A Remote-Start App Exposed Thousands of Cars to Hackers

https://www.wired.com/story/mycar-remote-start-vulnerabilities

Last winter, a hacker who goes by the handle Jmaxxz was looking for a Christmas present for his girlfriend. She’d recently flown back from a work trip and complained that her fingers had been painfully cold on her drive home from the airport, thanks to below-freezing winter weather and a circulatory system condition known as Raynaud’s disease. So Jmaxxz had the idea to buy her a remote starter that would connected to her car’s dashboard and, with an accompanying device and app called Linkr, allow her to start the car’s engine with a tap on her phone. That way, on her next trip, she could start heating up the car as soon as her plane touched down.

But even as he was installing that setup, he had misgivings. A security-minded software engineer for a company he declined to name, Jmaxxz wondered what sort of remote hacking he might have left his girlfriend’s car susceptible to. “In the back of my head I kept thinking, what’s the risk of this system, I’m putting her car on the internet,” he remembers. “I told myself, ‘ignorance is bliss. I’m not going to look at it. Don’t look at it.'”

He looked at it. And within 24 hours of doing so, in January of this year, he found exactly what he had feared: vulnerabilities that would let any hacker fully hijack that remote unlock and ignition device, providing a handy tool for stealing any of tens of thousands of vehicles. “You could locate cars, identify them, unlock them, start the car, trigger the alarm,” says Jmaxxz. “Really anything a legitimate user could do, you could do.”

“The problem is that these bugs shipped in the first place.”

Jmaxxz, Hacker

In a talk at the Defcon hacker conference today in Las Vegas, Jmaxxz described a series of vulnerabilities in MyCar, a system made by Canadian company Automobility, whose software is rebranded and distributed under names including MyCar Kia, Visions MyCar, Carlink, and Linkr-LT1. MyCar’s devices and apps connect to radio-based remote start devices like Fortin, CodeAlarm, and Flashlogic, using GPS and a cellular connection to extend their range to anywhere with an internet connection. But with any of three different security flaws present across those apps—which Jmaxxz says he reported to the company and have since been fixed—he says he could have gained access to MyCar’s database backend, letting him or a less friendly hacker pinpoint and steal any car connected to the MyCar app, anywhere in the world.

Based on a scan of MyCar’s exposed database—and Jmaxxz says he was careful not to access anyone else’s private data—he estimates that there were roughly 60,000 cars left open to theft by those security bugs, with enough exposed data for a hacker to even choose the make and model of the car they wanted to steal. “You want a new Cadillac? You can find a new Cadillac,” Jmaxxz says.

When Jmaxxz began digging into the internals of Automobility’s apps in January, he says he first found that they included hardcoded administrator credentials, which he could pull out and use to access the company’s backend data. But even beyond that, he describes two other kinds of common hackable flaws—widespread SQL injection bugs and direct object references vulnerabilities—that would have let him gain access to the same data and send commands to other users’ vehicles.

Jmaxxz says he warned Automobility and the US Computer Emergency Response Team of those vulnerabilities in February of this year. They were fixed over the next months. But he says he continued to find and report lingering SQL injection vulnerabilities in MyCar’s code to MyCar’s developer Automobility, some of which weren’t fixed until just days before his Defcon talk. WIRED reached out to Automobility, who didn’t immediately respond. A notice on the CERT website in April confirmed the vulnerability, and includes a statement from Automobility. “All the resources at our disposal have been used to promptly address the situation, and we have fully resolved the issue,” the company wrote in the statement to CERT. “During this vulnerability period, no actual incident or issue with compromised privacy or functionality has been reported to us or detected by our systems.”

The danger of those bugs, Jmaxxz argues, went beyond theft or remote alarm-triggering pranks. Remotely starting a car without the owner’s knowledge could lead to dangerous carbon monoxide leaks, he points out. “If you start a car and it’s in a closed structure, you can end up in a situation where someone can die,” Jmaxxz says.

Separately, Jmaxxz says he found in his probing of MyCar’s database that it had also stored vastly more information about his girlfriend’s car than he expected. Over just 13 days, it had collected 2,000 locations of the car. “That one offends me more than all the others,” he says.”That’s not what I signed up for.”

