A fake VS Code extension posing as a Moltbot AI assistant installed ScreenConnect malware, giving attackers persistent remote access to developer syst
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Initial access hackers switch to Tsundere Bot for ransomware attacks
A prolific initial access broker tracked as TA584 has been observed using the Tsundere Bot alongside XWorm remote access trojan to gain network access that could lead to ransomware attacks.
Proofpoint researchers have been tracking TA584’s activity since 2020 and say that the threat actor has significantly increased its operations recently, introducing a continuous attack chain that undermines static detection.
Tsundere Bot was first documented by Kaspersky last year and attributed to a Russian-speaking operator with links to the 123 Stealer malware.
New sandbox escape flaw exposes n8n instances to RCE attacks
Two vulnerabilities in the n8n workflow automation platform could allow attackers to fully compromise affected instances, access sensitive data, and execute arbitrary code on the underlying host.
Identified as CVE-2026–1470 and CVE-2026–0863, the vulnerabilities were discovered and reported by researchers at DevSecOps company JFrog.
Despite requiring authentication, CVE-2026–1470 received a critical severity score of 9.9 out of 10. JFrog explained that the critical rating was due to arbitrary code execution occurring in n8n’s main node, which allows complete control over the n8n instance.
Wave of Suicides Hits as India’s Economy Is Ravaged by AI
As Rest of World reports, rising anxiety over the influence of AI, on top of already-grueling 90-hour workweeks, has proven devastating for workers. While it’s hard to single out a definitive cause, a troubling wave of suicides among tech workers highlights these unsustainable conditions.
Complicating the picture is a lack of clear government data on the tragic deaths. While it’s impossible to tell whether they are more prevalent among IT workers, experts told Rest of World that the mental health situation in the tech industry is nonetheless “very alarming.”
The prospect of AI making their careers redundant is a major stressor, with tech workers facing a “huge uncertainty about their jobs,” as Indian Institute of Technology Kharagpur senior professor of computer science and engineering Jayanta Mukhopadhyay told Rest of World.
10,000 Brain Scans Reveal Why Your Memory Gets Worse With Age
Our episodic memory – the ability to recall past events and experiences – is known to decline as we age. Exactly how and why has remained something of a mystery, and a recent study goes some way towards solving it.
Researchers led by a team from the University of Oslo in Norway wanted to see whether this memory loss affects everyone equally, or if it might be driven by individual risk factors, such as the APOE ε4 gene linked to Alzheimer’s disease.
The scale of their analysis is impressive. The scientists combined data from 3,737 cognitively healthy participants, tracked over several years, including 10,343 MRI scans and 13,460 memory assessments, from multiple long-running studies.
Key to human intelligence lies in how brain networks work together, neuroimaging study suggests
Modern neuroscience understands the brain as a set of specialized systems. Aspects of brain function such as attention, perception, memory, language, and thought have been mapped onto distinct brain networks, and each has been examined largely in isolation.
While this approach has yielded major advances, it has left unresolved one of the most basic facts about human cognition: its overall unity as an integrated system.
Now, researchers at the University of Notre Dame have conducted a neuroimaging study to investigate how the brain is organized and how that integrated system gives rise to intelligence. Their study was published in the journal Nature Communications.
Deep-learning algorithms enhance mutation detection in cancer and RNA sequencing
Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning algorithms, ClairS-TO and Clair3-RNA, that significantly advance genetic mutation detection in cancer diagnostics and RNA-based genomic studies.
The pioneering research team, led by Professor Ruibang Luo from the School of Computing and Data Science, Faculty of Engineering, has unveiled two groundbreaking deep-learning algorithms—ClairS-TO and Clair3-RNA—set to revolutionize genetic analysis in both clinical and research settings.
Leveraging long-read sequencing technologies, these tools significantly improve the accuracy of detecting genetic mutations in complex samples, opening new horizons for precision medicine and genomic discovery. Both research articles have been published in Nature Communications.