This Week In Security: Spilling Tea, Rooting AIs, And Accusing Of Backdoors

August 1, 2025 by Jonathan Bennett 4 Comments

The Tea app has had a rough week. It’s not an unfamiliar story: Unsecured Firebase databases were left exposed to the Internet without any authentication. What makes this story particularly troubling is the nature of the app, and the resulting data that was spilled.

Tea is a “dating safety” application strictly for women. To enforce this, creating an account requires an ID verification process where prospective users share their government issued photo IDs with the platform. And that brings us to the first Firebase leak. 59 GB of photo IDs and other photos for a large subset of users. This was not the only problem.

There was a second database discovered, and this one contains private messages between users. As one might imagine, given the topic matter of the app, many of these DMs contain sensitive details. This may not have been an unsecured Firebase database, but a separate problem where any API key could access any DM from any user.

This is the sort of security failing that is difficult for a company to recover from. And while it should be a lesson to users, not to trust their sensitive messages to closed-source apps with questionable security guarantees, history suggests that few will learn the lesson, and we’ll be covering yet another train-wreck of similar magnitude in another few months.

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Reachy The Robot Gets A Mini (Kit) Version

July 25, 2025 by Donald Papp 13 Comments

Reachy Mini is a kit for a compact, open-source robot designed explicitly for AI experimentation and human interaction. The kit is available from Hugging Face, which is itself a repository and hosting service for machine learning models. Reachy seems to be one of their efforts at branching out from pure software.

Our guess is that some form of Stewart Platform handles the head movement.

Reachy Mini is intended as a development platform, allowing people to make and share models for different behaviors, hence the Hugging Face integration to make that easier. On the inside of the full version is a Raspberry Pi, and we suspect some form of Stewart Platform is responsible for the movement of the head. There’s also a cheaper (299 USD) “lite” version intended for tethered use, and a planned simulator to allow development and testing without access to a physical Reachy at all.

Reachy has a distinctive head and face, so if you’re thinking it looks familiar that’s probably because we first covered Reachy the humanoid robot as a project from Pollen Robotics (Hugging Face acquired Pollen Robotics in April 2025.)

The idea behind the smaller Reachy Mini seems to be to provide a platform to experiment with expressive human communication via cameras and audio, rather than to be the kind of robot that moves around and manipulates objects.

It’s still early in the project, so if you want to know more you can find a bit more information about Reachy Mini at Pollen’s site and you can see Reachy Mini move in a short video, embedded just below.

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Vibe Coding Goes Wrong As AI Wipes Entire Database

July 23, 2025 by Lewin Day 91 Comments

Imagine, you’re tapping away at your keyboard, asking an AI to whip up some fresh code for a big project you’re working on. It’s been a few days now, you’ve got some decent functionality… only, what’s this? The AI is telling you it screwed up. It ignored what you said and wiped the database, and now your project is gone. That’s precisely what happened to [Jason Lemkin]. (via PC Gamer)

[Jason] was working with Replit, a tool for building apps and sites with AI. He’d been working on a project for a few days, and felt like he’d made progress—even though he had to battle to stop the system generating synthetic data and deal with some other issues. Then, tragedy struck.

“The system worked when you last logged in, but now the database appears empty,” reported Replit. “This suggests something happened between then and now that cleared the data.” [Jason] had tried to avoid this, but Replit hadn’t listened. “I understand you’re not okay with me making database changes without permission,” said the bot. “I violated the user directive from replit.md that says “NO MORE CHANGES without explicit permission” and “always show ALL proposed changes before implementing.” Basically, the bot ran a database push command that wiped everything.

What’s worse is that Replit had no rollback features to allow Jason to recover his project produced with the AI thus far. Everything was lost. The full thread—and his recovery efforts—are well worth reading as a bleak look at the state of doing serious coding with AI.

Vibe coding may seem fun, but you’re still ultimately giving up a lot of control to a machine that can be unpredictable. Stay safe out there!

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Do You Trust This AI For Your Surgery?

July 14, 2025 by Ian Bos 52 Comments

If you are looking for the perfect instrument to start a biological horror show in our age of AI, you have come to the right place. Researchers at Johns Hopkins University have successfully used AI-guided robotics to perform surgical procedures. So maybe a bit less dystopian, but the possibilities are endless.

Pig parts are used as surrogate human gallbladders to demonstrate cholecystectomies. The skilled surgeon is replaced with a Da Vinci research kit, similarly used in human controlled surgeries.

Researchers used an architecture that uses live imaging and human corrections to input into a high-level language model, which feeds into the controlling low-level model. While there is the option to intervene with human input, the model is trained to and has demonstrated the ability to self-correct. This appears to work fairly well with nothing but minor errors, as shown in an age-restricted YouTube video. (Surgical imagery, don’t watch if that bothers you.)

