Coinspect confirms over $5M stolen via the Ill Bloom flaw. Weak seed generation left older mobile and browser-extension wallets exposed.
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Ransomware Negotiator Gets 70 Months in Prison for Aiding BlackCat Attacks
A 41-year-old former ransomware negotiator has been sentenced to nearly six years (i.e., 70 months) in prison in the U.S. for their role in conspiring with the now-defunct BlackCat ransomware operators to extort multiple victims and working with two other cybersecurity professionals to target additional victims in 2023.
In a sentencing memorandum, federal prosecutors described Martino as a “double agent working to maximize the harm to his clients and the financial gain to cybercriminals who paid him a part of the ransom.”
Angelo Martino, 41, of Land O’Lakes, Florida, pleaded guilty to one-count information charging him with conspiring to interfere with interstate commerce through extortion back in April. The defendant worked as a negotiator on behalf of five different ransomware victims, while providing BlackCat attackers with confidential information regarding their negotiating position and strategy without their knowledge or permission.
Microsoft expects more Windows security updates from AI-discovered flaws
Microsoft says Windows users should expect to see an increase in security updates as the company increasingly relies on artificial intelligence to discover vulnerabilities in its codebase.
In a blog post published today, Microsoft said advances in AI have significantly accelerated vulnerability discovery, allowing engineers to identify more security issues before they can be exploited in zero-day attacks.
“The pace of vulnerability discovery is changing with advances in AI making it possible to find more issues, faster, across more code, with new mechanisms that can accelerate both discovery and analysis,” Microsoft said.
OpenMandriva Linux says contributor tried to sabotage the project
The OpenMandriva Linux project announced that it was the target of an attempted act of internal sabotage after a dispute among contributors.
The attempted destructive action extended from wiping GitHub repositories to pushing an empty package that could have damaged users’ systems.
OpenMandriva is an independent, community-run Linux distribution, forked from Mandriva Linux in 2012 and maintained by the OpenMandriva Association.
Plain language AI workflow tool could cut cloud energy use and costs dramatically
Agentic workflows are artificial intelligence-powered software systems that chain together multiple models and external tools to tackle complicated tasks, like analyzing a video and answering questions about it. But the way these highly fragmented systems are designed and deployed often causes inefficiencies that can lead to wasted computation, energy and cost.
To improve efficiency, researchers from MIT and Microsoft developed an intelligent system that streamlines the process of designing agentic workflows and automatically optimizes how those workflows are implemented. With this new method, a developer can describe what they want the agentic workflow to do in plain language, without needing to specify all the details of their application in advance.
The system automatically figures out the best models and tools to use, as well as the ideal hardware configuration and computational resource allocation when the workflow is executed by a cloud provider. It adjusts those configurations on the fly based on each user’s priorities, such as minimizing costs or maximizing speed.
New physics-based machine-learning method speeds search for 2D quantum materials
Researchers at The University of Manchester have developed a new computational approach to help identify two-dimensional materials that may host unusual quantum behavior. The work, published in Science Advances, focuses on materials with “flat bands,” electronic states where electrons have very little kinetic energy. In these materials, interactions between electrons can become much more important, creating conditions linked to phenomena such as magnetism, unconventional superconductivity and topological electronic behavior.
Finding real materials with flat bands from large datasets is difficult. Conventional searches often rely on density functional theory calculations, which can reveal a material’s electronic structure but are time-consuming when applied across thousands of possible candidates.
The Manchester team took a different route. They developed a physics-informed scoring system that captures two signatures of flat-band behavior, low band dispersion and a strong peak in the density of states, then trained a model to estimate that score directly from atomic structure.