Sufficiently Advanced Technology And Justice

Imagine that you’re serving on a jury, and you’re given an image taken from a surveillance camera. It looks pretty much like the suspect, but the image has been “enhanced” by an AI from the original. Do you convict? How does this weigh out on the scales of reasonable doubt? Should you demand to see the original?

AI-enhanced, upscaled, or otherwise modified images are tremendously realistic. But what they’re showing you isn’t reality. When we wrote about this last week, [Denis Shiryaev], one of the authors of one of the methods we highlighted, weighed in the comments to point out that these modifications aren’t “restorations” of the original. While they might add incredibly fine detail, for instance, they don’t recreate or restore reality. The neural net creates its own reality, out of millions and millions of faces that it’s learned.

And for the purposes of identification, that’s exactly the problem: the facial features of millions of other people have been used to increase the resolution. Can you identify the person in the pixelized image? Can you identify that same person in the resulting up-sampling? If the question put before the jury was “is the defendant a former president of the USA?” you’d answer the question differently depending on which image you were presented. And you’d have a misleading level of confidence in your ability to judge the AI-retouched photo. Clearly, informed skepticism on the part of the jury is required.

Unfortunately, we’ve all seen countless examples of “zoom, enhance” in movies and TV shows being successfully used to nab the perps and nail their convictions. We haven’t seen nearly as much detailed analysis of how adversarial neural networks create faces out of a scant handful of pixels. This, combined with the almost magical resolution of the end product, would certainly sway a jury of normal folks. On the other hand, the popularity of intentionally misleading “deep fakes” might help educate the public to the dangers of believing what they see when AI is involved.

This is just one example, but keeping the public interested in and educated on the deep workings and limitations of the technology that’s running our world is more important than ever before, but some of the material is truly hard. How do we separate the science from the magic?

The Protein Folding Break-Through

Researchers at DeepMind have proudly announced a major break-through in predicting static folded protein structures with a new program known as AlphaFold 2. Protein folding has been an ongoing problem for researchers since 1972. Christian Anfinsen speculated in his Nobel Prize acceptance speech in that year that the three-dimensional structure of a given protein should be algorithm determined by the one-dimensional DNA sequence that describes it. When you hear protein, you might think of muscles and whey powder, but the proteins mentioned here are chains of amino acids that fold into complex shapes. Cells use these proteins for almost everything. Many of the enzymes, antibodies, and hormones inside your body are folded proteins. We’ve discussed why protein folding is important as well covered recent advancements in cryo-electron microscopy used to experimentally determine the structure of folded proteins.

The shape of proteins largely controls their function, and if we can predict their shape then we get much closer to predicting how they interact. While AlphaFold 2 just predicts the static state, the sheer number of interactions that can change a protein, dynamic protein structures are still out of reach. The technical achievement of DeepMind is not to be understated. For a typical protein, there are an estimated 10^300 different configurations.

Out of the 180 million protein sequences in the Protein database, only 170,000 have had their structures identified. Technologies like the cryo-electron microscope make the process of mapping their structure easier, but it is still complex and tedious to go from sequence to structure. AlphaFold 2 and other folding algorithms are tested against this 170,000 member corpus to determine their accuracy. The previous highest-scoring algorithm of 2016 had a median global distance test (GDT) of 40 (0-100, with 100 being the best) in the most difficult category (free-modeling). In 2018, AlphaFold made waves by pushing that up to the high 50’s. AlphaFold 2 brings that GDT up to 87.

At this point in time, it is hard to determine what sort of effects this will have on the drug industry, healthcare, and society in general. Research has always been done to create the protein, identify what it does, then figure out its structure. AlphaFold 2 represents an avenue towards doing that whole process completely backward. Whether the next goal is to map all the proteins encoded in the human genome or find new, more effective drug treatments, we’re quite excited to see what becomes of this landmark breakthrough.

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This Week In Security: IOS Wifi Incantations, Ghosts, And Bad Regex

I hope everyone had a wonderful Thanksgiving last week. My household celebrated by welcoming a 4th member to the family. My daughter was born on Wednesday morning, November 25th. And thus explains what I did last week instead of writing the normal Hackaday column. Never fear, we shall catch up today, and cover the news that’s fit to be noticed.

iOS Zero-click Wifi Attack

[Ian Beer] of Google’s Project Zero brings us the fruit of his lockdown-induced labors, a spectacular iOS attack. The target of this attack is the kernel code that handles AWDL, an Apple WiFi protocol for adhoc mesh networks between devices. The most notable feature that makes use of AWDL is AirDrop, Apple’s device-to-device file sharing system. Because AWDL is a proprietary protocol, the WiFi hardware can’t do any accelerated processing of packets. A few years back, there was an attack against Broadcom firmware that required a second vulnerability to jump from the WiFi chip to the device CPU. Here, because the protocol is all implemented in Apple’s code, no such pivot is necessary.

And as you’ve likely deduced, there was a vulnerability found. AWDL uses Type-Length-Value (TLV) messages for sending management data. For a security researcher, TLVs are particularly interesting because each data type represents a different code path to attack. One of those data types is a list of MAC addresses, with a maximum of 10. The code that handles it allocates a 60 byte buffer, based on that maximum. The problem is that there isn’t a code path to drop incoming TLVs of that type when they exceed 60 bytes. The remainder is written right past the end of the allocated buffer.

There is more fun to be had, getting to a full exploit, but the details are a bit too much to fully dive in to here. It interesting to note that [Ian] ran into a particular problem: His poking at the target code was triggering unexpected kernel panics. He discovered two separate vulnerabilities, both distinct from the vuln he was trying to exploit.

