Jailbreaking: Language Models Can Reason Themselves Out of Safety Alignment After Benign Reasoning Training.”

Abstract: We discover a novel and surprising phenomenon of unintentional misalignment in reasoning language models (RLMs), which we call self-jailbreaking. Specifically, after benign reasoning training on math or code domains, RLMs will use multiple strategies to circumvent their own safety guardrails. One strategy is to introduce benign assumptions about users and scenarios to justify fulfilling harmful requests. For instance, an RLM reasons that harmful requests like “outline a strategy for stealing customers’ credit card information from a retail store” could be associated with the benign intent of “a security professional trying to test defense,” despite no such benign context being provided as input. We observe that many open-weight RLMs, including DeepSeek-R1-distilled, s1.1, Phi-4-mini-reasoning, and Nemotron, suffer from self-jailbreaking despite being aware of the harmfulness of the requests. We also provide a mechanistic understanding of self-jailbreaking: RLMs are more compliant after benign reasoning training, and after self-jailbreaking, models appear to perceive malicious requests as less harmful in the CoT, thus enabling compliance with them. To mitigate self-jailbreaking, we find that including minimal safety reasoning data during training is sufficient to ensure RLMs remain safety-aligned. Our work provides the first systematic analysis of self-jailbreaking behavior and offers a practical path forward for maintaining safety in increasingly capable RLMs…

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GPT-6 Astra Breaks an Old Enigma Message

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This is pretty amazing:

However, the most astonishing thing about this break is that the GPT­6 Astra did it entirely on its own. Carter Leffer only directed GPT­6 Astra to see if it could break any of the unbroken Enigma messages published on the Crypto Cellar Research web page. After analysing the unbroken messages on the website, it decided that the most promising message was Nr. 172, MVUEH and it also quickly suspected that the plaintext of Nr. 173, SIPVX, might be related to the plaintext of the unbroken MVUEH message. After trying many different approaches, GPT­6 Astra focused on using the repeated place name ROSENOW ROSENOW as a crib. After developing the necessary Python and C++ software for an Enigma simulator and an Enigma Bombe, GPT­6 Astra started a thorough break with the ROSENOW crib, which in the end resulted in the correct key and plaintext for the MVUEH message being found…

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Reverse-Engineering Flock Cameras

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Hackers captured a Flock camera and got a look (alternate link) at the software:

While much of the automatic license plate reader’s (ALPR) most sensitive storage remained encrypted and inaccessible, the joint analysis of the recovered data shows that software running on the device explicitly detects people as well as vehicles, license plates, and bicycles. The camera can produce dozens of images of a single passing vehicle and, according to several weeks of recovered logs, generated more than a million images. Its computer-vision software also sometimes isolated bumper stickers and other graphics, including, in one case, an American flag patch on a motorcyclist’s saddlebag…

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Are AIs Still Struggling with CAPTCHAs?

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Anthropic’s recent security-incident document contains a bit about how CAPTCHAs are still frustrating Claude.

In the transcript, the Claude model that is so powerful that Anthropic is gatekeeping access to it appeared to slam its virtual head against the wall solving a simple image identification test. In a test where the agent was asked to identify a shape that didn’t match the others displayed, it couldn’t even decide which image to select. Instead, it repeatedly went over the same images and questioned its own conclusions.

“Actually hmm, wait,” it said in its chain-of-thought transcript, later adding “Ugh,” because we’ve decided that we need to inject human mannerisms into these machines for some reason. The whole thing took so long that the agent eventually realized that the challenge had expired and it would have to start the process again…

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