Even now that Automobility has fixed the bugs that Jmaxxz reported, he argues that it still represents a worst-case scenario of internet-of-things companies that don’t carry out even basic security practices. “The problem is that these bugs shipped in the first place,” he says. “In my opinion this should have come up in any kind of security testing.”

Needless to say, Jmaxxz pulled the MyCar device out of his girlfriend’s car earlier this year. He eventually built his own DIY solution, with code he says he’ll make available on Github. The system, he says, will do just as good a job as MyCar at remotely warming up a car—and makes a better Christmas present than exposing her vehicle to an internet full of car thieves.


More Great WIRED Stories

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August 10, 2019 at 01:54PM

Mysterious, Ancient Radio Signals Keep Pelting Earth. Astronomers Designed an AI to Hunt Them Down.

https://www.space.com/fast-radio-bursts-australia-artificial-intelligence.html

Sudden shrieks of radio waves from deep space keep slamming into radio telescopes on Earth, spattering those instruments’ detectors with confusing data. And now, astronomers are using artificial intelligence to pinpoint the source of the shrieks, in the hope of explaining what’s sending them to Earth from — researchers suspect — billions of light-years across space.

Usually, these weird, unexplained signals are detected only after the fact, when astronomers notice out-of-place spikes in their data — sometimes years after the incident. The signals have complex, mysterious structures, patterns of peaks and valleys in radio waves that play out in just milliseconds. That’s not the sort of signal astronomers expect to come from a simple explosion, or any other one of the standard events known to scatter spikes of electromagnetic energy across space. Astronomers call these strange signals fast radio bursts (FRBs). Ever since the first one was uncovered in 2007, using data recorded in 2001, there’s been an ongoing effort to pin down their source. But FRBs arrive at random times and places, and existing human technology and observation methods aren’t well-primed to spot these signals.

Now, in a paper published July 4 in the journal Monthly Notices of the Royal Astronomical Society, a team of astronomers wrote that they managed to detect five FRBs in real time using a single radio telescope. 

Related: The 12 Strangest Objects in the Universe

Wael Farah, a doctoral student at Swinburne University of Technology in Melbourne, Australia, developed a machine-learning system that recognized the signatures of FRBs as they arrived at the University of Sydney’s Molonglo Radio Observatory, near Canberra. As Live Science has previously reported, many scientific instruments, including radio telescopes, produce more data per second than they can reasonably store. So they don’t record anything in the finest detail except their most interesting observations.

Farah’s system trained the Molonglo telescope to spot FRBs and switch over to its most detailed recording mode, producing the finest records of FRBs yet.

Based on their data, the researchers predicted that between 59 and 157 theoretically detectable FRBs splash across our skies every day. The scientists also used the immediate detections to hunt for related flares in data from X-ray, optical and other radio telescopes — in hopes of finding some visible event linked to the FRBs — but had no luck.

Their research showed, however, that one of the most peculiar (and frustrating, for research purposes) traits of FRBs appears to be real: The signals, once arriving, never repeat themselves. Each one appears to be a singular event in space that will never happen again.

Originally published on Live Science.

Sudden shrieks of radio waves from deep space keep slamming into radio telescopes on Earth, spattering those instruments’ detectors with confusing data. And now, astronomers are using artificial intelligence to pinpoint the source of the shrieks, in the hope of explaining what’s sending them to Earth from — researchers suspect — billions of light-years across space.

Usually, these weird, unexplained signals are detected only after the fact, when astronomers notice out-of-place spikes in their data — sometimes years after the incident. The signals have complex, mysterious structures, patterns of peaks and valleys in radio waves that play out in just milliseconds. That’s not the sort of signal astronomers expect to come from a simple explosion, or any other one of the standard events known to scatter spikes of electromagnetic energy across space. Astronomers call these strange signals fast radio bursts (FRBs). Ever since the first one was uncovered in 2007, using data recorded in 2001, there’s been an ongoing effort to pin down their source. But FRBs arrive at random times and places, and existing human technology and observation methods aren’t well-primed to spot these signals.

