SAP npm packages poisoned on April 29, 2026 + AES-256-GCM encrypted credential theft + AI coding tools abused for spread.
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GitHub fixes RCE flaw that gave access to millions of private repos
In early March, GitHub patched a critical remote code execution vulnerability (CVE-2026–3854) that could have allowed attackers to access millions of private repositories.
The flaw was reported on March 4, 2026, by researchers at cybersecurity firm Wiz through GitHub’s bug bounty program. GitHub Chief Information Security Officer Alexis Wales said the company’s security team reproduced and confirmed the vulnerability within 40 minutes and deployed a fix to GitHub.com less than two hours after receiving the report.
CVE-2026–3854 affects GitHub.com, GitHub Enterprise Cloud, GitHub Enterprise Cloud with Data Residency, GitHub Enterprise Cloud with Enterprise Managed Users, and GitHub Enterprise Server.
Popular WordPress redirect plugin hid dormant backdoor for years
The Quick Page/Post Redirect plugin, installed on more than 70,000 WordPress sites, had a backdoor added five years ago that allows injecting arbitrary code into users’ sites.
The malware was uncovered by Austin Ginder, the founder of WordPress hosting provider Anchor, who found it after 12 infected sites on his fleet triggered a security alert.
Quick Page/Post Redirect plugin, available on WordPress.org for several years, is a basic utility plugin used for creating redirects in posts, pages, and custom URLs.
Hackers arrested for hijacking and selling 610,000 Roblox accounts
The Ukrainian police have arrested three individuals who hacked more than 610,000 Roblox gaming accounts and sold them for a profit of $225,000.
The arrests were made by the police in Lviv after conducting ten searches on targeted locations, seizing $35,000 in cash, 37 mobile phones, 11 desktop computers, seven laptops, five tablets, and four USB drives.
Although the police did not specify the game platform targeted by the hackers, aged 19, 21, and 22, the Prosecutor General’s Office stated that it was Roblox.
“An Update from the Sparks Brain Preservation” — April 30th Service
Our speaker this month is Jordan Sparks with the Sparks Brain Preservation organization in Oregon. Our event is in ZOOM Only, no in person meeting this month, meeting ins ZOOM on Thursday, April 30th, opening at 6:00 PM for our social hour, with the main event starting at 7:00 PM Eastern Time Jordan will tell us about his project, which was formerly the Oregon Brain Preservation, and before that Jordan formed Oregon Cryonics. This is an entirely different type of bio-stasis then cryonics. Their stated goal is to preserve the structure of the entire brain at a fine ultrastructural level. This includes the synaptic architecture as well as detailed molecular information such as protein post-translational modifications, cellular epigenetic patterns, and subcellular distributions of molecules.
The Entrepreneurial University
More academic and nonprofit labs should act as spinoff factories — both creating innovative foundational technologies *and* pushing these technologies forward towards the entrepreneurial translation needed to truly change the world for the better.
A research university emphasizes entrepreneurial science—and spawns start-ups in fields as varied as genetic medicine, humanoid robotics and carbon-catching materials.
Mapping Gene Variants Reveals New Neurodevelopmental Condition
By mapping all the possible variations in a single gene, researchers have uncovered a previously hidden neurodevelopmental condition.
ReNU syndrome is a rare, inherited neurodevelopmental disorder identified in 2024 that affects brain function, development, and motor skills and is predicted to affect tens of thousands of individuals worldwide.
Not all Alzheimer’s leads to dementia
One possible explanation is that resilient brains are better at repairing themselves during Alzheimer’s. “Perhaps they can add new brain cells to a network that is degenerating”, the author says.
This idea is linked to a process called adult neurogenesis, which refers to the birth of new brain cells (neurons) in the adult brain. It has been well-established in other animals, but its existence in humans has been debated for years.
To study this, the team used human brain tissue from the Netherlands Brain Bank, which collects and stores donated brain samples for research. They included brains from control donors with no brain pathology, Alzheimer’s patients, and individuals with Alzheimer’s pathology who remained resilient to developing dementia.
The team focused on a small part of the brain’s memory center, likely one of the few areas where these new brain cells could form. “These cells are extremely rare, so we had to develop new ways to find them,” the author says. “We really zoomed in on the exact spot where we expected them to be.”
The team found what they were looking for: so-called “immature” neurons. These cells resemble young, not fully developed neurons. “Even at an average age of over 80, we still found these immature neurons in all groups,” the author says.
But the biggest surprise came next. While the team had expected to find much more of these cells in the resilient group than in the Alzheimer’s patients, the difference was not as big as expected.
Surprisingly, the team found that the key difference lies in how the immature neurons behave. “In resilient individuals, these cells seem to activate programs that help them survive and cope with damage,” the author says. “We also see lower signals related to inflammation and cell death.”
Brain-inspired approach can teach AI to doubt itself just enough to avoid overconfidence
Most contemporary artificial intelligence (AI) systems learn to complete tasks via machine learning and deep learning. Machine learning is a computational approach that allows models to uncover patterns in data that are useful for making predictions. Deep learning, on the other hand, is a subset of machine learning that entails the use of multi-layered neural networks, which can autonomously extract features and learn complex patterns from unstructured data, sometimes with little or no human supervision.
Many AI systems trained with these approaches also produce confidence scores for their predictions. These scores are essentially estimates of how probable it is for a specific prediction to be accurate. Past studies suggest that in many cases, AI systems are overconfident and assign high confidence scores to wrong answers, or even present inaccurate information as a fact. This limits their reliability, particularly in high-stakes applications where wrong predictions can have serious consequences.
Researchers at the Korea Advanced Institute of Science and Technology recently introduced a new brain-inspired training approach that could yield more realistic AI confidence estimates. Their proposed strategy, introduced in a paper published in Nature Machine Intelligence, entails briefly training artificial neural networks on random noise (i.e., data with no meaningful patterns) and arbitrary outputs, so that they can learn to produce more realistic confidence estimates before learning specific tasks.