GitHub added npm staged publishing with mandatory 2FA approval to reduce software supply chain attack risks.
Get the latest international news and world events from around the world.
FBI warns of Kali365 phishing service targeting Microsoft 365 accounts
The FBI is warning about the Kali365 phishing-as-a-service platform (PhaaS) that is used to hijack Microsoft 365 accounts by abusing OAuth device code authentication to steal session tokens and bypass multi-factor authentication (MFA).
According to the FBI PSA, Kali365 first emerged in April 2026 and is distributed via Telegram channels for cybercriminals seeking an easier way to compromise Microsoft 365 accounts without stealing passwords or intercepting MFA codes.
The platform uses device code phishing, an increasingly popular method that abuses Microsoft’s legitimate OAuth 2.0 Device Authorization grant flow to gain access to Microsoft Entra and Microsoft 365 accounts.
Anthropic’s restricted Claude Mythos model may be coming to Claude Code
Anthropic appears to be preparing for the public rollout of “Mythos,” which was announced in April as a restricted model that poses major security risks to private and public software.
On April 7, Anthropic announced the Mythos in early preview and called it a new frontier model with strikingly advanced capabilities in computer security tasks.
Anthropic said the Mythos model shows major improvements in code reasoning and autonomy, far above its current flagship model, Opus 4.7.
Dark personality traits linked to a higher tolerance for morally questionable behaviors
The study contributes to the scientific knowledge about dark personality traits. However, the study was conducted on a relatively small group of students and solely based on self-reports. Studies on larger groups, involving other demographics, and those using more objective measures of endorsement of morally debatable behaviors might not yield identical results.
The paper, “Relationships between the Dark Triad and Justification of Morally Debatable Behaviors in College Students,” was authored by Emma P. Paulson and Terry F. Pettijohn II.
Childhood trauma predicts higher risk of combined mental and physical illness in later life
Researchers modeled the specific dosage of trauma to highlight an escalating relationship between the sheer volume of trauma and later health vulnerabilities. Small amounts of childhood adversity corresponded to relatively modest increases in health risks. However, once a person’s trauma score passed four distinct adverse experiences, the upward trajectory of their health risk accelerated rapidly.
The researchers also investigated the stepping stones connecting early trauma to later disease onset. Using a statistical technique called mediation analysis, they looked for intermediate health issues that acted as bridges over the span of a lifetime. They found that developing either a single physical illness or isolated depression in early adulthood often served as an indirect pathway to combined disease in older age.
For individuals with the highest amounts of early trauma, early-onset depression played a particularly strong bridging role. An initial diagnosis of depression frequently paved the way for additional physical conditions as time went on. These findings align with biological theories suggesting that severe childhood stress permanently disrupts the body’s immune regulation and stress hormone pathways.
Some People Can ‘See’ Time, Thanks to a Hidden Superpower—And It’s Quietly Shaping Their Perception
This trait could shed light on the mysteries of human perception. Does it live within you?
MIT researchers use AI to uncover atomic defects in materials
In biology, defects are generally bad. But in materials science, defects can be intentionally tuned to give materials useful new properties. Today, atomic-scale defects are carefully introduced during the manufacturing process of products like steel, semiconductors, and solar cells to help improve strength, control electrical conductivity, optimize performance, and more.
But even as defects have become a powerful tool, accurately measuring different types of defects and their concentrations in finished products has been challenging, especially without cutting open or damaging the final material. Without knowing what defects are in their materials, engineers risk making products that perform poorly or have unintended properties.
Now, MIT researchers have built an AI model capable of classifying and quantifying certain defects using data from a noninvasive neutron-scattering technique. The model, which was trained on 2,000 different semiconductor materials, can detect up to six kinds of point defects in a material simultaneously, something that would be impossible using conventional techniques alone.