Lifeboat Foundation

“When a new user logs into the server, it immediately stops all ‘noisy’ activities, lying dormant until the server is idle again. After execution, it deletes its binary and continues to run quietly in the background as a service.”

It’s worth noting that some aspects of the campaign were disclosed last month by Cado Security, which detailed an activity cluster that targets internet-exposed Selenium Grid instances with both cryptocurrency mining and proxyjacking software.

Specifically, the fileless perfctl malware has been found to exploit a security flaw in Polkit (CVE-2021–4043, aka PwnKit) to escalate privileges to root and drop a miner called perfcc.

Apple’s iOS 18.0.1 fixes a VoiceOver password vulnerability and an audio bug in iPhone 16. Update now!

Cloudflare mitigates a record-breaking 3.8 Tbps DDoS attack, marking a surge in global cyber threats.

LiteSpeed Cache plugin vulnerability (CVE-2024–47374) exposes WordPress sites to XSS attacks. Update to version 6.5.1 now.

Google enhances Pixel security in Android 14 to block baseband attacks, 2G downgrades, and SMS Blaster fraud.

MIT researchers have developed a miniature, chip-based “tractor beam,” like the one that captures the Millennium Falcon in the film “Star Wars,” that could someday help biologists and clinicians study DNA, classify cells, and investigate the mechanisms of disease.

Small enough to fit in the palm of your hand, the device uses a beam of light emitted by a silicon-photonics chip to manipulate particles millimeters away from the chip surface. The light can penetrate the glass cover slips that protect samples used in biological experiments, enabling cells to remain in a sterile environment.

Traditional optical tweezers, which trap and manipulate particles using light, usually require bulky microscope setups, but chip-based optical tweezers could offer a more compact, mass manufacturable, broadly accessible, and high-throughput solution for optical manipulation in biological experiments.

Workplace AI tools can do tasks by themselves. Getting them to stop is the problem.

The Hubbard model is a studied model in condensed matter theory and a formidable quantum problem. A team of physicists used deep learning to condense this problem, which previously required 100,000 equations, into just four equations without sacrificing accuracy. The study, titled “Deep Learning the Functional Renormalization Group,” was published on September 21 in Physical Review Letters.

Dominique Di Sante is the lead author of this study. Since 2021, he holds the position of Assistant Professor (tenure track) at the Department of Physics and Astronomy, University of Bologna. At the same time, he is a Visiting Professor at the Center for Computational Quantum Physics (CCQ) at the Flatiron Institute, New York, as part of a Marie Sklodowska-Curie Actions (MSCA) grant that encourages, among other things, the mobility of researchers.

He and colleagues at the Flatiron Institute and other international researchers conducted the study, which has the potential to revolutionize the way scientists study systems containing many interacting electrons. In addition, if they can adapt the method to other problems, the approach could help design materials with desirable properties, such as superconductivity, or contribute to clean energy production.

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A collaboration of a neurologist, a computer scientist, and a philosopher has just put forward a new theory of consciousness. It is based on the idea of causal models. The authors claim boldly that their idea solves the hard problem of consciousness and explains why zombies don’t exist in nature. Really? I’ve had a look.

Continue reading “New Theory of Consciousness Explains Why Zombies Don’t Exist” »