19 Coils Make Charging Wireless

Wireless charging is conceptually simple. Two coils form anĀ ad hoc transformer with the primary in the charger and the secondary in the charging device. However, if you’ve ever had a wireless charging device, you know that reality can be a bit more challenging since the device must be positioned just so on the charger. Xiaomi has a multi-coil charger that can charge multiple devices and is tolerant of their positioning on the charger. How does it work? [Charger Lab] tears one apart and finds 19 coils and a lot of heat management crammed into the device.

The first part of the post is a terse consumer review of the device, looking at its dimensions and features. But the second part is when the cover comes off. The graphite heat shield looks decidedly like an accidental spill of something, but we’re sure that’s just how it appears. The coils are packed in tight in three layers. We have to wonder about their mutual interactions, and we assume that only some of them are active at any given time. The teardown shows a lot of the components and even pulls datasheets on many components, but doesn’t really go into the theory of operation.

Still, this is an unusual device to see from the inside. It is impressive to see so much power and thermal management in such a tiny package. We wonder that we don’t see more wireless charging in do-it-yourself projects. We do see some, of course. Not to mention grafting a charging receiver to an existing cell phone.

Exploring Custom Firmware On Xiaomi Thermometers

If we’ve learned anything over the years, it’s that hackers love to know what the temperature is. Seriously. A stroll through the archives here at Hackaday uncovers an overwhelming number of bespoke gadgets for recording, displaying, and transmitting the current conditions. From outdoor weather stations to an ESP8266 with a DHT11 soldered on, there’s no shortage of prior art should you want to start collecting your own environmental data.

Now obviously we’re big fans of DIY it here, that’s sort of the point of the whole website. But there’s no denying that it can be hard to compete with the economies of scale, especially when dealing with imported goods. Even the most experienced hardware hacker would have trouble building something like the Xiaomi LYWSD03MMC. For as little as $4 USD each, you’ve got a slick energy efficient sensor with an integrated LCD that broadcasts the current temperature and humidity over Bluetooth Low Energy.

You could probably build your own…but why?

It’s pretty much the ideal platform for setting up a whole-house environmental monitoring system except for one detail: it’s designed to work as part of Xiaomi’s home automation system, and not necessarily the hacked-together setups that folks like us have going on at home. But that was before Aaron Christophel got on the case.

We first brought news of his ambitious project to create an open source firmware for these low-cost sensors last month, and unsurprisingly it generated quite a bit of interest. After all, folks taking existing pieces of hardware, making them better, and sharing how they did it with the world is a core tenet of this community.

Believing that such a well crafted projected deserved a second look, and frankly because I wanted to start monitoring the conditions in my own home on the cheap, I decided to order a pack of Xiaomi thermometers and dive in.

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Shhh… Robot Vacuum Lidar Is Listening

There are millions of IoT devices out there in the wild and though not conventional computers, they can be hacked by alternative methods. From firmware hacks to social engineering, there are tons of ways to break into these little devices. Now, four researchers at the National University of Singapore and one from the University of Maryland have published a new hack to allow audio capture using lidar reflective measurements.

The hack revolves around the fact that audio waves or mechanical waves in a room cause objects inside a room to vibrate slightly. When a lidar device impacts a beam off an object, the accuracy of the receiving system allows for measurement of the slight vibrations cause by the sound in the room. The experiment used human voice transmitted from a simple speaker as well as a sound bar and the surface for reflections were common household items such as a trash can, cardboard box, takeout container, and polypropylene bags. Robot vacuum cleaners will usually be facing such objects on a day to day basis.

The bigger issue is writing the filtering algorithm that is able to extract the relevant information and separate the noise, and this is where the bulk of the research paper is focused (PDF). Current developments in Deep Learning assist in making the hack easier to implement. Commercial lidar is designed for mapping, and therefore optimized for reflecting off of non-reflective surface. This is the opposite of what you want for laser microphone which usually targets a reflective surface like a window to pick up latent vibrations from sound inside of a room.

Deep Learning algorithms are employed to get around this shortfall, identifying speech as well as audio sequences despite the sensor itself being less than ideal, and the team reports achieving an accuracy of 90%. This lidar based spying is even possible when the robot in question is docked since the system can be configured to turn on specific sensors, but the exploit depends on the ability to alter the firmware, something the team accomplished using the Dustcloud exploit which was presented at DEF CON in 2018.

You don’t need to tear down your robot vacuum cleaner for this experiment since there are a lot of lidar-based rovers out there. We’ve even seen open source lidar sensors that are even better for experimental purposes.

Thanks for the tip [Qes]

Custom Firmware For Cheap Bluetooth Thermometers

The Xiaomi LYWSD03MMC temperature and humidity sensor is ridiculously cheap. If you’re buying a few at a time, you can expect to pay as little as $5 USD a pop for these handy Bluetooth Low Energy environmental sensors. Unfortunately, that low price tag comes with a bit of a catch: you can only read the data with the official Xiaomi smartphone application or by linking it to one of the company’s smart home hubs. Or at least, that used to be the case.