Now, in a paper published July 4 in the journal Monthly Notices of the Royal Astronomical Society, a team of astronomers wrote that they managed to detect five FRBs in real time using a single radio telescope. [The 12 Strangest Objects in the Universe]

Wael Farah, a doctoral student at Swinburne University of Technology in Melbourne, Australia, developed a machine-learning system that recognized the signatures of FRBs as they arrived at the University of Sydney’s Molonglo Radio Observatory, near Canberra. As Live Science has previously reported, many scientific instruments, including radio telescopes, produce more data per second than they can reasonably store. So they don’t record anything in the finest detail except their most interesting observations.

Farah’s system trained the Molonglo telescope to spot FRBs and switch over to its most detailed recording mode, producing the finest records of FRBs yet.

Based on their data, the researchers predicted that between 59 and 157 theoretically detectable FRBs splash across our skies every day. The scientists also used the immediate detections to hunt for related flares in data from X-ray, optical and other radio telescopes — in hopes of finding some visible event linked to the FRBs — but had no luck.

Their research showed, however, that one of the most peculiar (and frustrating, for research purposes) traits of FRBs appears to be real: The signals, once arriving, never repeat themselves. Each one appears to be a singular event in space that will never happen again.

Originally published on Live Science.

Sudden shrieks of radio waves from deep space keep slamming into radio telescopes on Earth, spattering those instruments’ detectors with confusing data. And now, astronomers are using artificial intelligence to pinpoint the source of the shrieks, in the hope of explaining what’s sending them to Earth from — researchers suspect — billions of light-years across space.

Usually, these weird, unexplained signals are detected only after the fact, when astronomers notice out-of-place spikes in their data — sometimes years after the incident. The signals have complex, mysterious structures, patterns of peaks and valleys in radio waves that play out in just milliseconds. That’s not the sort of signal astronomers expect to come from a simple explosion, or any other one of the standard events known to scatter spikes of electromagnetic energy across space. Astronomers call these strange signals fast radio bursts (FRBs). Ever since the first one was uncovered in 2007, using data recorded in 2001, there’s been an ongoing effort to pin down their source. But FRBs arrive at random times and places, and existing human technology and observation methods aren’t well-primed to spot these signals.

Now, in a paper published July 4 in the journal Monthly Notices of the Royal Astronomical Society, a team of astronomers wrote that they managed to detect five FRBs in real time using a single radio telescope. [The 12 Strangest Objects in the Universe]

Wael Farah, a doctoral student at Swinburne University of Technology in Melbourne, Australia, developed a machine-learning system that recognized the signatures of FRBs as they arrived at the University of Sydney’s Molonglo Radio Observatory, near Canberra. As Live Science has previously reported, many scientific instruments, including radio telescopes, produce more data per second than they can reasonably store. So they don’t record anything in the finest detail except their most interesting observations.

Farah’s system trained the Molonglo telescope to spot FRBs and switch over to its most detailed recording mode, producing the finest records of FRBs yet.

Based on their data, the researchers predicted that between 59 and 157 theoretically detectable FRBs splash across our skies every day. The scientists also used the immediate detections to hunt for related flares in data from X-ray, optical and other radio telescopes — in hopes of finding some visible event linked to the FRBs — but had no luck.

Their research showed, however, that one of the most peculiar (and frustrating, for research purposes) traits of FRBs appears to be real: The signals, once arriving, never repeat themselves. Each one appears to be a singular event in space that will never happen again.

Originally published on Live Science.

Sudden shrieks of radio waves from deep space keep slamming into radio telescopes on Earth, spattering those instruments’ detectors with confusing data. And now, astronomers are using artificial intelligence to pinpoint the source of the shrieks, in the hope of explaining what’s sending them to Earth from — researchers suspect — billions of light-years across space.

Usually, these weird, unexplained signals are detected only after the fact, when astronomers notice out-of-place spikes in their data — sometimes years after the incident. The signals have complex, mysterious structures, patterns of peaks and valleys in radio waves that play out in just milliseconds. That’s not the sort of signal astronomers expect to come from a simple explosion, or any other one of the standard events known to scatter spikes of electromagnetic energy across space. Astronomers call these strange signals fast radio bursts (FRBs). Ever since the first one was uncovered in 2007, using data recorded in 2001, there’s been an ongoing effort to pin down their source. But FRBs arrive at random times and places, and existing human technology and observation methods aren’t well-primed to spot these signals.