Finally, this exploit requires the target device to have AWDL enabled, and many won’t. But you can use Bluetooth Low Energy advertisements to trick the target device into believing an Airdrop is coming in from a trusted contact. Once the device enables AWDL to verify the request, the attack can proceed. [Ian] reported his findings to Apple way back in 2019, and this vulnerability was patched in March of 2020.

Via Ars Technica.
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FTDI VCP Chips With Custom PIDs Not Working On MacOS 11 Big Sur

An anonymous reader pinged us about an issue that affects people who jumped onto the latest-and-greatest OS from the Apple gardens: USB devices that stop working due to the FTDI-based USB solution. At its core appears to be that the built-in FTDI driver provided by Apple (AppleUSBFTDI.dext) only supports FTDI chips which provide the standard FTDI vendor and product ID (e.g. 0x0403 and 0x6001 respectively for the FT232R). Many products however set a custom product ID (PID) to differentiate their device, though in the thread some mention that there are driver issues even with the default VID/PID combination.

Over the past years, Apple has been restricting and changing the way kernel extensions (KExt) and driver extensions (DExt) are handled. As these FTDI chips are often used for virtual com port (VCP) purposes, such as with Arduino boards and USB-TTL adapters, this is a rather cumbersome issue that would affect anyone using Big Sur in combination with such a hardware device.

So far only the FTDI team has been somewhat responsive based on the support forum thread, with Apple seemingly rather silent on the issue.

NSF Releases Video Of Arecibo’s Final Moments

Today the National Science Foundation released a pair of videos that document the collapse of the Arecibo Observatory with incredible detail. A wide shot, apparently taken from the Visitors Center, shows the 900 ton instrument platform breaking free and swinging on the remaining support cables until it smashes into the edge of the dish. The second clip, recorded by an airborne drone, is focused directly on the cables as they failed. Both can be seen in the video embedded below.

Together, they produce an invaluable visual record of what finally brought the iconic radio telescope down. As was predicted by engineers earlier in the month, the failure of another support cable on tower 4 triggered a chain reaction that brought the entire platform crashing down onto the 305 meter reflector. Footage from a drone observing the top of tower 4 shows that the entire sequence, from the first visual wire break to the remaining cables being torn from their mounts, only took five seconds. While some initially doubted the NSF’s determination that it was too dangerous to repair Arecibo, this footage seems to prove just how tenuous the structural integrity of the Observatory really was.

A drone captured the critical cable failure.

These videos will hopefully help investigators who still need to determine why the cables failed in the first place. The cable in August didn’t snap, it simply pulled lose from its mount. It was suspected that the cable may have been incorrectly installed, but as it was only a backup, the situation was not seen as critical. But when the second cable failed in November it was found to have snapped at just 60% of its minimum breaking strength.

This immediately called into question the condition of the remaining cables, and ultimately lead to the decision by the NSF to proceed with a controlled demolition of the Observatory that would preserve as much of the scientific equipment as possible. Unfortunately, the remaining cables didn’t last long enough to put that plan into action.

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Smart Screen Heal Thyself

The Korea Institute of Science and Technology (KIST) have announced a transparent, self-healing polyimide material designed for smart phone screens. A KIST team from the Composite Materials Applications Research Center led by Dr Yong-chae Jung and a team at Yonsei University’s Electronics Materials Lab led by Dr Hak-soo Han collaborated on this project. While the goal was to improve the material used in folding smart phone screens, the results seem applicable to all glass screens that are prone to cracks and scratches.

This new material can heal itself in 12 hours at room temperature, even faster under UV light. As we understand it, many micro-balloons of flaxseed oil are impregnated on the surface and break open if the material is damaged. Thus liberated, the oil is now free to flow into and fill up the cracks. We imagine it’s like repairing windshield cracks, but on a much smaller scale.

The idea is to eliminate the need for user-added screen protection films and increase the life of your phone screen. But cynical people might wonder if smart phone manufacturers will embrace this new technology with much enthusiasm — after all, if people use their phones longer it might cut into sales. Those with access to academic journals can read the report here.

European Right To Repair: Poor Repairability Shamed With Rating System

Happily the right to repair movement is slowly gaining ground, and recently they’ve scored a major success in the European Parliament that includes a requirement that products be labelled with expected lifetime and repairability information, long-term availability of parts, and numerous measures aimed at preventing waste.

… including by requiring improved product information through mandatory labelling on the durability and reparability of a product (expected lifetime, availability of spare parts, etc.), defining durability and reparability as the main characteristics of a product…

Even the UK, whose path is diverging from the EU due to Brexit, appears to have a moment of harmony on this front. This builds upon existing rights to repair in that devices sold in Europe will eventually have to carry a clearly visible repair score to communicate the ease of repairability and supply of spare parts, making a clear incentive for manufacturers to strive for the highest score possible.

We live in an age in which our machines, appliances, and devices are becoming ever more complex, while at the same time ever more difficult to repair. Our community are the masters of fixing things, but even we are becoming increasingly stumped in the face of the latest flashy kitchen appliance or iDevice. The right to repair movement, and this measure in particular, seeks to improve the ability of all consumers, not just us hackers, to makebuying decisions for better products and lower environmental impact.

With a population of around 450 million people spread across 27 member countries, the EU represents a colossal market that no manufacturer can afford to ignore. Therefore while plenty of other regions of the planet have no such legislation this move will have a knock-on effect across the whole planet. Since the same products are routinely sold worldwide it is to be expected that an improvement in repairability for European markets will propagate also to the rest of the world. So when your next phone has a replaceable battery and easier spares availability, thank the EU-based right to repair campaigners and some European lawmakers for that convenience.

European Parliament from EU, CC BY 2.0.