Microsoft

StealC and Amadey: Breaking down infostealers and the cybercrime services that deliver them

On June 24, 2026, Microsoft’s Digital Crimes Unit (DCU) facilitated the takedown, suspension, and blocking of domains that ...
Microsoft

Guarding AI memory

Microsoft takes a defense-in-depth approach to protect AI memory spanning every layer of the stack: storage, retrieval, model ...
Security Boulevard

When AI Agents Become Bots: A Field Report from the Authentication Layer

Security vendors and their customers have spent considerable time debating where to draw the line between “legitimate” AI agents and “malicious” bots. A 31-day campaign against a major consumer ...
Tom's Hardware on MSN

Hades malware campaign now tricks AI bots by injecting text about biological and nuclear weapons

This is probably the dictionary illustration for "deceptively simple." ...
IEEE

Adversarial Challenges in Network Intrusion Detection Systems: Research Insights and Future Prospects

Abstract: Machine learning has brought significant advances in cybersecurity, particularly in the development of Intrusion Detection Systems (IDS). These improvements are mainly attributed to the ...
Nature

Genome-guided generative adversarial learning enables nanopore adaptive sequencing

Nanopore adaptive sequencing enables real-time target enrichment, yet current deep-learning methods require costly, sample-specific experimental training data. To address this, we developed GANBase, a ...
CNAS

Adversarial Distillation

The Chinese Communist Party (CCP) views artificial intelligence (AI) as central to strategic competition with the United States and is pursuing every means to strengthen its AI ecosystem. China’s base ...
IEEE

Defenses in Adversarial Machine Learning: A Systematic Survey From the Lifecycle Perspective

Abstract: Adversarial phenomena have been widely observed in machine learning (ML) systems, especially those using deep neural networks. These phenomena describe situations where ML systems may ...