Now, in a paper published July 4 in the journal Monthly Notices of the Royal Astronomical Society, a team of astronomers wrote that they managed to detect five FRBs in real time using a single radio telescope. [The 12 Strangest Objects in the Universe]

Wael Farah, a doctoral student at Swinburne University of Technology in Melbourne, Australia, developed a machine-learning system that recognized the signatures of FRBs as they arrived at the University of Sydney’s Molonglo Radio Observatory, near Canberra. As Live Science has previously reported, many scientific instruments, including radio telescopes, produce more data per second than they can reasonably store. So they don’t record anything in the finest detail except their most interesting observations.

Farah’s system trained the Molonglo telescope to spot FRBs and switch over to its most detailed recording mode, producing the finest records of FRBs yet.

Based on their data, the researchers predicted that between 59 and 157 theoretically detectable FRBs splash across our skies every day. The scientists also used the immediate detections to hunt for related flares in data from X-ray, optical and other radio telescopes — in hopes of finding some visible event linked to the FRBs — but had no luck.

Their research showed, however, that one of the most peculiar (and frustrating, for research purposes) traits of FRBs appears to be real: The signals, once arriving, never repeat themselves. Each one appears to be a singular event in space that will never happen again.

Originally published on Live Science.

Sudden shrieks of radio waves from deep space keep slamming into radio telescopes on Earth, spattering those instruments’ detectors with confusing data. And now, astronomers are using artificial intelligence to pinpoint the source of the shrieks, in the hope of explaining what’s sending them to Earth from — researchers suspect — billions of light-years across space.

Usually, these weird, unexplained signals are detected only after the fact, when astronomers notice out-of-place spikes in their data — sometimes years after the incident. The signals have complex, mysterious structures, patterns of peaks and valleys in radio waves that play out in just milliseconds. That’s not the sort of signal astronomers expect to come from a simple explosion, or any other one of the standard events known to scatter spikes of electromagnetic energy across space. Astronomers call these strange signals fast radio bursts (FRBs). Ever since the first one was uncovered in 2007, using data recorded in 2001, there’s been an ongoing effort to pin down their source. But FRBs arrive at random times and places, and existing human technology and observation methods aren’t well-primed to spot these signals.

Now, in a paper published July 4 in the journal Monthly Notices of the Royal Astronomical Society, a team of astronomers wrote that they managed to detect five FRBs in real time using a single radio telescope. [The 12 Strangest Objects in the Universe]

Wael Farah, a doctoral student at Swinburne University of Technology in Melbourne, Australia, developed a machine-learning system that recognized the signatures of FRBs as they arrived at the University of Sydney’s Molonglo Radio Observatory, near Canberra. As Live Science has previously reported, many scientific instruments, including radio telescopes, produce more data per second than they can reasonably store. So they don’t record anything in the finest detail except their most interesting observations.

Farah’s system trained the Molonglo telescope to spot FRBs and switch over to its most detailed recording mode, producing the finest records of FRBs yet.

Based on their data, the researchers predicted that between 59 and 157 theoretically detectable FRBs splash across our skies every day. The scientists also used the immediate detections to hunt for related flares in data from X-ray, optical and other radio telescopes — in hopes of finding some visible event linked to the FRBs — but had no luck.

Their research showed, however, that one of the most peculiar (and frustrating, for research purposes) traits of FRBs appears to be real: The signals, once arriving, never repeat themselves. Each one appears to be a singular event in space that will never happen again.

Originally published on Live Science.

Sudden shrieks of radio waves from deep space keep slamming into radio telescopes on Earth, spattering those instruments’ detectors with confusing data. And now, astronomers are using artificial intelligence to pinpoint the source of the shrieks, in the hope of explaining what’s sending them to Earth from — researchers suspect — billions of light-years across space.

Usually, these weird, unexplained signals are detected only after the fact, when astronomers notice out-of-place spikes in their data — sometimes years after the incident. The signals have complex, mysterious structures, patterns of peaks and valleys in radio waves that play out in just milliseconds. That’s not the sort of signal astronomers expect to come from a simple explosion, or any other one of the standard events known to scatter spikes of electromagnetic energy across space. Astronomers call these strange signals fast radio bursts (FRBs). Ever since the first one was uncovered in 2007, using data recorded in 2001, there’s been an ongoing effort to pin down their source. But FRBs arrive at random times and places, and existing human technology and observation methods aren’t well-primed to spot these signals.

