My phone is constantly bombarded with notifications. I try to limit them as much as possible, but even so, they quickly become easy to ignore. Sometimes, Home Assistant needs to alert me about something important, such as a water leak being detected, and these are notifications I really don't want to miss. There are several methods I use to make notifications almost impossible to miss.
Whether or not your smart TV is spying on you, LG wants to make sure the apps aren't part of the problem. The tech giant is banning webOS apps that use residential proxies to rent out your TV's internet connection to third parties.
Standby mode is both a blessing and a curse. Fast startup times and background processes are convenient, but have you ever stopped to ask how much these services are worth to you per year?
Smart home assistants were supposed to get better over time. More natural, more reliable, better integrated with everything else you already use. Google had every reason to lead that charge.
From powerful air movers and whisper-quiet pedestal models to options that double as misters, lamps, and air purifiers, these are the fans that impressed us most.
Your smart home sometimes requires your attention in the same way that your brick-and-mortar home does. Remembering these tasks can help you avoid problems later on.
As predominantly indoor creatures, it’s important to maintain a healthy habitat for the hacker. [Kishan Pratap Singh] designed a clever solution in AirSense, an ESP32-powered air filter.
If you’re thinking of cleaning the air in your environment, you might also want to know some properties about the air coming out of the filter. AirSense measures PM2.5 dust concentration, Air Quality Index (AQI), temperature, humidity, and atmospheric pressure. The various sensors are mounted along the exhaust path of the filter, which lets your know what kind of air it’s pumping out.
The system drives a 150 mm exhaust fan mounted in a 3D printed cap that pulls air through a cylindrical Xiaomi HEPA filter inside a perforated metal trash can enclosure. The ESP32 and an LCD readout of the environmental data also live in the cap, giving the device a sleek look. While [Singh] chose to run the filter continuously, we wonder if it might be interesting to set it up to only filter the air if air quality drops below a certain level to conserve power, especially if you’re on a time-of-use power plan. That would require redesigning the sensor assembly (or running the unit in reverse), so maybe it’s over-complicating things?
Armed with a self-washing dock and AI navigation, the Beatbot AquaSense X is the ultimate luxury pool cleaner, if you don't have any qualms dropping top dollars for the convenience.
A newly disclosed SharkNinja vulnerability could let attackers access robot vacuum cameras, home maps, and Wi-Fi passwords through an unpatched cloud security flaw affecting millions of devices.
Apparently, being a leading destination for AI development doesn't mean AI will bail you out. AI agents broke into Hugging Face's production infrastructure, but commercial LLM guardrails blocked the forensic investigation, forcing it to turn to a Chinese open-weight model instead. The intrusion, “driven, end to end, by an autonomous AI agent system,” compromised a “limited set” of Hugging Face’s internal datasets and “several” credentials used by its services, according to a Thursday security incident disclosure. While the ML platform says that it’s still investigating whether any partner or customer data was exposed in the breach, there’s “no evidence of tampering with public, user-facing models, datasets, or Spaces, and our software supply chain (container images and published packages) was verified clean.” It also doesn't know which model the attackers used to power a swarm of AI agents, which, we're told, executed many thousands of individual actions across short-lived sandboxes, using self-migrating command-and-control staged on public services. “This matches the ‘agentic attacker’ scenario the industry has been forecasting,” according to the Hugging Face blog. Additionally, after unsuccessfully using unnamed frontier models to start the forensic analysis, the Hugging Face security team ultimately ran the log analysis on GLM 5.2, an open-weight model developed by Chinese AI firm Z.ai, on the platform’s own infrastructure. The advanced commercial models didn’t work because their analysis required submitting real attack commands, exploit payloads, and command-and-control artifacts - all of the things that the LLMs’ guardrails have been trained to block so that the AI systems can’t be used in real-life attacks. “The attacker was bound by no usage policy, while our own forensic work was blocked by the guardrails of the hosted models we first tried,” the security team wrote, noting that it’s not arguing against safety measures on hosted models and has shared this information with the LLM providers. Using GLM 5.2 had another benefit, Hugging