Threat intelligence
The Microsoft Threat Intelligence community is made up of world-class experts, security researchers, analysts, and threat hunters who analyze 100 trillion signals daily to discover threats and deliver timely and timely, relevant insight to protect customers. See our latest findings, insights, and guidance.
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Analyzing open-source bootloaders: Finding vulnerabilities faster with AI
Using Microsoft Security Copilot to expedite the discovery process, Microsoft has uncovered several vulnerabilities in multiple open-source bootloaders impacting all operating systems relying on Unified Extensible Firmware Interface (UEFI) Secure Boot. -
Connect with Microsoft Security at Black Hat USA 2024
Join Microsoft Security leaders and other security professionals from around the world at Black Hat USA 2024 to learn the latest information on security in the age of AI, cybersecurity protection, threat intelligence insights, and more. -
Mitigating Skeleton Key, a new type of generative AI jailbreak technique
Microsoft recently discovered a new type of generative AI jailbreak method called Skeleton Key that could impact the implementations of some large and small language models. -
AI jailbreaks: What they are and how they can be mitigated
Microsoft security researchers, in partnership with other security experts, continue to proactively explore and discover new types of AI model and system vulnerabilities. -
How Microsoft discovers and mitigates evolving attacks against AI guardrails
Read about some of the key issues surrounding AI harms and vulnerabilities, and the steps Microsoft is taking to address the risk. -
Discover a new era of security with Microsoft at RSAC 2023
Microsoft Security will be at the 2023 RSA Conference and we’d love to connect with you there. -
AI-driven adaptive protection against human-operated ransomware
We developed a cloud-based machine learning system that, when queried by a device, intelligently predicts if it is at risk, then automatically issues a more aggressive blocking verdict to protect the device, thwarting an attacker’s next steps. -
Seeing the big picture: Deep learning-based fusion of behavior signals for threat detection
Learn how we’re using deep learning to build a powerful, high-precision classification model for long sequences of wide-ranging signals occurring at different times. -
New machine learning model sifts through the good to unearth the bad in evasive malware
Most machine learning models are trained on a mix of malicious and clean features.