Now, in a paper published July 4 in the journal Monthly Notices of the Royal Astronomical Society, a team of astronomers wrote that they managed to detect five FRBs in real time using a single radio telescope. [The 12 Strangest Objects in the Universe]

Wael Farah, a doctoral student at Swinburne University of Technology in Melbourne, Australia, developed a machine-learning system that recognized the signatures of FRBs as they arrived at the University of Sydney’s Molonglo Radio Observatory, near Canberra. As Live Science has previously reported, many scientific instruments, including radio telescopes, produce more data per second than they can reasonably store. So they don’t record anything in the finest detail except their most interesting observations.

Farah’s system trained the Molonglo telescope to spot FRBs and switch over to its most detailed recording mode, producing the finest records of FRBs yet.

Based on their data, the researchers predicted that between 59 and 157 theoretically detectable FRBs splash across our skies every day. The scientists also used the immediate detections to hunt for related flares in data from X-ray, optical and other radio telescopes — in hopes of finding some visible event linked to the FRBs — but had no luck.

Their research showed, however, that one of the most peculiar (and frustrating, for research purposes) traits of FRBs appears to be real: The signals, once arriving, never repeat themselves. Each one appears to be a singular event in space that will never happen again.

Originally published on Live Science.

Sudden shrieks of radio waves from deep space keep slamming into radio telescopes on Earth, spattering those instruments’ detectors with confusing data. And now, astronomers are using artificial intelligence to pinpoint the source of the shrieks, in the hope of explaining what’s sending them to Earth from — researchers suspect — billions of light-years across space.

Usually, these weird, unexplained signals are detected only after the fact, when astronomers notice out-of-place spikes in their data — sometimes years after the incident. The signals have complex, mysterious structures, patterns of peaks and valleys in radio waves that play out in just milliseconds. That’s not the sort of signal astronomers expect to come from a simple explosion, or any other one of the standard events known to scatter spikes of electromagnetic energy across space. Astronomers call these strange signals fast radio bursts (FRBs). Ever since the first one was uncovered in 2007, using data recorded in 2001, there’s been an ongoing effort to pin down their source. But FRBs arrive at random times and places, and existing human technology and observation methods aren’t well-primed to spot these signals.

Now, in a paper published July 4 in the journal Monthly Notices of the Royal Astronomical Society, a team of astronomers wrote that they managed to detect five FRBs in real time using a single radio telescope. [The 12 Strangest Objects in the Universe]

Wael Farah, a doctoral student at Swinburne University of Technology in Melbourne, Australia, developed a machine-learning system that recognized the signatures of FRBs as they arrived at the University of Sydney’s Molonglo Radio Observatory, near Canberra. As Live Science has previously reported, many scientific instruments, including radio telescopes, produce more data per second than they can reasonably store. So they don’t record anything in the finest detail except their most interesting observations.

Farah’s system trained the Molonglo telescope to spot FRBs and switch over to its most detailed recording mode, producing the finest records of FRBs yet.

Based on their data, the researchers predicted that between 59 and 157 theoretically detectable FRBs splash across our skies every day. The scientists also used the immediate detections to hunt for related flares in data from X-ray, optical and other radio telescopes — in hopes of finding some visible event linked to the FRBs — but had no luck.

Their research showed, however, that one of the most peculiar (and frustrating, for research purposes) traits of FRBs appears to be real: The signals, once arriving, never repeat themselves. Each one appears to be a singular event in space that will never happen again.

Originally published on Live Science.

Sudden shrieks of radio waves from deep space keep slamming into radio telescopes on Earth, spattering those instruments’ detectors with confusing data. And now, astronomers are using artificial intelligence to pinpoint the source of the shrieks, in the hope of explaining what’s sending them to Earth from — researchers suspect — billions of light-years across space.

