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 its AI-powered Recall feature on AMD and Intel-powered Copilot+ PCs enrolled in the Windows 11 Insider program. [...]
The popular Ultralytics YOLO11 AI model was compromised in a supply chain attack to deploy cryptominers on devices running versions 8.3.41 and 8.3.42 from the Python Package Index (PyPI) [...]
The FBI warns that scammers are increasingly using artificial intelligence to improve the quality and effectiveness of their online fraud schemes, ranging from romance and investment scams to job hiring schemes. [...]
Google Chrome's upcoming feature uses AI to provide a summary of reviews from independent websites about the store or website you're visiting. [...]