A screenshot of the drone monitoring application, showing spoofed drones and their coordinates

Can’t Disable DJI Drone ID? Spoof It With An ESP!

We have been alerted to a fun tool, a DJI DroneID spoofer software for ESP8266/ESP32 and some other popular MCUs. Last year, we’ve told you about DJI DroneID — a technology DJI added to their drones, which broadcasts data including the drone operator’s GPS position, which, in turn, appears to have resulted in Ukrainian casualties in the Ukraine war. The announcement tweet states that DJI has added mechanisms from downgrading firmware. Hence, the spoofer.

There’s no other hardware needed, well other than an ESP8266 or ESP32 devboard, anyway. After the break you can find a video tutorial from [Joshua Bardwell] that shows you how to upload the code using Arduino IDE, and even going through coordinate tweaks. If you ever reminisced about the concept of throwies and were wondering what kind of useful, well, there’s your answer: clone the Git repo, compile it, program some interesting coordinates in, and witness the imaginary drones fly.

All in all, we get a lovely addition to our shenanigan toolkits. Surely, someone could use a neural network to distinguish real drones from fake ones, but it’s nothing that can’t be solved with a bit of code. Looking for a less daring hack? Well, you can always add some automation to your DJI drone by poking at the RGB LED signals.

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Screenshot of the SDR software in action, with decoded data in a terminal, and a map that shows the location received from the decoded data

Loudmouth DJI Drones Tell Everyone Where You Are

Back when commercial quadcopters started appearing in the news on the regular, public safety was a talking point. How, for example, do we keep them away from airports? Well, large drone companies didn’t want the negative PR, so some voluntarily added geofencing and tracking mechanisms to their own drones.

When it comes to DJI, one such mechanism is DroneID: a beacon on the drone itself, sending out a trove of data, including its operator’s GPS location. DJI also, of course, sells the Aeroscope device that receives and decodes DroneID data, declared to be for government use. As it often is with privacy-compromising technology, turns out it’s been a bigger compromise than we expected.

Questions started popping up last year, as off-the-shelf quadcopters (including those made by DJI) started to play a part in the Russo-Ukrainian War. It didn’t take long for Ukrainian forces to notice that launching a DJI drone led to its operators being swiftly attacked, and intel was that Russia got some Aeroscopes from Syria. DJI’s response was that their products were not meant to be used this way, and shortly thereafter cut sales to both Russia and Ukraine.

But security researchers have recently discovered the situation was actually worse than we expected. Back in 2022, DJI claimed that the DroneID data was encrypted, but [Kevin Finisterre]’s research proved that to be a lie — with the company finally admitting to it after Verge pushed them on the question. It wouldn’t even be hard to implement a worse-than-nothing encryption that holds up mathematically. However, it seems, DroneID doesn’t even try: here’s a GitHub repository with a DroneID decoder you can use if you have an SDR dongle.

Sadly, the days of companies like DJI standing up against the anti-copter talking points seem to be over, Now they’re setting an example on how devices can subvert their owners’ privacy without reservation. Looks like it’s up to hackers on the frontlines to learn how to excise DroneID, just like we’ve done with the un-nuanced RF power limitations, or the DJI battery DRM, or transplanting firmware between hardware-identical DJI flight controller models.

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Modular Anti-Drone Drone Sacrifices Itself For Self Defense

Part Racing Drone, Part RC Airplane, Part Rocket…all Menace. How else could you describe a quadcopter that shoots off at high speed and is designed for taking down other small quadcopters? The Interceptor Drone by [Aleksey] borrows elements from all of the aforementioned disciplines of flying things.

Built with standard racing drone parts, [Aleksey] assures that no prohibited parts are used in its construction. Instead, the Interceptor Drone relies on a very powerful motors and a light weight frame to keep the power to weight ratio in the “rocketing into the sky” category.

A close up shows the details: Detachable motors and rotors and the stowed net.

But what Interceptor Drone would be complete without a way to take its target out of the sky? This is where the biggest divergences begin. The motors are all oriented to point away from the center-line of the craft. Upon command, these motors actually detach from the frame, each spreading out and deploying the corner of a net that’s designed to entangle the rotors of the target, causing its battle with gravity to come to a grinding halt.