Usually, these weird, unexplained signals are detected only after the fact, when astronomers notice out-of-place spikes in their data — sometimes years after the incident. The signals have complex, mysterious structures, patterns of peaks and valleys in radio waves that play out in just milliseconds. That’s not the sort of signal astronomers expect to come from a simple explosion, or any other one of the standard events known to scatter spikes of electromagnetic energy across space. Astronomers call these strange signals fast radio bursts (FRBs). Ever since the first one was uncovered in 2007, using data recorded in 2001, there’s been an ongoing effort to pin down their source. But FRBs arrive at random times and places, and existing human technology and observation methods aren’t well-primed to spot these signals.

Now, in a paper published July 4 in the journal Monthly Notices of the Royal Astronomical Society, a team of astronomers wrote that they managed to detect five FRBs in real time using a single radio telescope. [The 12 Strangest Objects in the Universe]

Wael Farah, a doctoral student at Swinburne University of Technology in Melbourne, Australia, developed a machine-learning system that recognized the signatures of FRBs as they arrived at the University of Sydney’s Molonglo Radio Observatory, near Canberra. As Live Science has previously reported, many scientific instruments, including radio telescopes, produce more data per second than they can reasonably store. So they don’t record anything in the finest detail except their most interesting observations.

Farah’s system trained the Molonglo telescope to spot FRBs and switch over to its most detailed recording mode, producing the finest records of FRBs yet.

Based on their data, the researchers predicted that between 59 and 157 theoretically detectable FRBs splash across our skies every day. The scientists also used the immediate detections to hunt for related flares in data from X-ray, optical and other radio telescopes — in hopes of finding some visible event linked to the FRBs — but had no luck.

Their research showed, however, that one of the most peculiar (and frustrating, for research purposes) traits of FRBs appears to be real: The signals, once arriving, never repeat themselves. Each one appears to be a singular event in space that will never happen again.

Originally published on Live Science.

via Space.com https://ift.tt/2CqOJ61

August 9, 2019 at 10:17AM

Teen Students Forced to Work Overtime Building Amazon Echo Devices In China

https://gizmodo.com/teen-students-forced-to-work-overtime-building-amazon-e-1837101059

In July, a 17-year-old high school student in China was sticking protective film over 3,000 Amazon Echo dots a day at the Foxconn factory in Hengyang. She was working ten hours a day and six days a week. And she was among more than 1,000 students employed by the factory to work overtime on Amazon’s devices.

“I tried telling the manager of my line that I didn’t want to work overtime,” the student, who went by the pseudonym Xiao Fang, told anonymous researchers who leaked their findings and transcripts of interviews with workers to Chinese Labor Watch. “But the manager notified my teacher and the teacher said if I didn’t work overtime, I could not intern at Foxconn and that would affect my graduation and scholarship applications at the school. I had no choice, I could only endure this.”

The China Labor Watch report, published on Thursday, covers a 2019 investigation into the Foxconn Hengang factory and the Guardian was allowed to review the underlying documents. Among the report’s findings was the claim that high school students ages 16 through 18 across a number of schools were recruited to work at the factory, and teachers were tasked with pressuring the teens into working overtime or night shifts. That often meant physical and verbal attacks on these interns, the report states.

Like Xiao, some of these interns were reportedly assigned the job of making Echo and Echo dot devices as well as Kindles and were employed for over two months to help fill a labor gap at the factory.

Xiao Chen, 18, was another student that interned at the Foxconn factory, according to the report. In September of last year, his vocational school suspended classes so that all the students could intern at the factory, of which some reported this to the Hengyang Education Bureau. Xiao’s second time interning was voluntary—he works night shifts and manufactures Echo devices to help pay off student fees. He works ten hours a day, six days a week.

The China Labor Watch investigation found that Foxconn had recruited 1,581 interns from vocational schools as of July 26. The interns were paid about $1.42 per hour, which was a decreased wage from the previous year. They also didn’t get any living stipends or bonuses, which they had in 2018. Teachers received a $425 subsidy from the factory, and schools were given $0.42 for each hour an intern worked, so there was certainly an incentive for both the factory and the school to log more hours.

While it isn’t illegal for a 16-year-old to work in China, it does violate the country’s labor law for them to work overtime or night shifts. In notes from a meeting addressing the issue of potentially missing production goals without the students working on prohibited shifts, management made it clear that they were aware of the issue. The Guardian quotes a Foxxcon official telling attendees of the meeting that, “Nightshift line leaders should check in with student interns and teachers more often, and report back any abnormal situation so that teachers can persuade students to work nightshifts and overtime.”

