Explore the intersection of AI and cybersecurity. Stay informed on AI-driven security trends, tools, and threats in the ever-evolving digital landscape.
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Background for this topic.
Artificial intelligence (AI) describes computer systems that perform tasks such as recognizing patterns, making predictions, understanding language, or generating content. In security reporting, the term commonly includes machine-learning models used for detection and analysis, as well as generative AI applications that produce text, code, images, or other outputs.
AI can help analyze security telemetry, prioritize vulnerabilities, and support investigations, but its outputs can be wrong or manipulated. Important attack surfaces include prompt injection that steers an application into unintended actions, sensitive data being exposed through prompts or model outputs, and excessive permissions granted to AI systems that use external tools. Models can also be degraded by poisoned training data or evaded with carefully crafted inputs. Practitioners should protect training and operational data, limit model access and tool permissions, test for adversarial behavior, and require appropriate human validation before high-impact decisions.
Microsoft is now testing WebAuthn API updates that add support for support for using third-party passkey providers for Windows 11 passwordless authentication. [...]
Microsoft announced today that its controversial AI-powered Recall feature is finally rolling out to Windows Insiders in the Dev Channel using Snapdragon-powered Copilot+ PCs. [...]
Microsoft announced today at its Ignite annual conference in Chicago, Illinois, that it's expanding its bug bounty programs with Zero Day Quest, a new hacking event focusing on cloud and AI products and platforms. [...]