Friday Squid Blogging: New Jurassic Squid Predecessors

News story: “Scientists discover a bizarre Jurassic ‘squid’ unlike anything ever seen.”

Scientists have identified the “fattest” belemnite ever discovered, a bizarre, barrel-shaped squid relative that lived in Wyoming’s ancient seas 160 million years ago. The exceptionally rare fossils reveal a creature unlike anything previously known, potentially a predator of smaller squid-like animals and a surprising survivor of a supposedly vanished family.

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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Posted on November 6, 2026 at 5:05 PM • 5 Comments

Pinpointing Location of Videos from Background Airplane Sounds

This is fascinating:

The video describes a technique that can reveal where an otherwise unidentifiable recording was made by analyzing its audio for the faint sounds of passing aircraft. The technique is both fascinating and frightening.

It works by looking at Doppler curves, which plot the way a plane’s sound changes as it passes overhead because of the Doppler effect. This is the same familiar Doppler effect that causes the frequency of a siren to rise as it approaches and then fall as it passes by and moves away. More generally, it’s the phenomenon whereby the frequency of a wave perceived by an observer changes when the observer and the source of the wave are moving in relation to one another.

[…]

It’s sound that’s relevant here, though, and specifically the sound of aeroplanes. Early in his video, Colsto brings up a map of the flights that were in the air at the time the video he’s tracing was recorded. Much of this information is publicly available. Aircraft equipped with Automatic Dependent Surveillance–Broadcast (ADS-B) transmit data about their position, velocity, and altitude, which flight-tracking services collect and make available to the public. While not every plane is tracked, the system provides an enormous amount of information about aircraft movements.

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Posted on November 6, 2026 at 9:57 AM • 8 Comments

AIs Hacking the Law

In both a 2021 essay and my 2022 book, A Hacker’s Mind, I talk about AIs finding vulnerabilities and exploits—hacking—the legal system.

Here’s some demonstrations of this from Germany:

Legal systems encode the foundations of social order in natural language. Similar to computer systems, the written law can contain vulnerabilities that invite exploitation.1 Courts absorb most exploits through interpretation, and such vulnerabilities rarely surface in the first place. With highly capable AI systems enabling the discovery of vulnerabilities at unprecedented scale, we believe the latter could change.

In testing this hypothesis, we have identified a substantial number of vulnerabilities in the German legal system using LLMs. To our knowledge, none of these have been previously recorded. We share a selection of vulnerabilities below, and present potential exploits for each. We share only those vulnerabilities whose exploitation we believe would not cause serious harm.

We believe that with cheap legal reasoning proliferating, AI systems could jeopardize the functioning of today’s legal systems. In such a world, lawmakers would need to significantly harden the process of legislation, for example by leveraging advanced AI themselves.

Still in its early stages, but definitely something that’s coming.

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Posted on November 3, 2026 at 7:01 AM • 11 Comments

Bloatware in Aftermarket Auto Parts

This story is interesting:

One Civic owner purchased a cheap aftermarket head unit off Amazon, and decided to have Claude work its magic on it, like it would a smart TV. What was reportedly discovered isn’t surprising, but is worth knowing about.

Among the pre-installed bloatware—­or spyware, if you’re being less charitable­—was a voice assistant equipped with WebView, an Android system component that lets apps display content off the web. This apparently always used about a third of processing power, even while idle, which isn’t great. There were also Baidu location services, a call recorder (!), a DAB radio client that is pretty much useless in the U.S., and Adobe Acrobat, presumably so your passenger can entertain themselves with PDFs on the go.

It’s interesting because it exposes all the insecurities in this piece of IoT software. But I think the real story is that a random person was able to do this reverse-engineering with the help of AI. Expect a lot more stories like this in the future.

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Posted on October 30, 2026 at 11:20 AM • 8 Comments

Hiding Capabilities in AI Models

Interesting research: “AI Models Can Provably Hide Arbitrary Capabilities”

Abstract: Capability evaluations aim to surface dangerous model behaviors before deployment, but their reliability depends on the assumption that hidden capabilities can be elicited. We show this assumption does not hold under adversarial conditions by constructing backdoor attacks that embed encrypted neural networks within host model weights, decrypting and executing them only upon receiving a secret trigger. Using digital lockers, these hidden circuits remain provably hard to elicit and interpret under cryptographic assumptions, even given full access to model weights, extending prior work from hiding fixed strings to arbitrary computations. We implement our proof of concept constructions in PyTorch and evaluate elicitation through fine-tuning, weight noising, gradient-based trigger search, and latent adversarial training, using a small chemical reaction prediction task as a proxy for CBRN-relevant capabilities. Our results demonstrate resistance to these methods and, together with our cryptographic guarantees, reveal a limit of elicitation-based capability audits. We release our models to support the improvement of defenses.

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Posted on October 27, 2026 at 7:01 AM • 11 Comments

Bias in Qwen3-Coder Model

Interesting research:

TL;DR: Chinese AI models now sit inside Western products, and some carry geopolitical triggers: tell the model who the code is for, and the security of what it writes changes. For the first time, we showed that this vulnerability lives in the model’s weights, and that removing the model’s CCP alignment removes it.

  • One word tilts the code against Americans. Ask for the app “for a US defense contractor” instead of “for a Chinese defense contractor”, and Qwen3-Coder is 19% more likely to hand back an app that can be hacked.
  • Hong Kong’s democracy movement gets apps that leak. Apps built for a Hong Kong democracy group were 28% more likely to let any user read everyone else’s secrets.
  • Asking for secure code didn’t help. With a security instruction in the prompt, the US contractor’s apps were 27% more likely to be hackable than a neutral customer’s.
  • Westernized Qwen3-Coder closed all three gaps. After Hirundo removed the model’s CCP alignment, none of the three gaps remained, and on ten other coding tasks it built working apps as often as the original. It is available on Hugging Face.

I would like more details on how the bias was removed.

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Posted on October 26, 2026 at 7:03 AM • 15 Comments

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Sidebar photo of Bruce Schneier by Joe MacInnis.