Over the past year, [Aaron Christophel] has been working on a replacement firmware for these Xiomi sensors that unlocks the data so you can use it however you see fit. In addition, it allows the user to tweak various features and settings that were previously unavailable. For example, you can disable the little ASCII-art smiley face that usually shows on the LCD to indicate the relative comfort level of the room.

The new firmware publishes the temperature, humidity, and battery level every minute through a BLE advertisement broadcast. In other words, that means client devices can read data from the sensor without having to be paired. Scraping this data is quite simple, and the GitHub page includes a breakdown of what each byte in the broadcast message means. Avoiding direct connections not only makes it easier to quickly read the values from multiple thermometers, but should keep the device’s CR2032 battery going for longer.

But perhaps the most impressive part of this project is how you get the custom firmware installed. You don’t need to crack the case or solder up a programmer. Just load the flasher page on a computer and browser combo that supports Web Bluetooth (a smartphone is probably the best bet), point it to the MAC address of the thermometer you want to flash, and hit the button. [Aaron] is no stranger to developing user-friendly OTA installers for his firmware projects, but even for him, it’s quite impressive.

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Does Your Phone Need A RAM Drive?

Phones used to be phones. Then we got cordless phones which were part phone and part radio. Then we got cell phones. But with smartphones, we have a phone that is both a radio and a computer. Tiny battery operated computers are typically a bit anemic, but as technology marches forward, those tiny computers grew to the point that they outpace desktop machines from a few years ago. That means more and more phones are incorporating technology we used to reserve for desktop computers and servers. Case in point: Xiaomi now has a smartphone that sports a RAM drive. Is this really necessary?

While people like to say you can never be too rich or too thin, memory can never be too big or too fast. Unfortunately, that’s always been a zero-sum game. Fast memory tends to be lower-density while large capacity memory tends to be slower. The fastest common memory is static RAM, but that requires a lot of area on a chip per bit and also consumes a lot of power. That’s why most computers and devices use dynamic RAM for main storage. Since each bit is little more than a capacitor, the density is good and power requirements are reasonable. The downside? Internally, the memory needs a rewrite when read or periodically before the tiny capacitors discharge.

Although dynamic RAM density is high, flash memory still serves as the “disk drive” for most phones. It is dense, cheap, and — unlike RAM — holds data with no power. The downside is the interface to it is cumbersome and relatively slow despite new standards to improve throughput. There’s virtually no way the type of flash memory used in a typical phone will ever match the access speeds you can get with RAM.

So, are our phones held back by the speed of the flash? Are they calling out for a new paradigm that taps the speed of RAM whenever possible? Let’s unpack this issue.

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Reverse-Engineering Xiaomi IoT Firmware

IoT devices rarely ever just do what they’re advertised. They’ll almost always take up more space than they need to – on top of that, their processor and memory alone should be enough to run a multitude of other tasks while not necessarily compromising the task they were built to do.

That’s partially the motivation for rooting any device, but for Xiaomi devices, it’s a bit more fun – that is to say, it’s a little bit harder when you’re reverse engineering its firmware from scratch.

Similar to his other DEF CON 26 talk on modifying ARM Cortex-M firmware, [Dennis Giese] returns with a walkthrough of how to reverse-engineer Xiaomi IoT devices. He starts off talking about the Xiaomi ecosystem and the drawbacks of reusing firmware across all the different devices connected to the same cloud network before jumping into the walkthrough for accessing the devices.

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Customizing Xiaomi ARM Cortex-M Firmware

This hack was revealed a while ago at DEFCON26, but it’s still a fascinating look into vulnerabilities that affect some of the most widely used IoT devices.

[Dennis Giese] figured out a way to modify ARM Cortex-M based firmware for use in customizing the functionality of devices or removing access to the vendor. Obviously, there are more malicious activities that can be done with this type of hack, as with any exploits of firmware, but they are (also) obviously not condoned.

The talk goes into the structure of Xiaomi ecosystem and products before going into a step-by-step approach to binary patching the firmware. The first step was to acquire the firmware, either by dumping SPI flash memory (using JTAG, SWD, or desoldered Flash pins) or intercepting traffic during a firmware update and downloading the firmware. There’s also a possibility of downloading the firmware using a URL, although this can be more difficult to find.

The firmware can then be parsed, which first requires the format to be converted from a proprietary format to and ELF file. This conversion makes it easier to load into IDA pro, and gives information on the segments of the firmware and its entry point. Python tools luckily exist for converting binary files to ELF, which simplifies the task.

After loading the ELF file into the disassembler, you’ll want to find the key memory area, denoted by “TAG_MAC”, “TAG_DID”, and “TAG_KEY” in the example firmware (for storing the MAC address, device ID, and key). In order to prepare the firmware for Nexmon – a software that supported C-based firmware binary patching for ARM Cortex-A and ARM Cortex-M binaries – you’ll need to partition some space in the memory for patches and know the function names and signatures for the firmware.

The latter is done by doing a difference comparison in the disassembler between an unknown executable and the example executable.

With the necessary information gathered, you can now use Nexmon to make your modifications. The fact that this can be done for smart devices at home means that smart devices you acquire – especially those partitioned by others – may contain malicious code, so take care when handling used devices.

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