How does the Interceptor Drone survive the attack? Without its motors, the core of the quadcopter falls to the earth. Arresting the fall is a parachute much like those used in model rocketry. An audio beacon sounds the alarm to help somebody to find it — a move taken straight from the RC aircraft hobby.

There’s certainly a lot of room to discuss legalities in localities, but regardless of opinion about the craft’s intended use, the system looks very slick, and there are some great hacks baked right in. Don’t want to build a drone-killing-drone? Maybe all you need is a pumpkin and good (bad?) timing.

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Tracking Drone Flight Path Via Video, Using Cameras We Can Get

Calculating three-dimensional position from two-dimensional projections are literal textbook examples in geometry, but those examples are the “assume a spherical cow” type of simplifications. Applicable only in an ideal world where the projections are made with mathematically perfect cameras at precisely known locations with infinite resolution. Making things work in the real world is a lot harder. But not only have [Jingtong Li, Jesse Murray et al.] worked through the math of tracking a drone’s 3D flight from 2D video, they’ve released their MultiViewUnsynch software on GitHub so we can all play with it.

Instead of laboratory grade optical instruments, the cameras used in these experiments are available at our local consumer electronics store. A table in their paper Reconstruction of 3D Flight Trajectories from Ad-Hoc Camera Networks (arXiv:2003.04784) listed several Huawei cell phone cameras, a few Sony digital cameras, and a GoPro 3. Video cameras don’t need to be placed in any particular arrangement, because positions are calculated from their video footage. Correlating overlapping footage from dissimilar cameras is a challenge all in itself, since these cameras record at varying framerates ranging from 25 to 59.94 frames per second. Furthermore, these cameras all have rolling shutters, which adds an extra variable as scanlines in a frame are taken at slightly different times. This is not an easy problem.

There is a lot of interest in tracking drone flights, especially those flying where they are not welcome. And not everyone have the budget for high-end equipment or the permission to emit electromagnetic signals. MultiViewUnsynch is not quite there yet, as it tracks a single target and video files were processed afterwards. The eventual goal is to evolve this capability to track multiple targets on live video, and hopefully help reduce frustrating public embarrassments.

[IROS 2020 Presentation video (duration 14:45) requires free registration, available until at least Nov. 25th 2020.]

Watching The Watchers: Are You The Star Of An Encrypted Drone Video Stream?

Small aircraft with streaming video cameras are now widely available, for better or worse. Making eyes in the sky so accessible has resulted in interesting footage that would have been prohibitively expensive to capture a few years ago, but this new creative frontier also has a dark side when used to violate privacy. Those who are covering their tracks by encrypting their video transmission should know researchers at Ben-Gurion University of the Negev demonstrated such protection can be breached.

The BGU team proved that a side-channel analysis can be done against behavior common to video compression algorithms, as certain changes in video input would result in detectable bitrate changes to the output stream. By controlling a target’s visual appearance to trigger these changes, a correlating change in bandwidth consumption would reveal the target’s presence in an encrypted video stream.

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Radio Jamming Rifle Claimed To Disable Drones

[Battelle], an Ohio-based non-profit R&D firm has just unveiled a device they call the DroneDefender — a long-range anti-drone defense weapon. It almost sounds like they’ve brought the fictional drone hunter’s RF cannon to life. But does it really work?

According to the site, it uses radio frequency disruption to blast unwanted drones out of the sky. Cool concept, but does it actually work? Unlike the hackable MAVLink protocol used by Parrot AR, ArduPilot and a handful of other consumer drones, this weapon uses brute radio signal force to disable any(?) consumer drone.

There’s a video after the break demonstrating a simulated use of the technology, which leaves us a bit confused. They show the drone slowly landing all nicely after being “guided” down by the rifle. If the system is jamming both GPS and the 2.4 GHz control link, the behavior will all depend on the software loaded on the drone. Some will go to a fail-safe mode, which is low throttle or motor power off, assuming the pilot has set fail-safe. Others may attempt to loiter on IMU sensors only.

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