This isn’t the first time Foxconn has been mired in controversy over its illegal labor practices regarding young workers. In 2017, six students ages 17 to 19 claimed that they had been working 11-hour days at a Foxconn plant in China as part of a mandatory, three-month program with their school. The students were reportedly among a group of 3,000 student interns tasked with helping to build the new iPhone X.

When reached for comment, an Amazon spokesperson told Gizmodo: 

We do not tolerate violations of our Supplier Code of Conduct. We regularly assess suppliers, using independent auditors as appropriate, to monitor continued compliance and improvement—if we find violations, we take appropriate steps, including requesting immediate corrective action. We are urgently investigating these allegations and addressing this with Foxconn at the most senior level. Additional teams of specialists arrived on-site this week to investigate, and we’ve initiated weekly audits of this issue.

A Foxconn spokesperson paraphrased by The Guardian said that the company “would increase the number of regular workers and review salaries immediately.”

Beyond just violating labor laws in China, the practice of exploiting students to meet the production needs during peak season is especially shitty when you remember just how much money Amazon is going to make off of their low-paid, intensely grueling, and academically valueless labor.

via Gizmodo https://gizmodo.com

August 9, 2019 at 12:42PM

Tomorrow’s bionic eyes will have ‘Predator’ vision

https://www.engadget.com/2019/08/09/Second-sight-orion-bionic-eyes-predator-vision/

Whether through illness or injury, 36 million people suffer from blindness worldwide, and until just a decade ago those afflicted had little chance of regaining their sight. In 2009, doctors at the University of Manchester implanted the first Argus II bionic eye in a patient. Now, 10 years later, the makers of the Argus II are trialing a more capable artificial-vision system — one that’s implanted directly into the patient’s brain.

It’s called the Orion Visual Cortical Prosthesis System, and it’s been developed by Second Sight Medical Products. Like the Argus II before it, the Orion system consists of a small camera mounted on a pair of glasses to capture images, a video-processing unit to convert what the camera sees into electrical impulses the wearer can interpret and an implant that stimulates the user’s brain to create a perceived image. However, unlike the Argus II which used implants that clamped onto the patient’s optic nerves, the Orion’s implant sits directly on the brain itself.

This implant is installed via a small craniotomy in the back of the patient’s head, above the occipital lobe. "They put the electrode array in there between the two halves of the brain against the visual cortex," Second Sight CEO Will McGuire told Engadget. "Then they basically screw the electronics package into the skull, just next to the craniotomy." This electronics package contains a small transmission coil that wirelessly receives data and power from the system’s external parts.

The installation process requires an overnight hospital stay followed by a three- to four-week recovery period before the unit is turned on. At that point the user is fitted with glasses, the various components are connected and "really what you’re hoping to get then is for them to start seeing spots of light, phosphenes, from some of the electronics," McGuire said. "But then there’s quite a bit of work that has to happen."

Those phosphenes are the result of the implant’s 60 electrode array electrically stimulating the visual cortex and each one needs to be individually tuned to provide the most distinct and discernable spot of light possible. This process requires weeks to months of adjustments to perfect. The next step is establishing a spatial map, ensuring that each electrode is energizing the correct spot on the patient’s brain. This involves having the patient repeatedly tap the specific spot the surface on a tablet when, say, electrode 32 is energized.

"It’s done over and over for each electrode — we really have to train them not to move their eyes, which is the natural response when you see light," Nik Talbot, Second Sight’s senior director, implant and R&D, explained. "As they move their eyes, the brain is expecting to see something different, where in fact, they’re not going to see anything different because they’re taking in everything through the camera. So they have to be taught to keep their eyes looking forward, the same as the camera."

Once the mapping is complete and confirmed accurate, that data are fed into an algorithm that "can be used to convert video into stimulation parameters to replicate what the camera is seeing," he continued. Then it’s a small matter of spending a few more months getting used to the system and learning how to use it most efficiently.