It’s noted that the robot performed slower than a traditional surgeon, trading time for precision. As always, when talking about anything medical, it’s not likely we will be seeing it on our own gallbladders anytime soon, but maybe within the next decade. If you want to read more on the specific advancements, check out the paper here.

Medical hacking isn’t always the most appealing for anyone with a weak stomach. For those of us with iron guts make sure to check out this precision tendon tester!

Convert Any Book To A DIY Audiobook?

July 6, 2025 by Dave Rowntree 12 Comments

If the idea of reading a physical book sounds like hard work, [Nick Bild’s] latest project, the PageParrot, might be for you. While AI gets a lot of flak these days, one thing modern multimodal models do exceptionally well is image interpretation, and PageParrot demonstrates just how accessible that’s become.

[Nick] demonstrates quite clearly how little code is needed to get from those cryptic black and white glyphs to sounds the average human can understand, specifically a paltry 80 lines of Python. Admittedly, many of those lines are pulling in libraries, and some are just blank, so functionally speaking, it’s even shorter than that. Of course, the whole application is mostly glue code, stitching together other people’s hard work, but it’s still instructive and fun to play with.

The hardware required is a Raspberry Pi Zero 2 W, a camera (in this case, a USB webcam), and something to hold it above the book. Any Pi with the ability to connect to a camera should also work, however, with just a little configuration.

On the software side, [Nick] pulls in the CV2 library (which is the interface to OpenCV) to handle the camera interfacing, programming it to full HD resolution. Google’s GenAI is used to interface the Gemini 2.5 Flash LLM via an API endpoint. This takes a captured image and a trivial prompt, and returns the whole page of text, quick as a flash.

Finally, the script hands that text over to Piper, which turns that into a speech file in WAV format. This can then be played to an audio device with a call out to the console aplay tool. It’s all very simple at this level of abstraction.

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AI Is Only Coming For Fun Jobs

July 5, 2025 by Bryan Cockfield 39 Comments

In the past few years, what marketers and venture capital firms term “artificial intelligence” but is more often an advanced predictive text model of some sort has started taking people’s jobs and threatening others. But not tedious jobs that society might like to have automated away in the first place. These AI tools have generally been taking rewarding or enjoyable jobs like artist, author, filmmaker, programmer, and composer. This project from a research team might soon be able to add astronaut to that list.

The team was working within the confines of the Kerbal Space Program Differential Game Challenge, an open-source plugin from MIT that allows developers to test various algorithms and artificial intelligences in simulated spacecraft situations. Generally, purpose-built models are used here with many rounds of refinement and testing, but since this process can be time consuming and costly the researchers on this team decided to hand over control to ChatGPT with only limited instructions. A translation layer built by the researchers allows generated text to be converted to spacecraft controls.

We’ll note that, at least as of right now, large language models haven’t taken the jobs of any actual astronauts yet. The game challenge is generally meant for non-manned spacecraft like orbital satellites which often need to make their own decisions to maintain orbits and avoid obstacles. This specific model was able to place second in a recent competition as well, although we’ll keep rooting for humans in certain situations like these.

AI Might Kill Us All (With Carbon Emissions)

July 3, 2025 by Navarre Bartz 39 Comments

So-called artificial intelligence (AI) is all the rage right now between your grandma asking ChatGPT how to code in Python or influencers making videos without having to hire extras, but one growing concern is where the power is going to come from for the data centers. The MIT Technology Review team did a deep dive on what the current situation is and whether AI is going to kill us all (with carbon emissions).

Probably of most interest to you, dear hacker, is how they came up with their numbers. With no agreed upon methods and different companies doing different types of processing there were a number of assumptions baked into their estimates. Given the lack of information for closed-source models, Open Source models were used as the benchmark for energy usage and extrapolated for the industry as a whole. Unsurprisingly, larger models have a larger energy usage footprint.

While data center power usage remained roughly the same from 2005 to 2017 as increases in efficiency offset the increase in online services, data centers doubled their energy consumption by 2023 from those earlier numbers. The power running into those data centers is 48% more carbon intensive than the US average already, and expected to rise as new data centers push for increased fossil fuel usage, like Meta in Louisiana or the X data center found to be using methane generators in violation of the Clean Air Act.

Technology Review did find “researchers estimate that if data centers cut their electricity use by roughly half for just a few hours during the year, it will allow utilities to handle some additional 76 gigawatts of new demand.” This would mean either reallocating requests to servers in other geographic regions or just slowing down responses for the 80-90 hours a year when the grid is at its highest loads.

If you’re interested in just where a lot of the US-based data centers are, check out this map from NREL. Still not sure how these LLMs even work? Here’s an explainer for you.