Malware Uses Router LEDs to Air Gap Data From Secure Networks

This malware will intercept specific data passing through the router, break it down into its binary format, and use a router LED to signal the data to a nearby attacker, with the LED turned on standing for a binary one and the LED turned off representing a binary zero.

An attacker with a clear line of sight to the equipment can record the blinking operation. This “attacker” can be a security camera, a company insider, recording equipment mounted on a drone, and various other setups where a video recording device has a clear sight of the router or switch’s blinking LEDs.
The more router LEDs, the higher the exfiltration speed

During their tests, researchers say they’ve tested various configurations for the video recording setup, such as optical sensors, security/CCTV cameras, extreme cameras, smartphone cameras, wearable/hidden cameras, and others.

The research team says it achieved the best results with optical sensors because they are capable of sampling LED signals at high rates, enabling data reception at a higher bandwidth than other typical video recording equipment.

Researchers say that by using optical sensors, they were able to exfiltrate data at a rate of more than 1000 bit/sec per LED. Since routers and switches have more than one LED, the exfiltration speed can be increased many times over if multiple LEDs are used for data exfiltration. Basically, the more ports the router and switch has, the more data the malware can steal from the device.

Source: Malware Uses Router LEDs to Steal Data From Secure Networks

Scientists Are Now Using AI to Predict Autism in Infants

Despite all the headway that science has made in understanding autism in recent years, knowing which children will one day develop autism is still almost impossible to predict. Children diagnosed with autism appear to behave normally until around two, and until then there is often no indication that anything is wrong.
[…]
In a paper out Wednesday in Science Translational Medicine, researchers from the University of North Carolina at Chapel Hill and Washington University School of Medicine scanned the brains of 59 high-risk, 6-month-old infants to examine how different regions of the brain connect and interact. At age two, after 11 of those infants had been diagnosed with autism, they scanned their brains again.
[…]
Using this method, researchers were able to accurately predict nine of the 11 infants who would wind up with an autism diagnosis. And it did not incorrectly predict any of the children who were not autistic.

“Our treatments of autism today have a modest impact at best,” said Joseph Piven, a psychiatrist at UNC Chapel Hill and author of the study, told Gizmodo. “People with autism continue to have challenges throughout their life. But there’s general consensus in the field that diagnosing earlier means better results.”

Source: Scientists Are Now Using AI to Predict Autism in Infants

The open source community is nasty and that’s just the docs

The 2017 Open Source Survey was hosted on GitHub, which “collected responses from 5,500 randomly sampled respondents sourced from over 3,800 open source repositories” and then added “over 500 responses from a non-random sample of communities that work on other platforms.” The questionnaire was also made available in Traditional Chinese, Japanese, Spanish, and Russian.

Interestingly, those behind the survey broke out “negative incidents” into a separate spreadsheet in that trove. That data reveals that 18 per cent of open source contributors have “personally experienced a negative interaction with another user in open source”. Fully half of participants “have witnessed one between other people”.

Most of the negative behaviour is explained as “rudeness”, which has been experienced witnessed by 45 per cent of participants and experienced by 16 per cent. GitHub’s summary of the survey says really nasty stuff like “sexual advances, stalking, or doxxing are each encountered by less than five per cent of respondents and experienced by less than two per cent (but cumulatively witnessed by 14%, and experienced by three per cent).” Twenty five per cent of women respondents reported experiencing “language or content that makes them feel unwelcome”, compared to 15 per cent of men.

This stuff has consequences: 21 per cent of those who see negative behaviour bail from projects they were working on.

Source: The open source community is nasty and that’s just the docs