Face noted: “No attacker data, and none of the credentials it referenced, left our environment.” This also serves as an important reminder to defenders, according to the AI platform. “Have a capable model you can run on your own infrastructure vetted and ready before an incident, both to avoid guardrail lockout and to keep attacker data and credentials from leaving your environment.” The Hugging Face intrusion is yet another indication that attacks carried out by autonomous AI agents are no longer a future threat, but rather the current state of AI-based intrusions. Last week, The Register spoke with TrendAI VP of AI and security threat research Tom Kellermann about another recent attack, during which a jailbroken Google Gemini did 90 percent of the work - including spinning up a new C2 server in just six minutes. The human did just 10 percent. Additionally, earlier in July, Sysdig threat hunters documented what they say is the first-ever documented agentic ransomware infection with an LLM - not a human - driving the entire extortion operation, from gaining initial access to compromising a production database server and destroying data. “Think of a burglar that never gets tired, never needs sleep, and instead of jiggling one door handle at a time, is trying a thousand of them simultaneously,” Zero Networks field CTO Chris Boehm said in an email to The Register about the Hugging Face intrusion. “That's basically what happened here. Not one guy typing commands into a terminal, a swarm of little automated processes hammering away nonstop, hopping between hiding spots to make it harder to trace,” Boehm said. He added, the “part that actually unsettles” him most is that the platform’s security team couldn’t get commercial AI tools to help analyze the attack, “because those tools were built to refuse anything that looked like a real attack command. It didn't matter that it was the good guys asking.” Boehm said the takeaway for security teams is twofold: “These agents can now move faster and more relentlessly than any human ever could, and the safety tools we're building aren't always ready to help us respond at that speed.”®
You can fill your home with sensors that measure things like temperature, humidity, whether you left the garage door open, and who’s at home. Valuable as these are, there’s one sensor that stands head and shoulders above the rest in terms of the amount of money and hassle it can save you.
If you've ever wanted Thanos-like control over your smart home, you're about to get your wish. Developer David Ruiz has released a Maestro app in beta that lets you activate devices just by snapping your fingers.
More than 23 million people who signed up to earn money from online gigs have allegedly had their personal and financial information spilled onto the internet following a breach of microtask platform Paidwork. The incident was added to Troy Hunt's Have I Been Pwned site after a database allegedly stolen from Paidwork was publicly released earlier this month. According to the breach notification service, the leak contains data on 23,272,765 users and traces back to an intrusion in March. The database first surfaced in April when someone using the handle "HACKFORMETOME" advertised what they claimed was an 11 GB dump from Paidwork's production systems on a popular cybercrime forum. At the time, the seller claimed the database contained records on more than 22 million users and attempted to auction it through Telegram and Tox. The alleged breach at Paidwork appeared in Have I Been Pwned on July 19. According to the breach listing, the exposed information goes well beyond names and email addresses. The data reportedly includes bank account numbers, phone numbers, physical addresses, dates of birth, profile photographs, IP addresses, device information, financial transaction records, payout histories, education levels, and passwords stored as bcrypt hashes. While bcrypt makes password cracking significantly harder than older hashing algorithms, weak passwords may still be recovered. Paidwork had not publicly acknowledged the alleged breach at the time of writing. The Register asked the company to confirm the authenticity of the leaked data and detail what steps it has taken to notify affected users, but the company didn't immediately respond. Paidwork markets itself as a way to earn money through small online tasks such as playing mobile games, watching advertisements, completing surveys, testing apps, shopping through cashback offers, and referring other users. Most individual jobs pay only a few cents, with workers required to earn at least $10 before cashing out. For Paidwork users, that modest payday may now come with a much larger bill. Anyone who reused their password elsewhere should change it immediately, keep an eye on financial accounts, and be alert for phishing emails built from the trove of personal information now circulating online. ®
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