Ire identifies another LOTUSLITE specimen
Project Ire examined a timely malware sample and determined its intent through reverse engineering—identifying LOTUSLITE characteristics even as most major EDR tools did not detect it.
Microsoft Research Blog
Ire identifies another LOTUSLITE specimen
Project Ire examined a timely malware sample and determined its intent through reverse engineering—identifying LOTUSLITE characteristics even as most major EDR tools did not detect it.
Recent Posts
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Data Formulator 0.7: AI-powered data analytics for enterprise data
Data Formulator introduces AI-powered analytics for enterprise data workflows. Data teams can easily bring enterprise data into an AI-ready workspace where users can explore, analyze, and visualize data with AI agents to turn raw data into actionable insights.
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Extending Human Intelligence Through AI
May 27, 2026 | Ken Archer and Harald WiltscheUnderstanding AI as an extension of human intelligence—not a replacement for it—offers a more grounded path for building trustworthy AI systems.
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MagenticLite, MagenticBrain, Fara1.5: An agentic experience optimized for small models
May 21, 2026 | Microsoft Research AI FrontiersMagenticLite is an agentic system for small models that works across the browser and local file system in a single workflow. It combines specialized models and orchestration to support efficient agentic performance on everyday tasks.
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Vega: Zero-knowledge proofs for digital identity in the age of AI
May 21, 2026 | Srinath SettyVega turns a full credential into a single proof, sharing only what is needed and nothing more, with performance that works in real apps.
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Further Notes on Our Recent Research on AI Delegation and Long-Horizon Reliability
Our recent paper, “LLMs Corrupt Your Documents When You Delegate”, has generated discussion about the reliability of AI systems in delegated workflows. We appreciate the interest in this work and want to clarify several important points about what the paper does—and does not—claim. The research…
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mimalloc: A new, high-performance, scalable memory allocator for the modern era
May 13, 2026 | Daan Leijenmimalloc is an open-source, modern, scalable memory allocator that is a drop-in replacement for malloc and free. It is relatively small (~12K lines), with clear internal data structures, and is easy to build and integrate into other projects. It provides bounded worst-case allocation times (up…
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GridSFM: A new, small foundation model for the electric grid
May 13, 2026Introducing GridSFM, a small foundation model that can predict AC optimal power flow in milliseconds, boosting efficiency and unlocking cost savings. Learn how GridSFM gives grid operators direct visibility into congestion, stability, and system health.
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Advancing AI for materials with MatterSim: experimental synthesis, faster simulation, and multi-task models
May 12, 2026MatterSim is expanding what AI can do for materials science—from faster large-scale simulations to MatterSim-MT, a new multi-task model for simulating properties beyond potential energy surfaces alone.
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SocialReasoning-Bench: Measuring whether AI agents act in users’ best interests
May 11, 2026Using SocialReasoning Bench, we observed a stable pattern across models—agents execute competently, but fail to consistently improve the user’s position, even with explicit instructions to optimize for user interest.
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Building realistic electric transmission grid dataset at scale: a pipeline from open dataset
May 8, 2026Microsoft Research is excited to release an open dataset of approximate transmission topology of the U.S. power grid derived from publicly available data. The ability to study transmission-level power grid behavior is essential for modern power systems research. Analyses of congestion, transmission expansion, demand growth,…
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Microsoft at NSDI 2026: Advances in large-scale networked systems
May 5, 2026 | Sujata BanerjeeMicrosoft researchers share advances in building and operating large-scale distributed systems, spanning datacenters, networking, and the growing intersection with AI during NSDI ’26.
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