The Orion is undergoing an Early Feasibility Study at UCLA Medical Center and the Baylor College of Medicine in Houston to ensure that the technology is safe for larger trials. Six patients, five men and one woman, were outfitted with the prosthesis in January 2018. Each of them is completely bilaterally blind. 13 months after the implants were installed only one patient reported a serious adverse effect, specifically, a seizure.

"Overall, for that number of subjects at that point, we feel that’s very good and very safe," McGuire remarked. "And I think the physician community would agree with it."

However, the road to FDA approval is a long one, despite being part of the agency’s Breakthrough Device Program. "The FDA gives that designation to technologies that are that are meeting a significant unmet clinical need," Talbot explained. "So there’s no other option out there, whether it be a therapy or whether it be some sort of diagnostic tool." Being the first and only implantable artificial-vision system is certainly enough to qualify. This designation also provides the research team with more direct, high-priority interactions with the FDA as they seek a path toward approval. McGuire hopes to have an agreement finalized with the FDA in the second half of this year. The team can’t yet disclose when they expect the devices to make it to market, however.

What’s most exciting is where the Second Sight team plans to take this technology next. In addition to packing more and more electrodes into the array to improve the image fidelity, expanding the electrode count to between 150 and 200 channels.

"We think we can make some significant improvements just on the software side," McGuire said. "And then there’s other technologies that are being developed out there that we’re not necessarily developing but we think to play a key role with artificial divisions. And we’ve got partners who are working on some of these right now."

For example, the team is looking into is distance filtering. Because the image input comes from a single camera, the patient has no depth perception. "If we had two cameras perhaps we could give them the option of only seeing objects that are within 10 feet or objects that are greater than 10 feet," Talbot said. "What that would do would clear up the image for them. Right now, they’re picking up things that are near and far. That can distort what they’re seeing and make it more difficult to interpret."

The team is also investigating face- and object-recognition features. Because the image that the user sees is still decidedly low-fidelity, incorporating these technologies would enable the system to assist its wearer beyond stimulating their brain. "They could have this object-recognition software tell them in their ear, iPhone or coffee cup" when the item is in the camera’s field of view, McGuire said.

Then there’s the Predator vision. Second Sight is looking into integrating a thermal camera, which would enable the user to see in infrared, into its system. "It would be good for them to have that as kind of a mode perhaps, in which they could switch to thermal imaging," McGuire said. "And they can identify where people are in the room, day or night, more easily. They could maybe identify the hot part of a stove or cup of coffee, things like that."

We’re still years away from having the technology behind Geordi LaForge’s visor, but enabling the visually impaired to hunt an elite team of commandos through the South American rainforest is a pretty solid tradeoff.

via Engadget http://www.engadget.com

August 9, 2019 at 11:06AM

Mod turns your Tesla into a rolling surveillance system

https://www.engadget.com/2019/08/10/tesla-surveillance-detection-scout-mod/

The Sentry Mode on Tesla cars has been helpful for catching thieves, but one security researcher wants to illustrate the advantages and pitfalls of taking that camera system to its logical conclusion. Tevora’s Truman Kain has developed a Surveillance Detection Scout mod that effectively turns a Model 3 or Model S into a rolling observation deck. The project plugs an NVIDIA Jetson Xavier computer into a USB port and uses open source machine learning to detect both faces and license plates. It sends a phone notification if it repeatedly spots the same plate or person, giving you a warning that someone may be tailing you or preparing to steal your car.

The Scout’s alerts (sent through IFTTT) are delayed by about a minute due to the time it takes to record video, and you currently have to create your own web server for this to work in the first place. However, it’s also using off-the-shelf hardware and code that doesn’t require tearing your car open. In theory, anyone who’s reasonably tech-savvy could use this.

Whether or not they do is another matter. It could help thwart thieves, stalkers and vandals, but there’s also the risk of flagging innocent people who just happen to share the same drive or are curious about the car. In some states, such as Georgia and New Hampshire, it might also be deemed illegal as an automatic license plate reader.

There are also privacy implications. It wouldn’t take much to modify the code to create a network of cars that could track people across wide areas, and even a single car might contain a wealth of sensitive data. In many ways, the Scout makes a case for limiting access to car cameras — there’s conspicuous room for abuse.

Source: Defcon, Wired

via Engadget http://www.engadget.com

August 10, 2019 at 05:42PM